BIG BAD BIAS BOOK

BIG BAD BIAS BOOK

Big Bad Bias Book

by Ganna Pogrebna and Karen Renaud illustrated by Marina Kovaleva

BIG BAD BIAS BOOK

Published in Australia by Behavioural Data Science Press Sydney, Australia © Behavioural Data Science Press 2025 All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without the prior written permission of the publisher.

Requests for permission to reproduce any part of this work should be submitted via https://bigbadbiasbook.com.

Marina Kovaleva has asserted her right to be identified as illustrator under the Copyright Act 1968.

ISBN: 978-0-6452760-77

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To every reader who has ever trusted their instincts only to be surprised by their own mind— this book is for you.

May we all come to see bias not as a flaw to be eradicated, but as a feature of human cognition to be understood, challenged, and sometimes even embraced.

Because the real danger isn’t in being biased— it’s in being unaware.

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ABOUT THE AUTHORS GANNA POGREBNA Professor of Behavioral Business Analytics and Data Science, Executive Director of AI and Cyber Futures Institute, Lead for Behavioral Data Science at the Alan Turing Institute

Professor Ganna Pogrebna is an academic, author, keynote speaker, consultant, and a pioneer in behavioral data science, applying insights from behavioral science to create AI-driven solutions that promote societal progress. She is the Professor and Executive Director of the Artificial Intelligence and Cyber Futures Institute and leads the Behavioral Data Science research at the Alan Turing Institute.

Additionally, Ganna holds an Honorary Professorship at the University of Sydney and serves as a distinguished Adjunct Professor at Warwick Business School and a Research Associate at the Centre for Competitive Advantage in the Global Economy.

With a Ph.D. in Economics and Social Sciences, Ganna has worked at prestigious institutions such as Columbia University, where her research focused on the intersection of human behavior and technology. Her work has supported businesses and governments in improving decision-making, particularly in cybersecurity and human-computer interaction. An experienced business consultant and keynote speaker, Ganna has also contributed to entertainment technology, developing a box-office prediction tool featured at the Stockholm Film Festival, and has conducted research on digital human rights during the COVID-19 pandemic. Ganna is an associate editor for Judgement and Decision Making, a methods editor for Leadership Quarterly, and an editor for Scientific Reports and Behavioral Data Science Week. She also runs the Data Driven YouTube channel. Her awards include the British Academy of Management Award (2018), the TechWomen100 UK Award (2019), and the Women in AI Asia Pacific Award (2024). Through a combination of humor and research, Ganna continues to inspire and educate others at the crossroads of technology and human behavior.

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KAREN RENAUD Reader in Computer and Information Sciences, University of Strathclyde

Dr Karen Renaud is a Scottish Computer Scientist, researcher and professor, working on all aspects of Human-Centered Security and Privacy. She is a Reader in Computer and Information Sciences at the University of Strathclyde. Karen’s research focuses on human-centered security, a branch of Human Computer Interaction (HCI). She is interested in the interplay between users and security in the context of societal and industrial use. She works towards creating a natural easy yet secure interaction between humans and devices. Her work has a strong development, experimental and deployment focus, testing solutions in practical situations. Karen has come up with a number of novel solutions to improve usability in a wide range of situations. She has also done fundamental work in understanding people’s mental models of security in a variety of applications and contexts. Karen is the recipient of many prizes and awards, including The Fulbright Scholarship and the Literati Award. She is a great example of truly interdisciplinary scholar, who successfully combines computer science, cyber security and behavioral science. Karen's work uses behavioral science techniques to improve security behaviors and to encourage end-user privacy-preserving behaviors. Her ground-breaking research harnesses methods and techniques from many disciplines, including behavioral science, to understand and influence people outcomes and reach behavioral change.

MARINA KOVALEVA Artist

Marina Kovaleva is a visionary artist and contemporary conceptualist painter. With a deep connection to the rich cultural traditions and vibrant landscapes of her early life, her art reflects a unique blend of symbolism and nature. Marina primarily works with oil, finding it the perfect medium to express her thoughts and worldview on canvas. Her futuristic and conceptual landscapes, people, animals, and flowers come to life through contrasting and harmonious colors, bold compositions, and artistic courage. Marina believes that art is a gateway to her emotions, offering endless opportunities to communicate her creative ideas to a broader audience. Her paintings are featured in numerous art collections across the US, Germany, Latvia, and other countries, showcasing the global reach of her work.

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PREFACE The Big Bad Bias Book was born out of a desire to bring order to the overwhelming and often chaotic landscape of bias. When one first encounters the literature on human behavior, it can feel as though hundreds of biases are staring back—scattered across fields, theories, and disciplines, each with its own terminology and nuance. This book began as an attempt to make sense of that complexity, to build a structure that could help newcomers navigate it with clarity and confidence. Initially conceived as a resource for university first-year students across disciplines, we quickly discovered that practitioners— from policy, design, education, and beyond—were just as eager for a clear, engaging guide to how biases shape our thinking. The result is a book that is playful in tone, grounded in science, and accessible to anyone with a curious mind—regardless of academic background or professional path.

At the heart of the book lies the Periodic Table of Biases—a visual framework we developed to organize over 200 well-documented cognitive and behavioral biases into meaningful thematic sections. These sections are reflected in the book’s structure: from individual quirks of attention and memory to the social forces that shape perception and judgement, to the deeply ingrained heuristics that guide decision-making.

The table doesn’t claim to be exhaustive, but it provides a practical and intuitive map for navigating the often-bewildering terrain of human reasoning.

Each bias included in this book is drawn from established cognitive psychology or behavioral science literature. Some of the terms—such as “cross-race effect” or “egocentric bias”—may sound jarring, outdated, or even offensive to some readers. We wish to emphasise that these are not terms we have invented; they reflect naming conventions historically used in the academic literature, and we have preserved them here for fidelity and transparency. Where appropriate, we encourage readers to question and critique these labels, just as science itself evolves through open and thoughtful challenge. We also want to address an important framing issue. Some chapter headings—such as “Limitations” of the Brain— may give the impression that the human brain is inherently flawed or deficient. This is not our intention.

As Nick Chater beautifully argues in The Mind is Flat, what we sometimes view as a limitation is often the flip side of a powerful cognitive adaptation. Forgetting, for instance, can be protective. Heuristics, while occasionally misleading, often save us from overload. A so-called “limitation” in one context can be a “superpower” in another. The framing of these sections is intended to reflect the language of the literature, not to diminish human capability or to pathologize normal cognition.

To aid further exploration, we have included a small selection of references at the end of each chapter.

These are not comprehensive bibliographies, but curated pointers—books, peer-reviewed articles, and occasional thought pieces—that provide a starting point for readers who wish to dig deeper. Many of these biases sit within large, ongoing research programs, and the literature continues to grow and selfcorrect.

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Indeed, behavioral science is a living discipline. While many of the effects in this book have been replicated across studies, cultures, and time, some may not stand the test of further scrutiny. We include replicability notes in each chapter to highlight the current state of evidence, and we will endeavour to dynamically update these sections as new data emerge.

Finally, if you find yourself puzzled, challenged, or inspired by the biases in this book—or if you spot an error, a mischaracterisation, or a blind spot—we warmly invite you to reach out via our website https://bigbadbiasbook.com. The journey to better understand human thinking is not one any of us can complete alone. This book is meant to spark curiosity, provoke thought, and perhaps even foster a little self-compassion.

We hope you enjoy exploring it as much as we enjoyed creating it.

Ganna and Karen Sydney and Glasgow, 2025

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Table of Contents About the Authors ................................................................................................................................................ v Preface ............................................................................................................................................................... vii Introduction: How To Read This Book .................................................................................................................. 1 Section I INDIVIDUAL ............................................................................................................................................ 7 Part 1 Personal Characteristics ............................................................................................................................. 9 Being Human Is Not Irrational ............................................................................................................................ 11 Ambiguity attitude ............................................................................................................................................. 12 Risk attitude ....................................................................................................................................................... 14 Part 2 “Limitations” of the Brain ........................................................................................................................ 17 Mind Is Flat ......................................................................................................................................................... 19 Availability heuristic ........................................................................................................................................... 20 Bizarreness effect ............................................................................................................................................... 22 Consistency bias ................................................................................................................................................. 24 Context effect ..................................................................................................................................................... 26 Conservatism or Regressive bias ........................................................................................................................ 28 Cross-race effect ................................................................................................................................................ 30 Cryptomnesia ..................................................................................................................................................... 32 Egocentric bias ................................................................................................................................................... 34 Fading affect bias ............................................................................................................................................... 36 False memory ..................................................................................................................................................... 38 Generation/Self-generation effect ..................................................................................................................... 40 Google effect ...................................................................................................................................................... 42 Humor effect ...................................................................................................................................................... 44 Lag effect ............................................................................................................................................................ 46 List-length effect ................................................................................................................................................ 48 ix

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Levels-of-processing effect ................................................................................................................................ 50 Leveling and sharpening .................................................................................................................................... 52 Mood-congruent memory bias .......................................................................................................................... 54 Misinformation effect ........................................................................................................................................ 56 Modality effect ................................................................................................................................................... 58 Next-in-line effect .............................................................................................................................................. 60 Part-list cueing effect ......................................................................................................................................... 62 Primacy, recency & serial position effect ........................................................................................................... 64 Positivity effect (Socio-emotional selectivity) .................................................................................................... 66 Peak-end rule ..................................................................................................................................................... 68 Picture superiority effect ................................................................................................................................... 70 Choice-supportive bias ....................................................................................................................................... 72 Contrast effect ................................................................................................................................................... 74 Declinism ............................................................................................................................................................ 76 Implicit association ............................................................................................................................................ 78 Negativity bias or Negativity effect .................................................................................................................... 80 Processing difficulty effect ................................................................................................................................. 82 Source confusion ................................................................................................................................................ 84 Suffix effect ........................................................................................................................................................ 86 Spotlight effect ................................................................................................................................................... 88 Spacing effect ..................................................................................................................................................... 90 Self-relevance effect .......................................................................................................................................... 92 Suggestibility ...................................................................................................................................................... 94 Stereotypical bias ............................................................................................................................................... 96 Testing effect ..................................................................................................................................................... 98 Telescoping effect ............................................................................................................................................ 100 Tachypsychia .................................................................................................................................................... 102 Travis syndrome ............................................................................................................................................... 104 Tip of the tongue.............................................................................................................................................. 106 Reminiscence bump ......................................................................................................................................... 108 von Restorff effect 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Verbatim effect ................................................................................................................................................ 112 Zeigarnik effect................................................................................................................................................. 114 Anchoring or focalism ...................................................................................................................................... 116 Attentional bias ................................................................................................................................................ 118 Focusing effect ................................................................................................................................................. 120 Frequency illusion or Baader-Meinhof effect................................................................................................... 122 Selection bias ................................................................................................................................................... 124 Part 3 Judgement ............................................................................................................................................. 127 Everything is relativE ........................................................................................................................................ 129 Duration neglect ............................................................................................................................................... 130 Gambler’s fallacy .............................................................................................................................................. 132 Hyperbolic discounting ..................................................................................................................................... 134 Licencing effect ................................................................................................................................................ 136 Moral credential effect..................................................................................................................................... 138 Recency illusion ................................................................................................................................................ 140 Projection bias .................................................................................................................................................. 142 Present bias ...................................................................................................................................................... 144 Time-saving bias ............................................................................................................................................... 146 Attribute substitution ....................................................................................................................................... 148 Automation bias ............................................................................................................................................... 150 Berkson’s paradox ............................................................................................................................................ 152 Base rate fallacy or Base rate neglect .............................................................................................................. 154 Clustering illusion ............................................................................................................................................. 156 Conjunction fallacy ........................................................................................................................................... 158 Distinction bias ................................................................................................................................................. 160 Default effect ................................................................................................................................................... 162 Decoy effect ..................................................................................................................................................... 164 Framing effect .................................................................................................................................................. 166 Information bias ............................................................................................................................................... 168 Less-is-better effect.......................................................................................................................................... 170 Neglect of 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Parkinson’s law of triviality .............................................................................................................................. 174 Regressive bias ................................................................................................................................................. 176 Survivorship bias .............................................................................................................................................. 178 Subadditivity effect .......................................................................................................................................... 180 Well travelled road effect ................................................................................................................................ 182 Zero-sum bias ................................................................................................................................................... 184 Dunning-Kruger effect...................................................................................................................................... 186 Hard-easy effect ............................................................................................................................................... 188 Overconfidence effect...................................................................................................................................... 190 Pessimism bias ................................................................................................................................................. 192 Restraint bias ................................................................................................................................................... 194 Congruence bias ............................................................................................................................................... 196 Insensitivity to sample size .............................................................................................................................. 198 Illicit transference ............................................................................................................................................ 200 Law of the instrument ...................................................................................................................................... 202 Look-elsewhere effect...................................................................................................................................... 204 Observer-expectancy effect ............................................................................................................................. 206 Outcome bias ................................................................................................................................................... 208 Planning fallacy ................................................................................................................................................ 210 Surrogation ...................................................................................................................................................... 212 Weber-Fechner law .......................................................................................................................................... 214 Denomination effect ........................................................................................................................................ 216 Disposition effect ............................................................................................................................................. 218 Endowment effect ........................................................................................................................................... 220 IKEA effect ........................................................................................................................................................ 222 Irrational escalation/Escalation of commitment ............................................................................................. 224 Loss aversion .................................................................................................................................................... 226 Money illusion .................................................................................................................................................. 228 Not invented here ............................................................................................................................................ 230 Pseudocertainty effect ..................................................................................................................................... 232 Unit bias 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Part 4 Decision Making ..................................................................................................................................... 237 Belief is reality .................................................................................................................................................. 239 Backfire effect .................................................................................................................................................. 240 Belief bias ......................................................................................................................................................... 242 Confirmation bias ............................................................................................................................................. 244 Continued influence effect ............................................................................................................................... 246 Conservatism (belief revision) .......................................................................................................................... 248 Experimenter’s or expectation bias ................................................................................................................. 250 End-of-history illusion ...................................................................................................................................... 252 Exaggerated expectation .................................................................................................................................. 254 Forer effect or Barnum effect .......................................................................................................................... 256 Form function attribution bias ......................................................................................................................... 258 Hindsight bias ................................................................................................................................................... 260 Hot-hand fallacy ............................................................................................................................................... 262 Illusion of control ............................................................................................................................................. 264 Illusory correlation ........................................................................................................................................... 266 Illusion of validity ............................................................................................................................................. 268 Illusory truth effect .......................................................................................................................................... 270 Mere exposure effect ....................................................................................................................................... 272 Normalcy bias ................................................................................................................................................... 274 Omission bias ................................................................................................................................................... 276 Ostrich effect .................................................................................................................................................... 278 Pareidolia ......................................................................................................................................................... 280 Reactive devaluation ........................................................................................................................................ 282 Risk compensation/Peltzman effect................................................................................................................. 284 Rhyme as reason effect .................................................................................................................................... 286 Subjective validation ........................................................................................................................................ 288 Semmelweis reflex ........................................................................................................................................... 290 Selective perception ......................................................................................................................................... 292 Status quo bias ................................................................................................................................................. 294 Zero-risk bias 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Inferences are key ............................................................................................................................................ 299 Ambiguity effect ............................................................................................................................................... 300 Allais paradox: Common consequence effect .................................................................................................. 302 Allais paradox: Common ratio effect ............................................................................................................... 304 Ellsberg paradox ............................................................................................................................................... 306 St Petersburg paradox...................................................................................................................................... 308 Violation of transitivity..................................................................................................................................... 310 Violation of independence ............................................................................................................................... 312 Violation of dominance .................................................................................................................................... 314 Anthropocentric thinking ................................................................................................................................. 316 Anthropomorphism or personification ............................................................................................................ 318 Functional fixedness ........................................................................................................................................ 320 Dread aversion ................................................................................................................................................. 322 Empathy gap .................................................................................................................................................... 324 Impact bias ....................................................................................................................................................... 326 Interoceptive bias ............................................................................................................................................ 328 Optimism bias .................................................................................................................................................. 330 Pro-innovation bias .......................................................................................................................................... 332 Reactance ......................................................................................................................................................... 334 Salience bias ..................................................................................................................................................... 336 Section II SOCIAL .............................................................................................................................................. 339 Part 5 Social...................................................................................................................................................... 341 Interaction effects ............................................................................................................................................ 343 Authority bias ................................................................................................................................................... 344 Actor-observer bias .......................................................................................................................................... 346 Cheerleader effect ........................................................................................................................................... 348 Defensive attribution hypothesis ..................................................................................................................... 350 Egocentric bias ................................................................................................................................................. 352 Extrinsic incentives bias ................................................................................................................................... 354 False consensus effect ..................................................................................................................................... 356 Fundamental attribution 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False uniqueness bias ....................................................................................................................................... 360 Halo effect ........................................................................................................................................................ 362 Illusion of asymmetric insight .......................................................................................................................... 364 Illusion of transparency .................................................................................................................................... 366 Illusory superiority ........................................................................................................................................... 368 Illusion of external agency ............................................................................................................................... 370 Just-world hypothesis ...................................................................................................................................... 372 Moral luck......................................................................................................................................................... 374 Naïve cynicism .................................................................................................................................................. 376 Naïve realism .................................................................................................................................................... 378 Ben Franklin effect ........................................................................................................................................... 380 Bias blind spot .................................................................................................................................................. 382 Compassion fade .............................................................................................................................................. 384 Curse of knowledge .......................................................................................................................................... 386 Courtesy bias .................................................................................................................................................... 388 Hostile attribution bias ..................................................................................................................................... 390 Identifiable victim effect .................................................................................................................................. 392 Pygmalion effect............................................................................................................................................... 394 Social desirability bias ...................................................................................................................................... 396 Shared information bias ................................................................................................................................... 398 Singularity effect .............................................................................................................................................. 400 System justification .......................................................................................................................................... 402 Self-serving bias................................................................................................................................................ 404 Sexual over/underperception bias ................................................................................................................... 406 Trait ascription bias .......................................................................................................................................... 408 Ultimate attribution error ................................................................................................................................ 410 Worse-than-average effect .............................................................................................................................. 412 Collective effects .............................................................................................................................................. 415 Availability cascade .......................................................................................................................................... 416 Bandwagon effect ............................................................................................................................................ 418 Group attribution error 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Groupthink ....................................................................................................................................................... 422 Herding............................................................................................................................................................. 424 Ingroup bias ..................................................................................................................................................... 426 Outgroup homogeneity bias ............................................................................................................................ 428 Social comparison bias ..................................................................................................................................... 430 Stereotyping ..................................................................................................................................................... 432 Third-person effect .......................................................................................................................................... 434 Women are wonderful effect........................................................................................................................... 436 INDEX ............................................................................................................................................................... 438

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INTRODUCTION: HOW TO READ THIS BOOK Ever flipped through a medical encyclopedia and suddenly convinced yourself you had every illness listed? Reading this book might feel a bit like that—only the diagnoses are cognitive biases. That’s not necessarily a bad thing. It turns out that recognising biases—especially your own—is the first step toward understanding how the mind really works. Yet, this book isn’t designed to diagnose, but it will certainly provoke reflection. Some entries may feel uncomfortably familiar. Others might explain behaviors you have witnessed in conversations with others, meetings, relationships, politics, or markets. And some will simply make you laugh, because they are so absurd—and so recognisable.

What This Book Is—and What It Is Not The Big Bad Bias Book is not a manifesto, nor a linear narrative, nor a psychology or behavioral science textbook. It is a map—a structured, visual, and accessible reference for exploring over 200 cognitive biases and heuristics. Think of it as a behavioral science field guide: something you can consult in the middle of a problem, in the aftermath of a questionable decision, or during a conversation that has clearly gone sideways. It is also designed to be read non-sequentially. You can start anywhere, skip sections, follow your curiosity, or zoom in on a specific category. Some chapters are short and playful, others more technical. There is no single “correct” path through the material—only your path.

How the Book Is Organized: The Periodic Table of Biases At the centre of this book is a visual organizing framework: the Periodic Table of Biases (see pp. 4-5).

Inspired by the logic of the chemical periodic table, it arranges biases into 14 colour-coded categories, each corresponding to a particular cognitive or behavioral function—such as memory, attention, confidence, or belief. This taxonomy is not cosmetic. It reflects real distinctions in how the brain encodes, retrieves, interprets, and acts upon information. It allows readers to see not just what each bias is, but how related biases group together—and occasionally, how they clash.

The colour-coded Periodic Table presented in this book is your navigation tool. You might use it in several ways: • Dip in and out: Read an entry when you encounter a new term in a podcast, a meeting, or a news article.

• Compare categories: Explore how Confidence Effects differ from Belief-Based Biases, or how Attention effects interact with Memory effects.

• Follow a colour trail: Pick one functional group—like Intertemporal Choice—and examine how those biases shape your decisions over time.

• Trace cognitive collisions: Use the table to uncover where multiple biases might reinforce or contradict each other in the same scenario.

The visual organization allows for both specificity and synthesis: zoom in on a single phenomenon or trace broader psychological patterns across domains.

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Level Individual

Functional Domain Personal Characteristics

Conceptual Frame Being human is not irrational

Limitations of the Brain

Mind is flat

Judgement

Decision making

Social

Social

Category

Definition

Human Characteristics

Stem from fundamental traits of human cognition and behavior— such as innate preferences. These are deeply rooted effects that reflect what it means to be human (e.g., Ambiguity attitude, Risk attitude).

Memory Effects

Reflect the selective and reconstructive nature of memory. What we remember, misremember, or forget often depends on emotional salience, recency, or context (e.g., False memory, Lag effect).

Attention Effects

Influence what we pay attention to, what we ignore, and how salience affects our perceptions. These effects help us filter overwhelming stimuli, but they can also distort reality by amplifying certain cues over others (e.g., Attentional bias, Focusing effect).

Intertemporal Choice

Reflect our struggle to manage short-term vs. long-term trade-offs.

Often discussed in the context of self-control, patience, and reward delay (e.g., Hyperbolic discounting, Present bias).

Information Processing

Arise from the shortcuts and simplifications our brains make when processing data. They often affect how we assess causality, complexity, or correlations, and are central to understanding flawed reasoning (e.g., Default effect, Decoy effect).

Confidence Effects

Relate to how confident we are in our knowledge or abilities. Often, these biases cause us to overestimate what we know or how accurately we can predict future events (e.g., Overconfidence effect, Dunning-Kruger effect).

Methodology Biases

Concern how research is designed, interpreted, or reported. They highlight pitfalls in scientific practice that can mislead evidencebased understanding (e.g., Outcome bias, Planning fallacy).

Value Processing

Cover how we evaluate worth, outcomes, and trade-offs. It includes distortions in how we perceive cost-benefit ratios or assign utility to different options (e.g., Endowment effect, Loss aversion).

Belief is reality

Belief-Based Biases

Reflect how existing beliefs shape our interpretation of new information. They often lead us to seek, recall, or prioritise evidence that aligns with what we already believe, reinforcing preconceptions (e.g., Illusion of control, Hindsight bias).

Inferences are key

Choice Under Risk/Uncertainty

Capture instances when individuals make decisions with incomplete or uncertain/ambiguous information. These effects describe how people estimate probabilities, weigh outcomes, and respond to risk. (e.g., Violation of transitivity, Ellsberg paradox).

Creativity Effects

Influence how we generate novel ideas or solve problems as well as reveal constraints and illusions in how humans explore alternatives or reinterpret problems (e.g., Anthropocentric thinking, Functional fixedness).

Sentiment and Senses

Reflect the influence of emotion and sensory input on decisionmaking. These include phenomena like visceral reactions, emotional contagion, and affective heuristics (e.g., Impact bias, Empathy gap).

Interaction effects

Interpersonal Effects

Deal with how we perceive, evaluate, or react to other individuals.

They affect things like trust, attribution of intent, and responses to feedback (e.g., Halo effect, Authority bias).

Collective effects

Populational Group Effects

Everything is relative

Colour Code

2

and

Manifest at the group level—through norms, demographic differences, or identity dynamics. They often relate to broader cultural or structural phenomena (e.g., Groupthink, Herding).

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Why the Groupings Matter

The categories in the table are not arbitrary. They are based on a synthesis of behavioral science, cognitive psychology, decision theory, and neuroscience. The goal is both cognitive and didactic: • Cognitive-functional: Each group reflects a different mental operation—memory, attention, value evaluation, social reasoning, etc.

• Didactic: By clustering related biases, the goal is to help you understand why these distortions occur and how they interrelate.

These groupings also help you locate patterns that might otherwise go unnoticed. For example: • Belief-Based Biases and Information Processing may jointly influence how we assess new data.

• Confidence Effects and Social Interaction Biases often operate together in leadership settings.

• Group Effects can exaggerate or suppress individual-level biases, leading to very different collective outcomes.

Applying This Book in Real Life This book is meant to be practical. It can be used in multiple contexts: • Personal growth: Spot thinking traps, understand internal conflict, or reflect on why you regret some choices but not others.

• Professional settings: Improve decision-making, product design, negotiation, or team dynamics by identifying predictable distortions in perception and evaluation.

• Community and policy: Detect the group-level dynamics—such as conformity, bias propagation, or polarisation—that affect institutions, campaigns, or public discourse.

Every entry is written with accessibility in mind. Some biases are robustly supported by decades of research; others are more contested. For transparency, we flag replicability and include curated references at the end of each chapter for those who want to explore further. All terminology—bias names, effects, constructs—is preserved from the original academic literature. While some may sound clunky, outdated, or even insensitive, we retain them for traceability. Where appropriate, we provide commentary or context. We ask readers to interpret terms like Cross-Race Effect or Mind is Flat not as value judgments, but as labels rooted in specific theoretical traditions.

Start Anywhere. Go Everywhere.

This book does not assume you are irrational. It assumes that you are human. Whether you’re a student trying to make sense of a confusing lecture, a manager frustrated by groupthink, a policy analyst searching for better interventions, or simply a curious mind wondering why people click on fake news—they are all here. So open to any page. Pick a category. Follow a colour-coded category or consult the alphabetical index at the end of this book. Let the table be your compass. And the next time someone says, “That’s just a bias,” you’ll know exactly which one—and why it matters.

Happy exploring!

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SECTION I INDIVIDUAL

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PART 1 PERSONAL CHARACTERISTICS

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BEING HUMAN IS NOT IRRATIONAL

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AMBIGUITY ATTITUDE Ambiguity attitude refers to an individual's preference or aversion towards situations where the probability of outcomes is uncertain or ambiguous.

He gestured to the boxes with a flourish. "Both have four balls inside. You can grab one through the side holes, but no peeking. Box one has an even split of yellow and blue.

Box two?" Rooney raised his eyebrows, "That's the wildcard—it's got an unknown mix."

Puzzled, Ellie asked, "Unknown mix?"

"Any combo of yellow and blue could be in there," Rooney said.

"So, it's the mystery box," Ellie mused, trying to understand the setup.

"Spot on. Now, do you want to win five bucks?

Just pull out a yellow ball."

Ellie thought for a second, then chose box one.

"It's a sure bet."

"But box two could be all yellow," Rooney teased.

"Maybe, but I like playing it safe," Ellie responded.

"That's exactly what I'm studying—our preference for certainty," Rooney smiled.

Ellie reached in and fetched a yellow ball with a grin. "Pay up!"

Handing over the five dollars, Rooney chuckled, "You proved it—we'd rather steer clear of the ambiguity."

Rooney sat at a table, two numbered boxes before him, as Ellie walked up, her interest immediately piqued. "What's with the boxes?" she asked.

"I've got to talk about uncertainty for class, so I'm running a little experiment," Rooney explained.

Ellie leaned forward, intrigued. ”Go on."

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uncertain future of digital. This decision to avoid the ambiguous risk of fully transitioning to digital eventually led to the company filing for bankruptcy in 2012, as they could not compete with fully digital companies like Canon and Nikon, which embraced the new technology much earlier (Mui, 2012).

About: Ambiguity attitude refers to the varied reactions individuals or organizations have towards uncertainty. This concept is rooted in the distinction between risk—situations where probabilities are known—and ambiguity, where these probabilities are unknown. Early theoretical explorations of this phenomenon were conducted by Daniel Ellsberg in 1961. His research demonstrated that individuals tend to prefer uncertain situations with known probabilities (risk) over those with unknown probabilities (ambiguity), a behavior termed "ambiguity aversion" (Ellsberg, 1961). This preference influences decision-making in contexts ranging from finance to healthcare, where the stakes of unknown outcomes can dramatically shift choices and strategies (Camerer and Weber, 1992).

Reproducibility: Ambiguity attitude has been studied across different cultures, and research shows it is influenced by both cultural and situational factors. For example, a study comparing French (Western) and Japanese (Eastern) participants tested how they made decisions involving uncertainty (Adachi et al., 2013). The study found cultural differences: French participants placed more importance on personal choice than Japanese participants, though less so than Americans in previous studies. These results suggest that while the tendency to react to uncertainty is widespread, how strongly it is felt and expressed varies across cultures and contexts.

Trivia Example: An amusing real-life instance of ambiguity aversion can be observed in consumer behavior (e.g., White and Perfors, 2022). For example, some people might choose well-known brands over generic or new brands, even when the generic brands offer the same quality at a lower price. The ambiguity of the unfamiliar brand's quality leads consumers to stick with the known, established brand rather than risk the uncertainty of the new one (e.g., Muthukrishnan et al., 2009).

Selected References Adachi, K., Yama, H., Van der Henst, J. B., Mercier, H., Karasawa, M., & Kawasaki, Y. (2013). Culture, ambiguity aversion and choice in probability judgments. International Journal of Creativity & Problem Solving, 23(2), 63–78.

Anthony, S. D. (2016, July). Kodak’s downfall wasn’t about technology. Harvard Business Review. https://hbr.org/2016/07/kodaks-downfall-wasnt-abouttechnology Camerer, C., & Weber, M. (1992). Recent developments in modeling preferences: Uncertainty and ambiguity.

Journal of Risk and Uncertainty, 5(4), 325–370.

Ellsberg, D. (1961). Risk, ambiguity, and the Savage axioms.

Quarterly Journal of Economics, 75(4), 643–669.

Mui, C. (2012, January 18). How Kodak failed.

Forbes.https://www.forbes.com/sites/chunkamui/2012/0 1/18/how-kodak-failed/

Business Example: A well-documented example of ambiguity attitude in business is Kodak's response to the rise of digital photography. In the late 1990s and early 2000s, digital photography was emerging, yet the exact impact it would have on the market was ambiguous. Kodak, a leader in film photography, underestimated this impact, favouring the known profitability of film over the

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RISK ATTITUDE Risk attitude refers to an individual's or organization's disposition towards risk, which influences how they perceive, evaluate, and respond to uncertain situations. do you keep buying lottery tickets?

Winning anything significant is practically impossible. It's a fantasy! Can't you see that?" he exclaimed.

Ellie, unfazed and cheerful, replied, "Maybe you're not the risk-taking type, but I am. I believe in my luck; we just view risk differently!"

"It's not about risk attitudes—it's about common sense," Rooney argued. "Buying lottery tickets is simply irrational."

Ellie was curious. "How so?"

Rooney explained, "Consider this: if I offered you a lottery ticket with a 50% chance of winning $100, the 'risk-free cash equivalent' would be $50. That's $100 times the 0.5 probability. Risk-taking people who enjoy risk might pay more than $50, while risk-averse people who don't like risk would pay less. It's normal and reflects their attitude towards risk. However, buying a ticket with a one in a million shot isn't just odd, it's downright foolish."

Ellie shrugged, "Call it foolish, but I still feel lucky today."

Rooney sighed in resignation. "You're impossible!"

Rooney was visibly frustrated with Ellie. "Why 14

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bold move was the decision to operate at low margins for extended periods to gain market share, which eventually led to Amazon becoming one of the largest and most influential companies in the world.

About: Risk attitude refers to how people or organizations respond to situations where the outcomes are uncertain, but the probabilities are known. For example, some people avoid taking risks, preferring safer options, while others are more willing to take chances for potential rewards. This concept has been studied for centuries, starting with Daniel Bernoulli in 1738, who explained that people value outcomes based on their personal satisfaction (or utility), not just monetary gain (Bernoulli, 1738). Later, John von Neumann and Oskar Morgenstern (1944) formalized this idea into expected utility theory (von Neumann and Morgenstern, 1944). Daniel Kahneman and Amos Tversky (1979) expanded this with prospect theory, showing how people weigh probabilities to make decisions (Kahneman and Tversky, 1979). People and organizations can be risk-averse, risk-neutral, or risk-seeking, depending on how they weigh potential losses against potential gains. These attitudes profoundly impact financial decisions, business strategies, and everyday choices (Loewenstein et al., 2001; Weber and Milliman, 1997).

Reproducibility: Research into risk attitude has been replicated across various contexts (e.g., Dohmen et al., 2011).

Studies often reveal that risk-averse individuals are more prevalent in the general population, though the proportion of risk-seekers can rise significantly in specific contexts like gambling or entrepreneurship. Additionally, cultural factors influence risk attitudes; e.g., societies with higher uncertainty avoidance tend to display greater risk aversion, while those with lower uncertainty avoidance may exhibit more riskseeking behavior (Shou et al., 2023). Although earlier economic research suggested that risk attitudes are stable traits, newer evidence has shown that they are often context-dependent (Loomes and Pogrebna, 2014).

Selected References Bernoulli, D. (1738). Specimen theoriae novae de mensura sortis.

Commentarii Academiae Scientiarum Imperialis Petropolitanae, 5, 175–192. (Translated in 1954 as “Exposition of a New Theory on the Measurement of Risk” in Econometrica, 22(1), 23–36).

Dohmen, T., Falk, A., Huffman, D., Sunde, U., Schupp, J., & Wagner, G. G. (2011). Individual risk attitudes: Measurement, determinants, and behavioral consequences. Journal of the European Economic Association, 9(3), 522–550.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–292.

Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, N. (2001).

Risk as feelings. Psychological Bulletin, 127(2), 267–286.

Loomes, G., & Pogrebna, G. (2014). Measuring individual risk attitudes when preferences are imprecise. Economic Journal, 124(576), 569–593.

Shou, Y., Olney, J., & Wang, M. C. (2023). Cross-cultural assessment and comparisons of risk tolerance across domains. Current Psychology, 42(18), 15368–15380.

Slovic, P. (1995). The construction of preference. American Psychologist, 50(5), 364–371. von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.

Weber, E. U., & Milliman, R. A. (1997). Perceived risk attitudes: Relating risk perception to risky choice. Management Science, 43(2), 123–144

Trivia Example: One illustration of risk-related behavior can be seen in the world of stock trading. For instance, investors who are risk-averse tend to prefer bonds or dividend-paying stocks with predictable returns, whereas risk-seeking investors might gravitate towards volatile tech stocks or options trading, where the potential for high returns is accompanied by significant risk (Slovic, 1995).

Business Example: A well-known example of a company that exhibited a risk-seeking attitude is Amazon.

Under the leadership of Jeff Bezos, Amazon pursued high-risk strategies that defied conventional business norms. This included aggressive investments in new technologies and business models, such as cloud computing through Amazon Web Services (AWS) at a time when this market was still in its infancy. Another 15

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PART 2 “LIMITATIONS” OF THE BRAIN

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MIND IS FLAT

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AVAILABILITY HEURISTIC Availability heuristic is when people make judgments about the likelihood of an event based on how easily an example, instance, or case relevant to it comes to mind.

Ellie found Rooney agitated, pacing the veranda like a restless shadow. "What's eating you?" she asked, placing her glass on the table.

Rooney slumped into a chair. "Mom's flying out for work again, and I'm just...worried."

"Isn't that routine for her?" Ellie probed gently.

He was quick to respond, "But flying is risky, Ellie. Planes crash, you know." Ellie attempted to calm him down "More people have car accidents than plane crashes, and you don't fret over her driving."

"That's different," Rooney insisted. "Cars give you control. Planes don't."

Seeing that logic wasn't calming him, Ellie switched tactics. ”Let’s look up some stats," she advised, tapping on her phone. ”Check this out —air travel's risk is one in over two hundred thousand. It's actually a lot safer than the risk of accident while driving."

Rooney's concern lingered. "But it's Mom..."

Ellie smiled. "How about we pick some raspberries from my greenhouse?"

Rooney’s mood lifted slightly. "Raspberries?

Hang, on – are you sure about that statistic?"

"Yes, I’m positive. Let's get some gloves and a mug," said Ellie, leading Rooney away from his worries.

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being low. Johnson & Johnson, the manufacturer of Tylenol, responded by recalling all Tylenol products and introducing tamper-evident packaging, which helped restore public trust.

About: The availability heuristic is a cognitive bias first described by psychologists Amos Tversky and Daniel Kahneman in 1973 (Tversky and Kahneman, 1973). It refers to the mental shortcut that relies on immediate examples that come to mind when evaluating a specific topic, concept, method, or decision. The heuristic operates under the assumption that if something can be recalled easily, it must be more important or likely than alternatives that do not come to mind as readily. Tversky and Kahneman highlighted its impact on decision-making and judgment. The availability heuristic has since been extensively studied and is recognized as an important concept in understanding human cognition, particularly in psychology, behavioral economics, and decision-making (Schwarz et al., 1991; Kunda, 1990).

Reproducibility: The availability heuristic is a well-documented psychological phenomenon with numerous studies supporting its presence in various decision- making processes (e.g., Gou, 2023).

However, its reproducibility can vary depending on several factors. Research shows that the heuristic's impact can be influenced by the context in which information is presented, the emotional salience of the information, and individual differences in cognitive processing.

For example, the heuristic is more likely to occur in situations where people are making judgments under time pressure or cognitive load, which limits their ability to search for and evaluate information thoroughly. While the availability heuristic often leads to biased judgments, it is not always the case; some researchers argue that its effects can be moderated by factors such as the perceived relevance of the information and the individual's motivation to be accurate (e.g., Koriat et al., 1980).

Trivia Example: One example of the availability heuristic in action is the public perception of the risk of plane crashes versus car accidents. While car accidents are statistically far more common and dangerous, plane crashes often receive more media coverage, making them more memorable. This heightened availability in memory leads people to overestimate the risk of flying, despite the actual statistics showing that driving is far more dangerous.

Selected References

Gou, Y. (2023). Availability heuristics and its applications in behavioral economics. Advances in Economics, Management and Political Sciences, 43, 192–196.

Koriat, A., Lichtenstein, S., & Fischhoff, B. (1980). Reasons for confidence.

Journal of Experimental Psychology: Human Learning and Memory, 6(2), 107 Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480–498.

Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61(2), 195–202.

Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.

Business Example: The availability heuristic can significantly impact consumer behavior and marketing strategies.

One example is the Tylenol cyanide poisoning scare in 1982. After seven people died from taking cyanide-laced Tylenol capsules, extensive media coverage led to widespread public fear of overthe- counter medications, despite the actual risk 21

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BIZARRENESS EFFECT The bizarreness effect is the tendency for unusual material or facts to be remembered better than ordinary material or facts.

"What do you make of my bold design choice?"

Ellie asked, gesturing toward a poster featuring a steel-grey robot clutching a vivid blue raspberry with "Raspberry Robot" emblazoned above.

Rooney, visibly irritated, retorted, ”I asked you to make a poster for our robotics club’s expo showcase. What's with the blue raspberry?"

Ellie, puzzled by his reaction, defended her work.

"It's distinctive, it'll draw a crowd to our booth."

"I'm not sure," Rooney replied skeptically. "Why blue, though? And it's huge.

The club's name was inspired by the Raspberry Pi, not a blue raspberry..."

Ellie countered confidently, "You may be great at math and robotics, but this is marketing. Oddities grab attention. Trust me on this."

"Fine," conceded Rooney, "We’re running out of time. Let's use your poster."

Two days later, an exhausted but satisfied Rooney called Ellie. "You were spot on—our booth was a hit, thanks to that blue raspberry!"

"See? I told you I had a knack for this," Ellie responded, pleased with herself.

"Genius! We made a lasting impression! Thank you!" said Rooney. Ellie hung up, thinking, "That's the power of the bizarreness effect."

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Gamble’s “Old Spice Guy” campaign launched in 2010. The advertisements featured actor Isaiah Mustafa delivering absurd yet humorous monologues while maintaining a suave demeanor. The bizarre and unconventional nature of the ads, paired with the tagline “The Man Your Man Could Smell Like,” made the campaign highly memorable. It captured the public’s attention, went viral, and led to a significant increase in Old Spice sales.

About: The bizarreness effect is a psychological phenomenon suggesting that bizarre or unusual information is often better remembered than common or ordinary information. Researchers began exploring this concept in the 1970s while studying the effects of distinctiveness on memory. Early studies found that bizarre sentences were more memorable than their commonplace counterparts (McDaniel and Einstein, 1986). This finding stems from the idea that bizarre information stands out in our memory due to its novelty and distinctiveness, making it easier to recall. Over the years, the bizarreness effect has been extensively studied in the context of memory and recall.

Reproducibility: The reproducibility of the bizarreness effect has been a subject of ongoing debate. While early studies strongly supported the effect, subsequent research has revealed nuances that challenge its simplistic interpretation, e.g., evidence suggests that the effect might not hold when bizarre information is presented within a meaningful context (e.g., McDaniel et al., 1995).

The type of memory test used plays a significant role (e.g., Geraci et al., 2013), i.e., the effect is more pronounced in free recall tasks, where participants generate memories without prompts, compared to recognition tasks, where they identify previously encountered information.

Trivia Example: A striking example of the bizarreness effect in real life is the “Exploding Whale” incident in Florence, Oregon, on November 12, 1970. The Oregon Highway Division, tasked with removing a beached sperm whale (cachalot) carcass, decided to use dynamite, believing it would efficiently dispose of the body. However, the explosion sent chunks of whale blubber flying hundreds of feet, damaging property and covering bystanders in remains. This event became widely remembered not only because of the peculiar decision to use explosives but also due to the dramatic and unexpected outcome. Its enduring presence in popular culture shows how unusual occurrences tend to embed themselves deeply in collective memory.

Selected References

Geraci, L., McDaniel, M. A., Miller, T. M., & Hughes, M. L. (2013).

The bizarreness effect: evidence for the critical influence of retrieval processes. Memory & Cognition, 41(8), 12281237.

McDaniel, M. A., & Einstein, G. O. (1986). Bizarre imagery as an effective memory aid: The importance of distinctiveness.

Journal of Experimental Psychology: Learning, Memory, and Cognition, 12(1), 54-65.

McDaniel, M. A., Einstein, G. O., DeLosh, E. L., May, C. P., & Brady, P. (1995).

The bizarreness effect: It's not surprising, it's complex. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(2), 422-435.

Business Example: The bizarreness effect can also be strategically leveraged in advertising to create memorable campaigns. One notable instance is Procter & 23

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CONSISTENCY BIAS Consistency bias is the tendency to align our recollections of past attitudes with our current selfimage, e.g., students who perform well at exams remember less pre-exam anxiety, while those who do poorly recall more.

"Hey, what's happening?" Ellie leaned in toward Rooney, who was ensconced at the kitchen table, encircled by a flood of candy wrappers and a nearly empty chocolate box.

"Just prepping for the Math Olympiad," he responded, focused on his notes.

"That's a chocolate mountain there—don't overdo it," she half-joked, masking her concern.

"It keeps my brain ticking," Rooney quipped, then noticed Ellie's furrowed brow.

"You seem stressed, too. What's going on?"

"Got a physics report due. I'm drowning in it," she exhaled, plucking the last chocolate from the box.

"Don't worry, I can help," Rooney offered warmly.

The following day, Rooney checked in. "How did your report turn out?" "Got a 60," Ellie replied, her tone was a blend of relief and disappointment. "You knew the material," Rooney encouraged.

"Yeah, but the nerves got me," she admitted.

"And your Olympiad?"

"Aced it. Took first place! And believe it or not, I wasn’t even that worried."

"Right, not worried, just an accidental chocolate feast," Ellie ribbed him.

He laughed. "Okay, I was a tad anxious.

Celebratory rollerblading tomorrow?"

"Absolutely. Pick me up?" she replied, her spirits lifted.

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for its dominance in personal computing through its Windows operating system and Office suite.

However, as cloud computing gained prominence, Microsoft shifted its strategic focus toward cloud-based services like Azure. The company began to emphasize its longstanding commitment to enabling enterprise productivity and scalability, reframing its past achievements as steppingstones to its current strategy. By aligning its historical narrative with its present focus on the cloud, Microsoft reshaped its past to create a seamless continuity with its priorities.

About: Consistency bias is a cognitive bias that leads people to remember their past attitudes and behaviors as more consistent with their current attitudes and behaviors than they steppingstones. An early discussion of this phenomenon was provided in the context of cognitive dissonance, proposing that individuals have a psychological need to maintain consistency between their beliefs, attitudes, and behaviors (Festinger, 1957). Over time, researchers have further explored this bias, finding that it can lead to distortions in autobiographical memory, showing that people often reconstruct their past beliefs and attitudes to align with their present views (e.g., Ross, 1989).

This bias is thought to serve the function of maintaining a positive self-image and reducing cognitive dissonance.

Reproducibility: Consistency bias has been replicated in various studies across different contexts, indicating its robustness as a psychological phenomenon (Conway and Ross, 1984, Brannon and Gawronski, 2018). However, the extent of the bias can vary depending on factors such as the salience of the attitude or behavior, the individual's motivation to maintain a positive self-image, and the presence of external cues that trigger memory recall. While the general phenomenon of consistency bias is well-established, further research is needed to understand the boundary conditions and mechanisms underlying its variability.

Trivia Example: A well-known example of consistency bias occurred during the Watergate scandal in the early 1970s. Former President Richard Nixon consistently denied any wrongdoing or involvement in the break-in at the Democratic National Committee headquarters. However, as evidence mounted, including the infamous White House tapes, Nixon's previous denials and statements were called into question. In his memoirs and subsequent interviews, Nixon continued to present his actions and decisions in a manner that was more consistent with his later justifications and explanations.

Selected References

Brannon, S. M., & Gawronski, B. (2018). Cognitive consistency in social cognition. Oxford Research Encyclopedia of Psychology. Oxford University Press.

Conway, M. A., & Ross, M. (1984). Getting what you want by revising what you had. Journal of Personality and Social Psychology, 47(4), 738–748.

Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.

Ross, M. (1989). Relation of implicit theories to the construction of personal histories. Psychological Review, 96(2), 341– 357.

Business Example: Consistency bias can be seen in Microsoft’s narrative shift during its transition to cloud computing. Historically, Microsoft was known 25

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CONTEXT EFFECT The context effect refers to the influence of environmental factors on the perception of stimuli. top-notch. I use one myself."

As they examined the locks, a salesman appeared, offering a wide selection. "We have twenty varieties, all reasonably priced," he said in a hushed tone. Ellie, cautious, asked to see some options. The salesman quickly set out three locks in green, red, and black, ranging from $100 to $150.

Rooney eyed the locks skeptically. "How secure are these?" "The $100 one is rated eight out of ten, the others nine out of ten," the salesman replied.

Ellie, now more confident, reached for the red $120 lock. Suddenly, the salesman presented another option – a massive, bright yellow lock for $200. Ellie was momentarily speechless, looking at the escalating prices from $100 to $200. She abruptly grabbed the $150 black lock. "This one."

"Why that one?" Rooney asked. "They're all rated nine and come with a lifetime warranty.

The $120 one is just as good."

"But if the $200 lock is the same, why is the cheaper one only $120?" Ellie pondered, now holding the red lock.

Rooney approached the salesman. "Give us a minute."

"Of course, let me know if you need help," the salesman said, retreating into the store.

Rooney whispered to Ellie, "It's a sales trick.

They're priced to make you pick the middle range. Don't fall for it. Go for the $120 one."

Ellie, now convinced, picked up the red lock.

"Okay, let's get this and head to the cash register. I saved $30, so maybe we can check out some T-shirts." Rooney sighed, "You do that. I'm done with shopping for today.

"Hey, what’s up?" Rooney grumbled, clearly unhappy that his Saturday morning was starting with a shopping trip. "I hate malls.

I'm not spending my day looking at clothes."

Ellie, visibly stressed, shared her experience from the previous day. "You won't believe it, but someone almost stole my bike yesterday. I need a new lock." Rooney retorted, "About time you replaced that rickety old lock. I'll help you find a sturdy one."

At the mall, they headed to the Bicycle Shop. The store was packed with an array of cycling gear, but they were focused on locks.

Rooney led Ellie to a display of robust, horseshoe-shaped steel locks. "These are 26

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About: The context effect is a psychological phenomenon that describes how the context in which information is presented can influence how that information is perceived, interpreted, and remembered. The concept emerged from early studies in cognitive psychology and perception, notably the work of Gestalt psychologists in the early 20th century, who emphasized the importance of context in visual perception. Subsequent research expanded the concept to encompass various aspects of cognition, including memory, decision-making, and language comprehension. It incorporates the encoding specificity principle, which posits that memory is enhanced when the context at retrieval matches the context at encoding, provided a theoretical foundation for understanding context effects (e.g., Tulving and Thomson, 1973).

Business Example: The context effect is often leveraged in marketing and advertising. The placement of products in a store can significantly impact consumer perception and purchasing decisions. One study found that products placed at eye level in a grocery store were perceived as higher quality and were more likely to be purchased than the same products placed on lower shelves (Cheema and Soman, 2008).

Reproducibility: The context effect is a well-replicated phenomenon in psychology, with numerous studies demonstrating its influence across different domains of cognition. The effect has been observed in various experimental settings, cultures, and populations, indicating its robustness and generalizability. However, the magnitude and direction of the context effect can vary depending on factors such as the specific task, the type of context, and individual differences in cognitive processing. Researchers continue to explore the underlying mechanisms and boundary conditions of context effects to better understand their impact on human cognition and behavior.

Trivia Example: A well-known example of the context effect is the "McGurk effect" (e.g., McGurk and MacDonald, 1976). In an experiment, participants watched a video of a person saying the sound "ga" while the audio played the sound "ba”. Surprisingly, many participants perceived the sound as "da," a blend of the visual and auditory inputs. This phenomenon demonstrates how visual context can influence auditory perception, leading to a different interpretation of the sound than what is actually heard. The McGurk effect has been replicated in numerous studies.

Selected References

Cheema, A., & Soman, D. (2008). The effect of partitions on controlling consumption. Journal of Marketing Research, 45(6), 665–675.

McGurk, H., & MacDonald, J. (1976). Hearing lips and seeing voices. Nature, 264(5588), 746–748.

Tulving, E., & Thomson, D. M. (1973). Encoding specificity and retrieval processes in episodic memory. Psychological Review, 80(5), 352–373

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CONSERVATISM OR REGRESSIVE BIAS Conservatism or regressive bias is a tendency to insufficiently revise one's beliefs when presented with new evidence.

Rooney explained with enthusiasm. "I helped at my brother's kindergarten, teaching counting with dice. The teachers wanted more math activities, so I made these banana counting cards. My brother loves bananas. Look - one, two, three, four bananas!"

Ellie chuckled, puzzling Rooney. "What's funny?"

"The colors are great," Ellie said, trying to be serious, "but why are bananas on palm trees?"

Rooney was baffled. "Aren't they from palm trees?"

Ellie corrected him gently. "Bananas are actually giant grasses, like lilies or orchids. They're not from palm trees."

"Impossible," Rooney scoffed. "I've seen bananas on trees in books." Ellie insisted, "Really, they're not tree plants. Check the internet."

Rooney, determined to prove his point, showed Ellie a picture on his tablet of tall banana plants. "See, palm trees!"

"That's a 'banana tree,' but it's technically a grass, not a palm," Ellie explained. Rooney, frustrated, insisted, "The type of plant doesn't matter. It's about counting bananas. I won't redraw them."

"Let me redo it," Ellie offered. "We don't want the kids thinking bananas grow on palm trees."

"I'll make you proud," Rooney boasted, displaying his hand-drawn cards to Ellie.

"What are these?" Ellie inquired, curious.

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financial decision-making. One example is the reluctance of investors to revise their stock valuations in response to new financial information. For instance, when a company announces unexpectedly high earnings, investors might underreact, leading to a slower than expected adjustment in the stock price. This phenomenon was observed in the stock market's response to earnings announcements stocks with the most surprising earnings announcements experienced a gradual price adjustment over time, rather than an immediate correction, indicating the presence of conservatism bias in investor behavior (e.g., De Bondt and Thaler, 1990).

About: The concept of conservatism or regressive bias in psychology refers to the tendency for people to insufficiently revise their beliefs when presented with new evidence. This phenomenon was first formally identified by Ward Edwards in the 1960s, particularly in the context of Bayesian probability judgment tasks (Edwards, 1968).

Edwards observed that individuals often failed to adequately update their probability estimates in light of new data, a pattern that deviated from the normative predictions of Bayesian inference.

This bias was initially termed "conservatism" because people conservatively clung to their prior beliefs, underweighting the impact of new information. Subsequent research expanded the understanding of this bias, exploring its presence in various domains such as decision-making, clinical judgment, and forecasting (Edwards, 1982).

Reproducibility: Conservatism bias is a well-documented phenomenon with a strong empirical foundation. It has been observed in various contexts, including probability judgment, decision-making, and financial forecasting. The bias is generally robust and replicable across different experimental settings and populations.

However, the degree of conservatism can vary depending on factors such as the ambiguity of the information, the individual's expertise, and the perceived reliability of the new evidence (e.g., Bedessem, 2021).

Trivia Example: A notable real-life example of conservatism bias occurred during the initial stages of the COVID-19 pandemic in early 2020. Many public health officials and governments were slow to revise their risk assessments and policy recommendations despite mounting evidence of the virus's rapid spread and severity. This underreaction can be partially attributed to conservatism bias, as authorities were hesitant to update their beliefs and predictions based on the new, alarming data. As a result, some countries experienced delays in implementing necessary measures such as travel restrictions, testing, and lockdowns, which may have contributed to the subsequent widespread transmission of the virus.

Selected References

Bedessem, B. (2021). Two conceptions of the sources of conservatism in scientific research. Synthese, 198(7), 6597–6614.

De Bondt, W. F. M., & Thaler, R. H. (1990). Do security analysts overreact? The American Economic Review, 80(2), 52–57.

Edwards, W. (1968). Conservatism in human information processing. New York: Wiley & Sons.

Edwards, W. (1982). Conservatism in human information processing (excerpted). In Judgment under Uncertainty: Heuristics and Biases. Cambridge University Press, New York, NY. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Business Example: The conservatism bias can significantly impact 29

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CROSS-RACE EFFECT Cross-race effect or own-race bias refers to the tendency to more easily recognize faces of the race that one is most familiar with, which is often one's own race.

"That sounds perfect," Rooney replied, a hint of distraction in his voice as he followed her.

Over glasses of freshly squeezed juice, he hesitantly opened up about camp, his cheeks flushing. "There's this girl, Yanzhen, from China, on our team. We really connected at camp. But, when I saw her at the store yesterday, she seemed like she didn't recognize me!"

Ellie looked at him, noticing the hint of disappointment in his eyes. "Are you surprised by that?"

"Yeah, I am," Rooney admitted, his gaze dropping. "We spent the whole week together, and then she acted like we'd never met. It's not like she needs glasses or anything."

Understanding dawned on Ellie. "It might be the cross-racial effect. People often have trouble recognizing faces from races they're not as familiar with." Rooney appeared thoughtful yet still troubled.

Ellie continued, "It's about exposure. For instance, someone who hasn't met many Chinese people might not easily distinguish between them. It's not personal. Your girlfriend Yanzhen probably just needs more time to adjust to new faces."

Rooney's blush deepened, and he murmured, almost to himself, "She's not ‘my girlfriend'." He quickly corrected himself, "I mean, it was just weird, that's all," and he focused back on his orange juice.

"Welcome back!" Ellie greeted Rooney with a warm smile. "Weren't you supposed to be at tennis camp for another week?"

Settling in, Rooney explained his early return.

"They cut it short this year, just a weeklong session."

As Ellie headed towards the kitchen, she offered, "How about some fresh orange juice? I've got a new juicer."

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indicate that security personnel may misidentify suspects from racial groups different from their own (e.g., Sporer, 2001). To address these challenges, companies often adopt strategies such as diversity training, which aims to improve cross-racial understanding, and the use of facial recognition technologies designed to minimize racial disparities. Yet, the effectiveness of such measures depends on how well they are implemented and whether they are complemented by broader systemic changes.

About: The cross-race effect, also known as the own-race bias, is a psychological phenomenon that refers to the tendency for individuals to more easily recognize and remember faces of their own racial group compared to faces of other racial groups.

This effect was documented in the early 20th century, with studies noting the difficulty of people in accurately identifying individuals of a different race (e.g., Feingold, 1914). The phenomenon gained significant attention in the 1960s and 1970s, with researchers conducting empirical studies that confirmed the existence of the effect (e.g., Brigham & Barkowitz 1978). The bias is thought to arise from a combination of factors, including lack of exposure to diverse racial groups, social categorization processes, and cognitive mechanisms that prioritize the encoding of race-congruent features.

Reproducibility: The cross-race effect has been extensively studied and replicated across different cultures and populations, establishing its reliability as a psychological phenomenon. This bias has been consistently observed in experimental paradigms such as face recognition tasks, lineup identifications, and memory recall tests Yet, the strength of the effect varies depending on the diversity of participants’ social environments, the racial groups being compared, and the methods used to assess face recognition accuracy (e.g., Hancock and Rhodes, 2008).

Trivia Example: A real-life example of the cross-race effect can be seen in the case of Ronald Cotton, an African American man wrongfully convicted in 1984 of raping a white woman, Jennifer Thompson.

Thompson mistakenly identified Cotton as her assailant from a police lineup, despite having spent considerable time studying her attacker's face during the crime. Cotton was exonerated in 1995 after DNA evidence proved his innocence.

This case highlights the potential consequences of the cross-race effect in eyewitness identification, as Thompson's difficulty in accurately recognizing a face of a different race contributed to a miscarriage of justice.

Selected References

Brigham, J. C., & Barkowitz, P. (1978). Do “they all look alike?” The effect of race, sex, experience, and attitudes on the ability to recognize faces. Journal of Applied Social Psychology, 8(4), 306–318.

Feingold, G. A. (1914). The influence of environment on identification of persons and things. Journal of Criminal Law and Criminology, 5(1), 39–51.

Hancock, K. J., & Rhodes, G. (2008). Contact, configural coding and the other- race effect in face recognition. British Journal of Psychology, 99(1), 45– 56.

Meissner, C. A., & Brigham, J. C. (2001). Thirty years of investigating the own- race bias in memory for faces: A meta-analytic review. Psychology, Public Policy, and Law, 7(1), 3–35.

Sporer, S. L. (2001). Recognizing faces of other ethnic groups: An integration of theories. Psychology, Public Policy, and Law, 7(1), 36–97.

Business Example: The cross-race effect has significant implications in security (Meissner & Brigham, 2001). This effect can lead to critical errors in identifying individuals from surveillance footage. Studies 31

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CRYPTOMNESIA Cryptomnesia is a memory bias where a person may mistakenly believe that a thought or idea is a new inspiration when it is, in fact, a memory they have forgotten. with a woman and an elderly man at the entrance, and clutched a dripping coffee cup.

"I can't stand Candace," Ellie burst out.

"Okay, ditch the coffee. Have some mint tea and tell me everything," Rooney suggested, taking her cup.

The tea did little to soothe Ellie. "Candace stole my elephant idea for the art show," she fumed, showing Rooney a photo of Candace's painting and her own earlier sketch. Both depicted an elephant in the clouds, strikingly similar.

"They do look alike," Rooney admitted. "See? It's blatant!"

"Did you mention your idea to her?" Rooney inquired.

"No, but it's obvious she copied me!" Ellie was indignant.

"Maybe it wasn't intentional," Rooney ventured, risking her ire. "Perhaps she saw your sketch and subconsciously recreated it.

Why not talk to her? Show her your work.

And hey, you didn't invite me to the exhibition."

Ellie, sipping her tea, pondered this.

That evening, she called Rooney. "You were right. I spoke to Candace, and she withdrew her painting. Can you believe it?"

"Told you so!" Rooney beamed. "So, can I come to the exhibition?"

"Absolutely, I'll pick you up tomorrow!"

"Why are you so grumpy today? Skip the coffee, let me get you a mint tea," Rooney said, noticing Ellie's sour mood. She was forty minutes late to the café, nearly collided 32

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previous campaign by another company. This unintentional replication can lead to legal disputes over copyright infringement and damage the reputation of the agency. Businesses often implement measures such as thorough research and review processes to minimize the risk of cryptomnesia and ensure the originality of their creative output.

About: Cryptomnesia is a psychological phenomenon where an individual unknowingly recalls a memory or idea and believes it to be new and original. The term was first introduced by psychologist Théodore Flournoy in the late 19th century, based on his studies of unconscious memory processes (Flournoy, 1900). Flournoy used the term to describe instances where individuals believed they were creating new content, such as writing or artistic works, but were actually recalling previously experienced or encountered material. The concept was further explored in the context of creativity and memory, with research indicating that cryptomnesia can occur due to the failure of source memory, where individuals are unable to accurately recall the origin of their memories or ideas.

Reproducibility: Cryptomnesia has been demonstrated in various experimental studies, indicating its reproducibility as a psychological phenomenon.

Researchers have employed tasks such as writing and idea generation to induce and measure cryptomnesia under controlled conditions (Brown and Murphy, 1989; Marsh and Bower, 1993). The phenomenon has been observed across different populations and settings, suggesting its generalizability. Cryptomnesia can be influenced by factors such as the similarity of the original and recalled material, the time elapsed between exposure and recall, and individual differences in memory and cognitive processing. Ongoing research continues to explore the mechanisms underlying cryptomnesia and strategies for reducing its occurrence in creative and professional contexts.

Trivia Example: An example of cryptomnesia can be found in the work of science fiction writer Helen Keller, who unknowingly reproduced content from a previously encountered text in her short story The Frost King. At age 11, Keller submitted the story to her teacher, who published it. Later, it was discovered that the story bore significant resemblance to Margaret Canby’s The Frost Fairies, a book Keller had read earlier but had forgotten. Keller’s case is often cited in psychological literature as a classic example of cryptomnesia.

Selected References

Brown, A. S., & Murphy, D. R. (1989). Cryptomnesia: Delineating inadvertent plagiarism. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15(3), 432– 442.

Flournoy, T. (1900). Des Indes à la Planète Mars: Étude sur un cas de somnambulisme avec glossolalie. Félix Alcan.

Marsh, R. L., & Bower, G. H. (1993). Eliciting cryptomnesia: Unconscious plagiarism in a puzzle task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19(3), 673–688.

Business Example: Cryptomnesia can have significant implications, particularly in industries that rely heavily on creativity and intellectual property. For example, in advertising, a creative director might propose a campaign concept believing it to be original, only to discover later that it closely resembles a 33

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EGOCENTRIC BIAS Egocentric bias is the tendency to rely too heavily on one's own perspective and/or have a higher regard for oneself than for others.

Ellie and Rooney glided into the park on their rollerblades, weaving through a vibrant scene of young moms with new strollers, diverse dogs, and older couples. Children's laughter echoed from the playground.

At the skate ramp, they watched a teenage boy performing impressive aerial tricks. "He's great," Ellie remarked.

"Nonsense," Rooney countered. "He's reckless.

I'll show you how it's done." Ellie watched anxiously as Rooney borrowed a skateboard from a group under a tree. "Do you even know how to skate?" she asked.

"I was a champion as a kid," Rooney boasted, his confidence unwavering. "How long ago was that?" Ellie's concern grew.

Ignoring her, Rooney launched into the ramp.

He started off smoothly, gaining height with each jump, matching the teenage boy's skill. "Watch this!" he yelled, attempting a somersault. But his landing was miscalculated; he stumbled and crashed onto the ramp, his skateboard clattering away…

In the hospital, a young paramedic finished tending to Rooney. "Well, dude," he said, "your eyebrow and lip are stitched, and the rib will heal. No concussion, you're lucky.

Miss, can you take him home for me, please?"

"Thank you, Doctor, I will" Ellie replied, trying to hide her amusement.

"I'm still cool, though," Rooney insisted, grinning despite his injuries. ”Of course, who would doubt that? Cool, cool," Ellie laughed, her eyes twinkling with a mix of concern and amusement.

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About: Egocentric bias is a psychological phenomenon that refers to the tendency of individuals to view themselves as more central, influential, or important in events and interactions than they actually are. The concept has its roots in early studies of social perception and attribution, with researchers like Lee Ross and Richard Nisbett highlighting the role of egocentric biases in explaining behavior in their 1977 book “The Person and the Situation” (Ross and Nisbett, 1977). The term "egocentric bias" was used to describe the various ways in which people’s selfcentered perspective influences their perceptions, memories, and judgments. This bias is thought to stem from cognitive and motivational factors, such as the inherent salience of one’s own experiences and the desire to maintain a positive self-image.

Business Example: Egocentric bias can manifest in leadership and team dynamics. A CEO might attribute the success of their company primarily to their own strategic vision and decision-making. One example of this is Thomas Edison, who, despite having significant impact on market systems, allegedly often took sole credit for inventions like the light bulb, despite significant contributions from collaborators at Menlo Park, such as Nikola Tesla. This caused resentment among his team.

Addressing egocentric bias in leadership is essential for fostering collaboration and ensuring all contributors feel valued (Baldwin, 2001; Israel, 2000).

Reproducibility: Egocentric bias is a well-documented and reproducible phenomenon in psychological research. Studies have consistently shown that individuals exhibit egocentric tendencies in a variety of contexts, including memory recall, attribution of success and failure, and perceptions of social interactions (Ross and Nisbett, 1977; Pronin et al., 2002). The bias has been observed across different cultures and populations, indicating its robustness.

Trivia Example: An example of egocentric bias can be found in the case of the Beatles' breakup. Each member of the band, John Lennon, Paul McCartney, George Harrison, and Ringo Starr, has given different accounts of their role in the band's breakup, with each tending to emphasize their own contributions and downplay their conflicts. For instance, in various interviews, Lennon and McCartney have each suggested that they were the primary creative forces behind the band's success. This discrepancy in accounts illustrates how egocentric bias may lead individuals to overestimate their own influence in shared events, even in situations involving collaboration and teamwork.

Selected References

Baldwin, N. (2001). Edison: Inventing the century. University of Chicago Press. Israel, P. (2000). Edison: A life of invention.

John Wiley & Sons.

Pronin, E., Lin, D. Y., & Ross, L. (2002). The bias blind spot: Perceptions of bias in self versus others. Personality and Social Psychology Bulletin, 28(3), 369–381.

Ross, L., & Nisbett, R. E. (1977). The person and the situation: Perspectives of social psychology. McGraw-Hill.

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FADING AFFECT BIAS Fading affect bias describes the phenomenon that the emotion associated with unpleasant memories fades more quickly than the emotion associated with positive events.

Rooney spotted Ellie on the street, her arms cradling a brightly colored package. She seemed in a rush, hardly noticing him until he called out and blocked her path with his bicycle.

"Hi, what's the rush?" he asked.

"I'm off to our water polo team's fifth anniversary," Ellie replied, excitement in her voice. "There's a big party tonight."

Rooney, puzzled, remembered differently. "But you hated water polo. You quit after two years, saying you had no friends there."

Ellie brushed off his comment. "You're mistaken.

I had great times and friends. We went to competitions, training camps, summer camps. I've got loads of fun photos."

Rooney recalled her past distress. "Weren't you the one who had her jersey stolen and swimming cap cut? You used to cry after practices."

"That's ridiculous," Ellie dismissed, shifting the conversation to her keychains for the girls.

"Do you think they'll like these?"

Realizing the futility of his argument, Rooney conceded. "They're great. Have fun tonight. See you tomorrow!" He pedalled away, still confused.

Ellie, undeterred, continued on her way, wondering what Rooney was talking about.

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with the company are positive. This bias can work to a business's advantage, as customers are more likely to remember positive experiences and forget negative ones, leading to increased brand loyalty and repeat business. Companies can capitalize on this phenomenon by focusing on creating positive experiences and quickly addressing any negative issues to ensure they do not linger in the customer's memory.

About: The fading affect bias is a tendency for the emotional intensity of negative memories to fade more rapidly than that of positive memories (e.g., Walker et al., 1997). This phenomenon is believed to be a coping mechanism that helps individuals maintain psychological well-being and a positive self-image (Walker et al., 2003). The fading affect bias has been studied extensively in the fields of memory, emotion, and cognitive psychology, contributing to our understanding of how emotions influence the encoding, storage, and retrieval of autobiographical memories.

Reproducibility: The fading affect bias has been replicated in various studies across different cultures and populations, demonstrating its robustness (Walker et al., 2003; Ritchie et al. 2009). The bias has been observed in both experimental and naturalistic settings, however, factors such as the severity of the emotion, individual differences in emotional regulation, and the context of the memory can influence the strength of the fading affect bias (e.g., Crawford et al., 2023). Current research continues to explore the underlying mechanisms and implications of this phenomenon for mental health and well-being.

Trivia Example: A real-life example of the fading affect bias can be seen in the phenomenon known as "nostalgia."

For instance, people often look back on their college days with fondness, remembering the fun and friendships more vividly than the stress of exams or the challenges of living away from home. This selective fading of negative emotions associated with past experiences can lead to an idealized and overly positive recollection of events. The term "nostalgia" itself, coined in the 17th century by Swiss physician Johannes Hofer, originally referred to a medical condition of homesickness but has since evolved to describe a sentimental longing for the past, often with a selective memory of positive emotions.

Selected References

Crawford, M. T., Marsh, C., & Clegg, J. (2023). Be here now: Dispositional mindfulness enhances fading affect bias.

Mindfulness, 14(12), 2906– 2916.

Hofer, J. (1688). Medical dissertation on nostalgia. Basel, Switzerland.

Ritchie, T. D., Skowronski, J. J., Hartnett, J. L., Wells, B. M., & Walker, W. R. (2009). The fading affect bias in the context of emotion activation level, mood, and personal theories of emotion change. Memory, 17(8), 822– 832.

Walker, W. R., Skowronski, J. J., & Thompson, C. P. (2003). Life is pleasant— and memory helps to keep it that way! Review of General Psychology, 7(2), 203–210.

Walker, W. R., Vogl, R. J., & Thompson, C. P. (1997).

Autobiographical memory: Unpleasantness fades faster than pleasantness over time. Applied Cognitive Psychology, 11, 399–413

Business Example: The fading affect bias can have implications for customer satisfaction and loyalty. For example, a customer who has a negative experience with a product or service may initially feel dissatisfied and frustrated. However, over time, the emotional impact of this negative experience may fade, especially if subsequent interactions 37

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FALSE MEMORY False memory is a mental experience that is mistakenly taken to be a veridical representation of an event from one's personal past.

"Hi, you remember about tomorrow, right?"

Rooney's voice echoed from the speaker.

"Remember what?" Ellie asked, still half-asleep.

"Our fishing trip with my uncle. We're leaving at 4 AM. You haven't forgotten, have you?"

"You've reminded me five times today, Rooney.

I'm packed and ready. My parents are at grandma's, coming back tomorrow night.

I've set the alarm," Ellie reassured him, her voice tinged with sleepiness.

"Double-check the alarm, will you?" Rooney persisted.

"I did, Rooney. Good night," Ellie replied, eager to return to sleep. "See you in the morning," Rooney's voice faded as the call ended.

Ellie was later jolted awake by her father. "It's seven in the evening, sleepyhead."

"What time is it?" Ellie panicked, realizing she missed the fishing trip. "Hi, Dad. When did you get back?"

"Just now. Your phone's been ringing nonstop," her father informed her.

Ellie grabbed her phone to Rooney's irate voice.

"What happened?" "I overslept," she admitted guiltily.

"I told you to check your alarm," Rooney fumed.

"I rang your doorbell, called your phone. Your neighbors almost called the police!" "I'm sorry, Rooney. Did you catch much?"

There was a pause. "Actually, quite a lot. Wish you were there. I'll tell you all about it when I get back tomorrow."

The phone's ringtone pierced the evening silence.

"Yes?" Ellie mumbled, sleepily tapping the speakerphone on her smartphone. She had just dozed off.

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backlash ensued, with many recalling the original Coca-Cola as superior, likely influenced by nostalgia and emotional attachment to the brand. This apparent false memory bias led consumers to misremember the taste of the original formula more favorably than it was. In response, Coca-Cola reintroduced the original as “Coca-Cola Classic,” which became a marketing triumph.

About: The concept of false memory emerged from research on the malleability of human memory and the factors that can lead to distortions in recall (Bulatova & Fukuda, 2025). Early studies demonstrated that memory is not a perfect reproduction of past events but is instead subject to reconstruction and influenced by existing knowledge and beliefs (Bartlett, 1932) . The term "false memory" gained prominence in the 1990s, particularly through the work of Elizabeth Loftus, who conducted seminal experiments illustrating how suggestions and leading questions can implant false memories in individuals' minds. Loftus' research showed that people could be made to believe they had experienced events that never actually occurred (Loftus, 1997).

Reproducibility: False memory is a well-replicated phenomenon in psychological research, with numerous studies demonstrating its occurrence across different contexts and methodologies.

Experiments using techniques such as the DeeseRoediger-McDermott (DRM) paradigm have consistently shown that people can develop false memories for words that were not presented in a list but are semantically related to the words that were (Roediger and McDermott, 1995). Though factors such as individual differences in susceptibility to suggestion, the plausibility of the false event, and the retrieval cues used can influence the likelihood and strength of false memory formation, the phenomenon has been observed in various populations and settings, indicating its robustness.

Trivia Example: A well-known example of false memory occurred in the case of the "Paul is dead" conspiracy theory surrounding The Beatles. In 1969, rumours began to circulate that Paul McCartney had died and been replaced by a look- alike. Fans claimed to find clues in the band's music and album artwork, such as the sound of a car crash in the song "Revolution 9" when played backward and the imagery on the cover of "Abbey Road." These clues led some people to develop false memories of hearing about McCartney's death on the news or noticing sudden changes in his appearance, despite the fact that McCartney was alive and well.

Selected References

Bartlett, F. C. (1932). Remembering: A study in experimental and social psychology. Cambridge University Press.

Bulatova, O., & Fukuda, K. (2025). Prediction-based false memory: Unconfirmed prediction can result in robust false memories. Cognition, 255, 106013.

Loftus, E. F. (1997). Creating false memories. Scientific American, 277(3), 70–75.

Roediger, H. L., & McDermott, K. B. (1995). Creating false memories: Remembering words not presented in lists.

Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(4), 803–814.

Business Example: False memory may have significant implications for brand perception and consumer behavior. In 1985, Coca-Cola launched New Coke after blind taste tests showed consumers preferred it to the original formula and Pepsi. However, public 39

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GENERATION/SELF-GENERATION EFFECT Generation/Self-generation effect is the tendency to better remember information if one generates it oneself rather than passively receives it. and so on," Ellie replied. Rooney nodded.

"It's not about the explanation, but the approach. People remember better when they figure out the answer logically, rather than just memorizing. For the 9s table, you can show him how 9 times any number is like 10 times that number minus the number itself. It's more about understanding than memorizing."

Ellie's interest piqued. "Really?"

"Yeah, watch this!" Rooney grabbed a piece of paper and a pen. He wrote down the 9s multiplication table, leaving blanks for the answers. "Now, for each multiplication, think of it as 10 times the number minus the number. So, 9 times 2 is like 20 minus 2, which is 18."

Ellie's mood visibly brightened.

"And here's another trick," Rooney continued.

He wrote down the table again, this time placing dots to represent tens and ones.

"For each multiplication from 9 times 2 onwards, subtract 1 from the number to get the tens. So, for 9 times 2, it's 2 minus 1, which is 1 ten. Then, write the units in reverse order from 0 to 9."

He demonstrated the method, filling in the table with the correct answers. Ellie watched in amazement.

"Wow! That's fantastic!" Ellie exclaimed.

"Thanks, I'll definitely try this." "Give it a shot. I bet your student will catch on quickly!" Rooney encouraged.

"I see you're in a bad mood today," Rooney observed, careful not to upset Ellie further.

"What's going on?"

"My dad asked me to teach the multiplication table of 9 to the boy next door. I've explained it 20 times, but he just can't grasp it. I'm at my wit's end. Maybe I'm not explaining it well," Ellie sighed.

"How did you teach him?" Rooney inquired.

"Just the usual way. 9 times 1 is 9, 9 times 2 is 18, 40

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This approach can lead to better retention of knowledge and skills, as employees are more actively engaged in the learning process (Berge, 2022). Additionally, encouraging employees to create their own summaries or teach-backs of key concepts can further enhance memory retention and understanding, applying the principles of the generation effect to improve training outcomes.

About: The generation effect, also known as the selfgeneration effect, is a psychological phenomenon that describes the improved memory retention of information that an individual actively generates or creates compared to information that is passively received. Early research demonstrated that participants were better at recalling words that they had generated themselves (e.g., by completing a word stem) than words that were simply presented to them (Slamecka and Graf, 1978). This effect is believed to be due to the increased cognitive engagement and deeper processing involved in generating information, which enhances encoding and retrieval. The generation effect has been extensively studied in the context of learning and memory (Bertsch et al., 2007).

Reproducibility: The generation effect has been extensively studied, with numerous theories attempting to explain its mechanisms and boundary conditions. A comprehensive meta-analysis of 126 articles has demonstrated that while some theoretical accounts are supported, others lack empirical backing (McCurdy et al., 2020).

Additionally, the impact of generation constraints—how strictly participants are guided to produce a specific response—emerged as a significant factor influencing the magnitude of the effect. These findings highlight the complexity of the generation effect and suggest that future research should further explore the roles of item and context memory, as well as generation constraints, in shaping this robust phenomenon.

Trivia Example: In many contexts, the generation effect can be seen in the creation of mnemonics, which are often used to remember lists or sequences of information. For instance, the mnemonic "Every Good Boy Deserves Fruit" is commonly used to remember the notes on the lines of the treble clef in music (E, G, B, D, F). By generating a meaningful phrase they can relate to, individuals can more easily recall the sequence of notes, demonstrating the enhanced memory retention associated with self-generated information.

Selected References

Berge, Z. L. (2022). Designing workplace training for generational differences: Does it matter? Merits, 2(4), 400–407.

Bertsch, S., Pesta, B. J., Wiscott, R., & McDaniel, M. A. (2007). The generation effect: A meta-analytic review. Memory & Cognition, 35(2), 201–210.

McCurdy, M. P., Viechtbauer, W., Sklenar, A. M., Frankenstein, A. N., & Leshikar, E. D. (2020). Theories of the generation effect and the impact of generation constraint: A metaanalytic review. Psychonomic Bulletin & Review, 27(6), 1139–1165.

Slamecka, N. J., & Graf, P. (1978). The generation effect: Delineation of a phenomenon. Journal of Experimental Psychology: Human Learning and Memory, 4(6), 592–604.

Business Example: The generation effect can be leveraged in training and development programs. For example, a company might use interactive learning modules that require employees to generate answers or solutions to problems rather than simply reading or listening to information.

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GOOGLE EFFECT Google effect (also known as digital amnesia) is the tendency to forget information that can be easily found using internet search engines. boxes, but they don't fit together," Ellie gestured towards the materials piled in the corner.

"Can I see your order list?" Rooney asked.

Ellie handed him the receipt. Rooney examined it closely. "Ah, I see the problem. You've got the frame size in inches and the crate size in centimeters. They won't match."

"I know an inch is 2.54 centimeters. I can't believe I overlooked that," Ellie said, annoyed with herself.

“Seriously? 2.54 centimeters? I thought it was 2.

Let me quickly Google it,” said Rooney.

"You're the mathematician, shouldn't you know these conversions?"

Rooney chuckled. "Why remember what I can easily find online? It's not essential to keep everything in your head."

Ellie was taken aback. "But it's common knowledge!"

"Maybe, but it's more efficient to look things up when needed," Rooney reasoned.

"So, what do I do now? Should we return the frames and order new ones?" Ellie pondered.

"Why go through all that hassle? Let's just adjust the frames ourselves. Grab some tools and a tape measure, and we'll fix them right up!" Rooney suggested with a confident smile.

"

Thanks for agreeing to help," Ellie said, her tone laced with frustration.

"No problem," Rooney replied. "What's the issue?"

"I tried making a new bed for the orchids in the greenhouse. I bought wooden frames and 42

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retrieval. For example, a marketing team might use a shared online database to store market research data. While this allows for easy access to information, team members may be less likely to remember the details of the research themselves, relying instead on the database for retrieval. This reliance on digital memory systems can have implications for knowledge retention and decision-making processes within organizations.

Businesses may need to balance the convenience of digital tools with strategies that promote internal memory retention and critical thinking among employees.

About: The Google effect, also known as digital amnesia, is a psychological phenomenon where individuals are less likely to remember information that they can easily access online using search engines like Google. The term was popularized in a study, which investigated the impact of the internet on memory processes (Sparrow et al., 2011). Research showed that when people expect to have access to information in the future, they are less likely to remember it and more likely to remember where to find it instead.

This effect reflects a shift in memory strategies, where individuals rely on external memory systems (e.g., the internet or their smartphones) for storing and retrieving information. The Google effect highlights the influence of digital technology on cognitive processes.

Reproducibility: The Google effect is a relatively new phenomenon in psychological research. To date, research has shown that individuals are more likely to remember how to find information than the information itself when they know it is available online (Ward, 2021). Yet, it is too early to make conclusions about the effect’s robustness.

Further research is needed to explore the longterm implications of the Google effect on memory and cognition.

Trivia Example: A real-world example of reliance on external aids impacting memory is seen in taxi drivers who depend on navigation systems. Traditional cab drivers, who memorize complex city layouts like London’s “The Knowledge,” show enhanced spatial memory and hippocampal growth. In contrast, drivers who rely heavily on GPS often demonstrate weaker memory for routes and landmarks, as their reliance on external devices reduces the need to internally encode and retain spatial information. This phenomenon reflects how dependence on external tools, can diminish internal memory retention over time (Maguire et al., 2000).

Selected References

Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S., & Frith, C. D. (2000).

Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences, 97(8), 4398–4403.

Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776–778.

Ward, A. F. (2021). People mistake the internet’s knowledge for their own. Proceedings of the National Academy of Sciences, 118(43), e2105061118.

Business Example: The Google effect can be seen in the way employees rely on digital tools for information

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HUMOR EFFECT Humor effect refers to the phenomenon where humorous items are more easily remembered than non-humorous ones.

"What do you think?" Rooney asked, a smug smile on his face.

Ellie, yawning, replied, "It's cool, I guess. But I don't know much about it."

Rooney, who had been rehearsing his math club presentation for the past hour, felt a twinge of annoyance. "You seem bored, and I need this presentation to be engaging. I don't want to put everyone to sleep tomorrow."

"Okay, let me try to help," Ellie said, more seriously. "Your presentation is a bit dry.

To appeal to a broader audience, you should mix in some humor."

"Humor? In a math presentation?" Rooney asked, skeptical.

"Yes! Humor makes information more digestible and memorable," Ellie insisted.

"But I don't know any jokes about integrals," Rooney admitted.

Ellie thought for a moment. "How about this one? A father checks his son's notebook: 'Why are your brackets so uneven?'

'They're not brackets, Dad, they're integrals.'" Rooney chuckled.

"Alright, I'll search for some integral jokes online," Rooney conceded, now more optimistic.

The next evening, Ellie received a call from her friend Mira. "You won't believe it, I ended up at a math club presentation yesterday. It was surprisingly fun! There was this guy talking about integrals – really interesting and funny. I even signed up for the club!"

"I'm sure you'll enjoy it!" Ellie replied, smiling to herself.

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premise, combined with the camel’s exaggerated personality, made the ad an instant hit. This campaign significantly boosted Geico’s brand recall and engagement. The ad garnered millions of views online and became a cultural phenomenon, with “Hump Day” jokes and references proliferating on social media. By leveraging humor, Geico effectively created a memorable, shareable marketing moment that enhanced its brand visibility and consumer connection.

About: The humor effect is a psychological phenomenon that describes the enhanced recall of humorous material compared to non-humorous material.

While the effect of humour on human psyche has been a subject of research for many centuries, systematic investigation of the humor effect on memory began in the latter half of the 20th century (e.g., Savage et al., 2017). Early empirical studies on the topic demonstrated that humorous sentences were better remembered than non-humorous ones (e.g., Goldstein and McGhee, 1972). The humor effect is believed to be due to the emotional arousal and increased attention that humorous material elicits, leading to more effective encoding and retrieval processes.

Reproducibility: The humor effect is a well-documented phenomenon with numerous studies supporting its reproducibility (e.g., Summerfelt et al., 2010).

Research has consistently shown that humorous material is better remembered than nonhumorous material across various contexts and populations (Schmidt, 1994; Garner, 2006). The effect has been observed in different types of humor, including verbal jokes, visual gags, and situational comedy, though factors such as the type of humor, the relevance of the humour to the material, and individual differences in humor appreciation can influence the strength of the effect.

Trivia Example: The humor effect can be seen in the famous "Who's on First?" comedy routine by Abbott and Costello. This sketch, first performed in the 1930s, involves a humorous dialogue about a baseball team with confusing player names. The routine has become iconic and is widely remembered and referenced, even decades after its initial performance. The lasting impact and recall of this humorous sketch demonstrate the humor effect in action, as the comedic nature of the routine has made it more memorable than many other contemporaneous performances.

Selected References

Garner, R. L. (2006). Humor in pedagogy: How ha-ha can lead to aha! College Teaching, 54(1), 177–180.

Goldstein, J. H., & McGhee, P. E. (1972). The psychology of humor.

Journal of Communication, 22(4), 367–386.

Savage, B. M., Lujan, H. L., Thipparthi, R. R., & DiCarlo, S. E. (2017).

Humor, laughter, learning, and health! A brief review.

Advances in Physiology Education.

Schmidt, S. R. (1994). Effects of humor on sentence memory.

Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(4), 953–967.

Summerfelt, H., Lippman, L., & Hyman Jr, I. E. (2010). The effect of humor on memory: Constrained by the pun. The Journal of General Psychology, 137(4), 376–394.

Business Example: The humor effect is exemplified by Geico’s “Hump Day” commercial, part of its “Happier Than” series. Released in 2013, the ad features a camel walking through an office asking employees, “Guess what day it is?” to which they respond, “It’s Hump Day!” The humorous

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LAG EFFECT The lag effect is the idea that spreading out study sessions over time helps people remember better than studying everything all at once. down the street. I need to learn this script for the casting session. Focus, you're Rob, and I'm Maria," Ellie instructed.

Rooney nodded seriously and began, "Maria?

How did you end up here?"

Ellie fell silent. Rooney looked up, puzzled, but she remained quiet. Suddenly, she exclaimed, "I've forgotten all my lines again! Why can't I remember my lines? I've been repeating them all day."

"Let's start over. Just talk to me," Rooney suggested soothingly, and read his line again.

Ellie was silent once more. Rooney, trying to help, whispered in a mock female voice, "I was just passing by."

"Don't prompt me!" Ellie snapped, frustrated. "I can't understand why I can't remember it!"

"Let's take a break and go for a walk. It might help," Rooney proposed. "A walk? I need to memorize this," Ellie protested.

"It's Saturday, and your casting isn't until Monday. A break could really help," Rooney reasoned.

Finally, Ellie agreed. After a three-hour walk, they returned to her kitchen. Rooney read his line again, "Maria? How did you end up here?"

"I was just passing through. So, I thought I'd stop by," Ellie responded, surprising herself with her perfect recall. She laughed, realizing the break had worked wonders.

"Here are your lines. You're going to read for a character named Rob," Ellie said, handing Rooney a script. "What's this for?" Rooney asked.

"I'm auditioning for an amateur theatre group 46

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approach helps create long-term brand associations and improves the likelihood of purchase decisions. Spacing out campaigns rather than concentrating all efforts at once leverages the lag effect to build and sustain consumer engagement and memory retention.

About: The lag effect is a psychological phenomenon observed in the study of memory, particularly in the context of spaced repetition and distributed practice (e.g., Pyc et al., 2014). It refers to the improved retention of information when there is a longer interval or "lag" between learning sessions. Early research by Hermann Ebbinghaus showed that memories became more durable with spaced repetitions, laying the groundwork for the subsequent investigation of the lag effect (Ebbinghaus, 1885). Later research further explored this phenomenon, showing that varying the lag between repetitions can enhance memory consolidation and retrieval (e.g., Melton, 1970; Cepeda et al., 2006).

Reproducibility: The lag effect is a well-replicated phenomenon in the field of psychology, with numerous studies demonstrating its impact on memory retention across different contexts and populations.

Research has consistently shown that spaced repetition with varying lags between learning sessions leads to better long- term memory retention compared to massed practice (Cepeda et al., 2006; Dunlosky et al., 2013). While the optimal lag duration may vary depending on factors such as the complexity of the material and the individual's learning style, the effect has been observed in various learning materials, including verbal, visual, and motor skills.

Trivia Example: One example of the lag effect can be seen in the memorization of lines by actors. Sir Anthony Hopkins, known for his meticulous preparation for roles, has reportedly used spaced repetition techniques for many years to memorize his lines.

By rehearsing lines with increasing intervals between sessions, actors take advantage of the lag effect to enhance their memory retention, ensuring that their performances are not only convincing in the short term but also enduring over the course of long shoots and theatre runs.

Selected References

Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380.

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology.

Psychological Science in the Public Interest, 14(1), 4–58.

Ebbinghaus, H. (1885). Über das Gedächtnis: Untersuchungen zur experimentellen Psychologie [On memory: Investigations in experimental psychology]. Duncker & Humblot.

Melton, A. W. (1970). The situation with respect to the spacing of repetitions and memory. Journal of Verbal Learning and Verbal Behavior, 9(5), 596– 606.

Pyc, M. A., Balota, D. A., McDermott, K. B., Tully, T., & Roediger, H. L. (2014).

Between-list lag effects in recall depend on retention interval.

Memory & Cognition, 42, 965–977

Business Example: The lag effect is evident in marketing strategies where advertisements are spaced over time to enhance consumer recall. For example, CocaCola’s holiday campaigns often reintroduce similar themes and visuals annually, with reminders spread throughout the season. By timing these ads at regular intervals, Coca-Cola ensures their message stays fresh in consumers’ minds without overwhelming them. This 47

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LIST-LENGTH EFFECT List-length effect occurs when the length of a list affects the recall of items on the list. Typically, shorter lists result in better recall, but the effect can vary.

"What's on your mind?" Rooney asked, noticing Ellie's distant expression.

"I'm struggling to remember dates for my art history presentation at the museum. I need to recall key events like Degas' birth and when he painted certain works," Ellie explained.

"Why not use slides?" Rooney suggested.

"I can't. There's no computer. I'll be speaking in front of the painting," Ellie clarified.

"How many dates are there?"

"I haven't counted," Ellie shrugged.

"Let's jot them down," Rooney said, grabbing a pen and paper. Minutes later, they had a list of seven dates.

"Only seven. That's manageable," Rooney observed.

"But I can't seem to remember them," Ellie sighed, indicating she only remembered three.

Rooney had an idea. "What if we expand the list?

It's proven that people remember more from a longer list than a short one."

"Really?" Ellie looked skeptical.

"Trust me, let's add a few more dates and see," Rooney encouraged. Reluctantly, Ellie agreed. The next evening, she called Rooney, her voice bright. "Hi, how did it go?" Rooney asked.

"Amazingly, I remembered almost all the dates!

Expanding the list really worked. Thanks!"

Ellie exclaimed.

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shopping lists and product choices. For example, a shopper with a long grocery list may be more likely to forget items or make errors in their selections compared to a shopper with a shorter list. Retailers can leverage this effect by strategically placing commonly forgotten items or impulse buys near the checkout area, increasing the likelihood that shoppers will remember or notice them at the last minute, even if they were not initially on their list.

About: The list-length effect is a phenomenon observed in memory research, particularly in the context of serial recall tasks. It refers to the finding that as the length of a list of items to be remembered increases, the likelihood of accurately recalling any given item from the list decreases. In 19th century, Hermann Ebbinghaus explored the capacity and limitations of human memory (Ebbinghaus, 1885), while subsequent research further investigated the list-length effect, demonstrating its impact on memory performance (e.g., Murdock, 1962; Watkins, 1974).

The list-length effect arises from a combination of increased interference among items, retention interval, attention, and contextual reinstatement.

Reproducibility: The list-length effect is a robust phenomenon in cognitive psychology, with numerous studies replicating its impact on memory recall. Research has consistently shown that recall accuracy decreases as the length of the list increases, across various types of stimuli and memory tasks (e.g., Bartoš and Gangur, 2023). The magnitude of the effect was found to vary depending on factors such as the type of material, the encoding conditions, and the retrieval cues provided.

Trivia Example: A real-life example of the list-length effect can be seen in the game show "Family Feud," where contestants are asked to recall items from a list based on survey responses. As the number of items on the list increases, contestants often struggle to remember all the responses, especially those mentioned less frequently by the surveyed audience. This demonstrates how the list-length effect can impact memory recall in a high-pressure, time-constrained environment.

Selected References

Bartoš, P., & Gangur, M. (2023). The list length effect and immediate free recall of visually displayed information in various forms. TEM Journal, 12(3), 1533–1540.

Ebbinghaus, H. (1885). Über das Gedächtnis: Untersuchungen zur experimentellen Psychologie [On memory: Investigations in experimental psychology]. Duncker & Humblot.

Murdock, B. B. (1962). The serial position effect of free recall.

Journal of Experimental Psychology, 64(5), 482–488.

Watkins, M. J. (1974). Concept and measurement of primary memory. Psychological Bulletin, 81(11), 695–711.

Business Example: The list-length effect can be observed in consumer behavior, particularly in the realm of

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LEVELS-OF-PROCESSING EFFECT Levels-of-processing effect suggests that memory recall is better if the information is processed at a deeper level.

"Your tea and berry smoothie," said the blond waiter with a pleasant face, placing the tray before Rooney and Ellie. They had been in the cafeteria for an hour, planning their weekend.

"Thanks," Rooney replied, noticing the waiter for the first time, despite this being their second order.

As the waiter, who also doubled as a barista, vanished behind the bar, Rooney turned to Ellie. "I feel like I've seen that guy before, but I can't place him."

"That's Oliver!" Ellie's eyes widened in recognition.

"Oliver?" Rooney echoed, puzzled. "How do you know him?"

"You've forgotten already? You worked with him last summer at that downtown café," Ellie reminded him.

Rooney racked his brain. "I did?"

"Yes, he was your coworker. Remember the endof-summer party? You introduced me to him," Ellie explained.

Rooney's memory clicked. "Oh, right! Oliver. He joined just before I left. How did you remember him, especially his name?"

Ellie laughed. "He reminded me of your little brother, also blond and named Oliver. It's funny how that works."

"Ah, yes, my brother Oliver. Now it makes sense," Rooney said, finally connecting the dots as he sipped his tea.

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by imagining how it would fit into their lives (deep processing) is likely to be more memorable than an advertisement that simply presents the product's features (shallow processing). This principle is used in interactive marketing campaigns, where customers are invited to participate in challenges, quizzes, or storytelling related to the product, thereby enhancing recall and brand association.

About: The levels-of-processing effect is a psychological phenomenon that suggests the depth of mental processing applied to information affects its subsequent recall. In 1972 Fergus I. M. Craik and Robert S. Lockhart proposed a framework for understanding memory that contrasted with the traditional stage theories of the time. Instead of focusing on separate memory stores (e.g., shortterm and long-term memory), Craik and Lockhart argued that memory retention is a function of the depth of processing, with deeper, more meaningful processing leading to better recall (Craik and Lockhart,1972). This idea led to many subsequent studies, emphasizing the importance of encoding processes and the nature of mental representations in memory formation and retrieval (e.g., Craik and Tulving, 1975; Eysenck, 1979).

Reproducibility: The levels-of-processing effect is a highly replicable phenomenon in cognitive psychology, with numerous studies supporting its validity across different types of stimuli and memory tasks. Research has consistently shown that deeper, more semantic processing of information leads to better recall than shallow, surface-level processing. The effect has been observed in various populations and settings, indicating its robustness. Factors such as the specific nature of the processing task, the type of material being processed, and individual differences in cognitive abilities can influence the strength of the effect (e.g., Peng et al., 2024).

Trivia Example: An example of the levels-of-processing effect can be seen in the memorization of song lyrics.

People often find it easier to remember lyrics that they have analyzed or related to personally (deep processing) compared to lyrics they have simply heard repeatedly without much thought (shallow processing). For instance, fans of the Beatles might remember the lyrics to "Yesterday" not just because they have heard the song many times, but because they have thought deeply about the song's meaning and how it relates to their own experiences.

Selected References

Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11(6), 671-684.

Craik, F. I. M., & Tulving, E. (1975). Depth of processing and the retention of words in episodic memory. Journal of Experimental Psychology: General, 104(3), 268-294.

Eysenck, M. W. (1979). Depth, elaboration, and distinctiveness. In L. S. Cermak & F. I. M. Craik (Eds.), Levels of processing in human memory (pp. 89- 118). Lawrence Erlbaum Associates.

Peng, N., Logie, R. H., & Della Sala, S. (2024). Effect of levels-ofprocessing on rates of forgetting. Memory & Cognition, 118.

Business Example: The levels-of-processing effect is applied in marketing and advertising strategies. For example, an advertisement that encourages consumers to actively engage with the product 51

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LEVELING AND SHARPENING Labeling is the process of assigning a word or phrase to an experience, which can affect memory and perception. Sharpening refers to the exaggeration of certain details in a memory over others..

"Wow, I didn't expect you to make it to the exhibition," Ellie expressed her surprise.

"I almost didn't, with all the work I had. But I'm glad I could come. Thanks for inviting me; it was really fascinating!" Rooney replied with genuine interest.

"I'm happy you enjoyed it. Which piece stood out to you the most?" Ellie inquired.

"To be honest, contemporary art usually isn't my cup of tea, but that painting with the balloon really caught my eye," Rooney said, his enthusiasm evident. "You know, the one at the end? It had this incredible 3D effect. At first glance, I thought it was a sculpture."

Ellie chuckled. "Oh, I know the one! But it's actually not a balloon; it's a polyhedron.

From afar, it resembles a ball, but up close, you can see its many faces and angles. It creates a fascinating effect."

"A polyhedron, really? I mistook it for a ball.

Well, I liked it regardless. It shows how little I know about art," Rooney admitted with a smile.

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campaigns, a company might level out complex technical specifications of a product to avoid overwhelming consumers, while sharpening the benefits that are most relevant to the target audience. This selective emphasis helps create a more compelling and memorable message that resonates with consumers' needs and preferences.

About: Leveling and sharpening are psychological phenomena related to memory distortion.

Frederic Bartlett introduced the concept of "effort after meaning" and proposed that when people try to recall a complex or unfamiliar story, they tend to level (simplify or omit details) and sharpen (emphasize or elaborate on certain details) the information based on their own cultural background and personal experiences (Bartlett, 1932). This theory was a departure from the view of memory as a passive storage system, suggesting instead that memory is an active, constructive process influenced by prior knowledge and expectations (e.g., Neisser, 1967).

Reproducibility: The phenomena of leveling and sharpening have been replicated and observed in various studies on memory and storytelling. Research has consistently shown that when people recall information, they tend to simplify complex details and emphasize certain elements based on their own cognitive biases and cultural influences However, the degree of leveling and sharpening can vary depending on factors such as the individual's familiarity with the material, the context of recall, and the social dynamics of the storytelling situation. Ongoing research continues to explore the mechanisms underlying these memory distortions and their implications for understanding human cognition (e.g., Van Geert et al., 2023)

Trivia Example: Leveling and sharpening can be seen in the retelling of urban legends or folktales. For instance, the story of "The Vanishing Hitchhiker" has many versions that differ in detail, but the core elements remain the same. As the tale is passed from person to person, certain details may be leveled out (e.g., the specific location of the encounter), while others are sharpened (e.g., the mysterious disappearance of the hitchhiker).

This process of selective emphasis and omission helps the story adapt to different cultural contexts while retaining its essential narrative.

Selected References

Bartlett, F. C. (1932). Remembering: A study in experimental and social psychology. Cambridge University Press.

Neisser, U. (1967). Cognitive psychology. Appleton-CenturyCrofts.

Van Geert, E., Frérart, L., & Wagemans, J. (2023). Towards the most prägnant Gestalt: Leveling and sharpening as contextually dependent adaptive strategies. Memory & Cognition, 1-25.

Business Example: Leveling and sharpening can be observed in the way companies communicate their brand stories or product features. For example, in advertising

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MOOD-CONGRUENT MEMORY BIAS Mood-congruent memory bias is the tendency for individuals to recall information more easily when it has the same emotional content as their current mood.

Rooney strode down the street, buoyed by high spirits. Fresh from summer tennis camp, he carried the summer cup he'd won, eager to share his triumph with Ellie. His plan to visit her later took an unexpected turn when he spotted her right outside his house, her mood visibly sour.

"Hi, Ellie! I was just heading to see you. Guess what? I won the Summer Cup!" Rooney beamed, then noticed her gloom. "Hey, why don't we celebrate at the club tonight?

There's a great DJ playing. Remember how fun it was last time?"

"I'm not in the mood for a club," Ellie snapped, her irritation palpable. Rooney, taken aback, quipped, "You seem thrilled."

"Can't you see?" Ellie pointed to her shoes.

Rooney then noticed the broken heel on her right shoe. "They were new, and now look at them. I barely made it here. Can you help me fix it?"

"Of course! Let's head to my place," Rooney replied, his cheer undimmed.

"What about the club?"

"Forget the club. I had a terrible time there last time. The music was awful, it was overcrowded, and some guy spilled coffee on my dress," Ellie grumbled.

"He tripped, Ellie. It was an accident," Rooney tried to reason. "Accident or not, my dress is ruined. I'm done with that club."

"Okay, let's skip the club. Come on, I'll make you some tea, and we'll see about fixing your shoe," Rooney offered, extending a comforting hand.

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About: The concept of mood-congruent memory bias, which is the tendency to recall information that is consistent with one's current mood, originated from the broader study of memory and affective states. In the 1970s and 1980s, researchers like Gordon Bower and Eric Eich began to explore how emotional states influence memory processes (e.g., Bower, 1981; Eich, 1995). Bower's associative network theory of memory, proposed in the 1980s, suggested that emotions can activate related memories, leading to the preferential recall of mood- congruent information. This theory laid the groundwork for understanding how mood states can serve as retrieval cues, shaping what we remember. The moodcongruent memory bias has since been extensively studied, contributing to our understanding of the interplay between emotion and memory.

Business Example: The mood-congruent memory bias can impact customer feedback and reviews. For example, a customer who has a negative experience at a restaurant may be in a bad mood when leaving feedback, leading them to selectively recall and emphasize other negative aspects of their visit, such as minor service issues or dissatisfaction with the food. This bias can result in disproportionately negative reviews, which may not fully represent the overall quality of the restaurant. Understanding this bias is important for businesses in managing customer relations and interpreting feedback.

Reproducibility: The mood-congruent memory has been consistently replicated in psychological research.

The bias has been observed across various emotional states, types of memory tasks, and populations. While factors such as the intensity of the mood, the nature of the to-be-remembered material, and individual differences in emotional regulation can influence the strength of the bias, ongoing research continues to explore the underlying mechanisms of mood-congruent memory bias and its implications for mental health and cognitive therapy (e.g., Faul and LaBar, 2023).

Trivia Example: A notable example of mood-congruent memory bias can be observed in music composition (Boltz, 2004). Artists like Adele, during emotionally charged periods such as heartbreak, often create songs that reflect themes of loss and sorrow. This bias suggests that their emotional state enhances the recall of similar past experiences, shaping the content and tone of their work. Adele’s album 21 is a case in point, as her emotional state during its creation reportedly influenced the deeply resonant and melancholic themes that connected with millions of listeners worldwide.

Mood-congruent memory plays a key role in such emotionally rich creative expressions.

Selected References

Boltz, M. G. (2004). The cognitive processing of film and musical soundtracks Memory & Cognition, 32, 1194–1205.

Bower, G. H. (1981). Mood and memory. American Psychologist, 36(2), 129– 148.

Eich, E. (1995). Mood as a mediator of place dependent memory.

Journal of Experimental Psychology: General, 124(3), 293– 308.

Faul, L., & LaBar, K. S. (2023). Mood-congruent memory revisited.

Psychological Review, 130(6), 1421–1456.

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MISINFORMATION EFFECT Misinformation effect occurs when a person's recall of episodic memories becomes less accurate due to post-event information.

"Hi, Rooney," Ellie's father greeted him warmly as he opened the door. "Ellie, Rooney's here!"

"Thanks, Dad," Ellie called out, bustling into the hallway while struggling into her jacket. "We're heading to rehearsal. We're both in a play." "Really? What's the play about?" her father inquired with interest.

"It's a musical, Dad. You'll see it in four months," Ellie replied, keeping the details under wraps.

Her father smiled nostalgically. "I remember you playing out scenes from Shakespeare with your brother when you were little. You were so good, even learned to read at three!"

Ellie kissed her father on the cheek, laughing.

"Dad, I love you, but I definitely couldn't read at three. We did have a home theater and costumes, though."

"Maybe not at three, but you were always so talented," her father chuckled.

"Alright, have fun. See you tonight!"

With a wave, Ellie and Rooney headed out for their rehearsal.

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false rumor about a food product containing harmful substances can lead to altered memories of past experiences with the product, even if the rumor is later debunked. This can result in longterm damage to the brand, as consumers may continue to associate the product with the misinformation. Companies need to actively manage their reputation and quickly address any misinformation to prevent lasting negative effects on consumer perceptions.

About: The misinformation describes how exposure to misleading information after an event can lead to distorted memories of that event. The concept was first introduced by Elizabeth Loftus and John Palmer in 1974, in a study where participants watched a film of a car accident and were then asked questions about the speed of the cars (Loftus and Palmer, 1974).

The wording of the questions influenced participants' estimates of the speed and their memories of the accident. This seminal research demonstrated that people's memories are not static but can be altered by subsequent information, a finding that has profound implications for eyewitness testimony, legal proceedings, and the study of memory (e.g., Loftus, 1975; Loftus and Hoffman, 1989).

Reproducibility: Many studies demonstrated the effect’s impact on memory across different contexts and populations. Factors such as the plausibility of the misinformation, the timing of its presentation, and individual differences in susceptibility to suggestion have been found to influence the strength of the effect. Nevertheless, the effect has been observed in various experimental paradigms, including those involving eyewitness testimony, autobiographical memory, and social media (e.g., Loftus, 2005).

Trivia Example: The misinformation effect can be seen in the case of the "Balloon Boy" incident in 2009. A family in Colorado reported that their six-year-old son was trapped in a homemade helium balloon that had floated away. The story received extensive media coverage, and many people formed vivid memories of seeing footage of the boy in the balloon. However, it was later revealed that the boy was hiding in his home the entire time, and there was no footage of him in the balloon. The widespread dissemination of false information led to the creation of false memories in the public's mind.

Selected References

Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 13(5), 585-589.

Loftus, E. F. (1975). Leading questions and the eyewitness report.

Cognitive Psychology, 7(4), 560-572.

Loftus, E. F., & Hoffman, H. G. (1989). Misinformation and memory: The creation of new memories. Journal of Experimental Psychology: General, 118(1), 100-104.

Loftus, E. F. (2005). Planting misinformation in the human mind: A 30-year investigation of the malleability of memory.

Learning & memory, 12(4), 361-366.

Business Example: In the business world, the misinformation effect can impact consumer perceptions and brand reputation. For example, a

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MODALITY EFFECT Modality effect refers to how memory performance can differ based on the mode of information presentation, with better recall for auditory information than for visual information.

"What are you searching for?" Ellie inquired, watching Rooney rummage through drawers.

"My keys. I lost them somewhere," Rooney replied, clearly flustered. "Think back to when you last had them," Ellie suggested.

Rooney paused, trying to recall. "I came home around 4 and headed to the kitchen with my keys. I remember opening the fridge...

Wait, I might have left them in the fridge door. I'll check."

A moment later, Rooney's voice echoed from the kitchen, a mix of relief and disbelief.

"Found them! In the refrigerator. I can't believe it. Thanks, Ellie. I never would've looked there without your help!"

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About: The modality effect refers to the enhanced memory performance for information presented in both auditory and visual modalities compared to information presented in only one modality. It is important to note, however, that the modality effect enhances memory performance primarily for auditory information compared to visual information. The modality effect is a phenomenon that is closely related to dualcoding theory (Paivio, 1971), but it also arises from cognitive load theory and the split-attention effect, which together explain how mixed modality presentations enhance learning (e.g., Baddeley and Hitch, 1974; Penney, 1989). Even though verbal and non-verbal systems operate independently in memory, they can interact to facilitate recall. This effect is thought to arise from the increased encoding opportunities and reduced cognitive load when information is processed through multiple sensory channels.

Business Example: A relatable example of the modality effect is seen in virtual meetings where information is both spoken by presenters and displayed visually on slides or shared documents. For instance, during a corporate presentation, employees are more likely to retain key points when the presenter narrates the content while participants view the same information on screen. This combination of auditory and visual modalities enhances memory by engaging multiple cognitive pathways, making the information easier to recall later.

Reproducibility: Recent findings in Virtual Reality (VR) environments challenge the effect’s generalizability. While it is commonly hypothesized that audio-visual presentations reduce cognitive load and improve outcomes like recall and comprehension, some studies have observed a reverse modality effect in VR settings.

For example, visual-only presentations in VR can result in better recall and comprehension than audio-visual combinations, potentially due to repeated reading or self-regulatory strategies.

These results suggest that the robustness of the modality effect depends on context, cognitive load, and individual strategies (e.g., Albus and Seufert, 2023).

Trivia Example: A common example of the modality effect occurs in online learning platforms. For instance, students using educational videos that pair narrated explanations with visual aids, such as diagrams or animations, tend to retain information more effectively than when only one mode is used. For example, a biology lesson explaining the process of photosynthesis with both spoken narration and labeled visuals engages both auditory and visual memory systems. This multimodal approach helps students understand and remember complex concepts, demonstrating how the modality effect enhances learning in non- business, educational contexts.

Selected References

Albus, P., & Seufert, T. (2023). The modality effect reverses in a virtual reality learning environment and influences cognitive load. Instructional Science, 51(4), 545–570.

Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47–89).

Academic Press.

Paivio, A. (1971). Imagery and verbal processes. Holt, Rinehart & Winston.

Penney, C. G. (1989). Modality effects and the structure of shortterm verbal memory. Memory & Cognition, 17(4), 398– 422.

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NEXT-IN-LINE EFFECT Next-in-line effect occurs when people are less likely to remember what the person in front of them in line says because they are focusing on their own performance.

"Well done!" Rooney congratulated Ellie, patting her shoulder. "Your performance was fantastic!"

Rooney had come to support Ellie in an art presentation contest. She had chosen to draw a live portrait, capturing a girl from the audience using her computer. In just 30 minutes, she created a delicate, pasteltoned portrait, impressing everyone by printing and gifting it to her model. Rooney, having helped Ellie prepare for months, was particularly proud, especially since he had managed the printer and equipment setup on stage.

"Thanks! I couldn't have done it without your help," Ellie responded humbly. "Don't sell yourself short! You were amazing. I'm betting on you for the first prize," Rooney beamed.

"We'll see," Ellie replied, unsure.

"Trust me, the only other notable act was the guy before you, the one who used volcanic sand.

It was pretty cool!"

"I missed that! I was so nervous, I don't remember anything before going on," Ellie admitted.

"That's normal when you're focused on your own performance. Anyway, let's head to the café while we wait for the results. Tea's on me.

I'm confident you've nailed it!" said Rooney.

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About: Next-in-line effect: The next-in-line effect refers to diminished recall of information presented before a turn. The concept was first identified and studied by Malcolm Brenner in 1973, who observed that individuals often have poorer memory for what was said by others immediately before their own turn to speak (Brenner, 1973).

This effect is believed to be due to the cognitive load and anxiety associated with anticipating and preparing for one's own performance, which can distract attention and impair encoding of surrounding information. The next-in-line effect has been explored in various contexts, including social psychology and memory research, contributing to our understanding of the factors that influence attention and recall in group settings (e.g., Bond and Titus, 1983).

Business Example: The next-in-line effect can impact the effectiveness of meetings and presentations. For example, during a team meeting where members take turns providing updates, individuals may have trouble remembering details from the update immediately before their own turn. To mitigate this effect, meeting facilitators can encourage active listening by providing brief pauses between speakers or summarizing key points before moving on to the next speaker.

Reproducibility: The next-in-line effect is well-documented: research has consistently shown that individuals have poorer recall for information presented immediately before or after their own turn in a sequence. The effect has been observed in various settings, however, factors such as the level of anxiety, the complexity of the task, and individual differences in attentional control can influence the strength of the next-in-line effect (e.g., Schacter et al., 2011).

Trivia Example: The next-in-line effect can be seen in academic conferences or classroom settings where students or researchers take turns presenting their work. Participants may find it difficult to recall details from the presentation immediately preceding their own, as their attention is focused on preparing for their upcoming presentation.

This phenomenon demonstrates how the anticipation of one's own performance can interfere with the processing of information presented by others in a sequential context.

Selected References

Brenner, M. (1973). The next-in-line effect. Journal of Verbal Learning and Verbal Behavior, 12(3), 320-323.

Bond, C. F., & Titus, L. J. (1983). Social facilitation: A meta-analysis of 241 studies. Psychological Bulletin, 94(2), 265-292.

Schacter D. L., Gilbert D.T., and D.M. Wegner (2011) Psychology (2nd Edition), New York: Worth.

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PART-LIST CUEING EFFECT Part-list cueing effect happens when providing some items from a list as cues impairs the recall of the other items.

"Listen..." said Rooney, patting his jacket pocket, "I think I left my phone at home!"

Rooney had dragged Ellie into a home goods store. Ellie hadn't wanted to go there, but she had decided to help Rooney now.

"It's okay," she said, "We came to the store. We can get by without a phone here.

We'll buy everything we need, and then we'll go to your house to get your phone."

"It's not about the phone," Rooney replied, "You see, I have a list on there of what we need to buy, complete with sizes and models."

"Okay, let's see: what do you remember from the list?" "I don't remember anything," Rooney said, annoyed.

"Let me try to help you. There must have been light bulbs on the list. Two of them burned out in your kitchen."

"Exactly!" Rooney cheered up, "The light bulbs were definitely on the list."

"Good, that's one item we've remembered. Now try to recall what else was there."

"I remember there were 15 items, but what they were, besides the light bulbs, I can't recall," Rooney's face fell again.

"Alright, I understand. We won't go back to your place for the phone now, but let me call your mom and ask her to dictate your list.

At least I didn't forget my phone!"

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analysis and suboptimal budgetary decisions. To address this, teams can analyze the full range of financial data before highlighting specific categories, ensuring a more holistic approach to budget planning and reducing the constraints imposed by part-list cueing.

About: The part-list cueing effect is observed in memory recall tasks, where presenting a subset of previously learned items as cues impairs the recall of the remaining items. Early research explored the impact of retrieval cues on memory performance, challenging the traditional view that additional cues should facilitate recall. It demonstrated that, under certain conditions, cues can inhibit memory retrieval (e.g., Slamecka, 1968; Tulving and Pearlstone, 1966). This phenomenon has been studied extensively in cognitive psychology, contributing to our understanding of the complex dynamics of memory retrieval processes.

Reproducibility: The part-list cueing effect has been observed in various experimental paradigms, including free recall, cued recall, and recognition tasks. It has been found, however, that factors such as the nature of the material, the format of the cues, and individual differences in memory strategies can influence the strength of the effect. Ongoing research continues to explore the mechanisms underlying the part-list cueing effect and its implications for memory theory and practice. A recent study shows that the part-list cueing effect is reliable when a large portion of a list is given as hints, making it harder to remember the rest of the items. However, when only a few hints are provided, memory isn’t affected, suggesting the effect only works when enough cues are presented to disrupt how we normally recall information (Akpinar et al., 2023).

Trivia Example: A real-life example of the part-list cueing effect can be observed in group brainstorming sessions.

When one participant lists several ideas, it can sometimes hinder other participants' ability to recall and contribute additional, unique ideas.

The initial list of ideas acts as a part-list cue, which paradoxically narrows the focus of the group's memory retrieval, limiting the generation of new ideas. This phenomenon illustrates the impact of part-list cues on collaborative memory and creativity.

Selected References

Akpinar, D., Bamford, V., Martinez Guzman, S., Nassuna, T., Stevens, M., & Kelley, M. R. (2023). When hints hurt memory: The influence of the number of part-set cues on free recall. Psi Chi Journal of Psychological Research, 28(1), 46–51.

Rundus, D. (1973). Negative effects of using list items as recall cues. Journal of Experimental Psychology, 97(2), 142–147.

Slamecka, N. J. (1968). An examination of trace storage in free recall. Journal of Experimental Psychology, 76(4), 504– 513.

Tulving, E., & Pearlstone, Z. (1966). Availability versus accessibility of information in memory for words. Journal of Verbal Learning and Verbal Behavior, 5(4), 381–391.

Business Example: The part-list cueing effect can manifest in financial reporting and forecasting. For example, if a company’s finance team begins a meeting by presenting a summary of a few key expense categories, team members may focus predominantly on these categories during discussions, overlooking other significant financial factors. This can lead to incomplete

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PRIMACY, RECENCY & SERIAL POSITION EFFECT Primacy effect is the better recall of items at the beginning of a list. Recency effect is the better recall of items at the end of a list. Together, they make up the serial position effect, which is the tendency of a person to recall the first and last items in a series best, and the middle items worst.

"Why are you so worried? Is it about the exhibition?" Rooney asked Ellie, who had just emerged from the gallery, looking anxious. He had been waiting outside for an hour, having risen early to help her with her painting. Only artists were allowed inside, and the exhibition wouldn't open for a few more hours.

"The painting's great, Ellie. Everyone will love it!"

Rooney reassured her.

"It's not the painting I'm worried about," Ellie replied. "I'm concerned it won't get noticed. It's hung right at the entrance. I feel like my effort was wasted."

Rooney chuckled. "You're seeing it all wrong. It's actually a prime spot! People tend to remember the first and last things they see.

Your painting being first is an advantage – it's more likely to be remembered. So cheer up! When do the doors open? I'm getting restless out here."

Ellie's mood brightened. "Do you really think so?"

"Absolutely," Rooney affirmed confidently.

"Your work's going to be the highlight of the day!"

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beginning and end of the pitch, ensuring these details are more memorable for potential clients.

Similarly, in corporate meetings, agenda items of critical importance are frequently positioned at the start and conclusion to capitalize on the primacy and recency effects. By structuring content around these memory principles, businesses can enhance audience retention and drive better decision-making outcomes, illustrating the practical value of understanding cognitive biases like the serial position effect.

About: The primacy, recency, and serial position effects describe how people tend to better remember items at the beginning (primacy effect) and end (recency effect) of a list compared to those in the middle. First identified by Hermann Ebbinghaus (1885) during his pioneering work on memory, these effects have provided key insights into how memory operates (Ebbinghaus, 1885). The primacy effect occurs because earlier items receive more attention and rehearsal, leading to stronger encoding in long-term memory (Glanzer & Cunitz, 1966). Conversely, the recency effect is attributed to the retention of later items in shortterm memory. The serial position effect overall reflects the interplay between these mechanisms, and its study has significantly advanced our understanding of memory processes, including encoding, retrieval, and forgetting.

Reproducibility: The serial position effect has been consistently replicated across various contexts, populations, and experimental paradigms, such as free recall tasks, serial learning, and recognition memory (Ebbinghaus, 1885; Murdock, 1962). Factors like list length, material type, and the interval between presentation and recall influence the strength of these effects. For instance, longer lists often amplify the primacy effect due to increased rehearsal opportunities, while shorter recall intervals tend to enhance the recency effect (Glanzer and Cunitz, 1966). Recent research extends this understanding to artificial intelligence; Guo and Vosoughi (2024) demonstrate that large language models also exhibit serial position effects, reflecting primacy and recency biases similar to those observed in human memory (Guo and Vosoughi, 2024).

Trivia Example: The serial position effect is frequently observed in television advertising, where viewers tend to recall the first and last commercials aired during a break more than those shown in the middle.

This phenomenon reflects the primacy and recency effects, with earlier ads benefiting from rehearsal opportunities and later ads from the recency effect of short-term retention (Murdock, 1962). Advertisers strategically exploit this effect by placing high-priority commercials at the beginning or end of ad blocks to maximize recall and impact.

Selected References

Ebbinghaus, H. (1885). Über das Gedächtnis: Untersuchungen zur experimentellen Psychologie [On memory: Investigations in experimental psychology]. Duncker & Humblot.

Glanzer, M., & Cunitz, A. R. (1966). Two storage mechanisms in free recall. Journal of Verbal Learning and Verbal Behavior, 5(4), 351–360.

Guo, X., & Vosoughi, S. (2024). Serial position effects of large language models.arXiv. https://arxiv.org/abs/2406.15981 Murdock, B. B. (1962). The serial position effect of free recall.

Journal of Experimental Psychology, 64(5), 482–488.

Business Example: The serial position effect is strategically utilized to improve communication and engagement. For instance, sales presentations often highlight key product features or selling points at the 65

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POSITIVITY EFFECT (SOCIO-EMOTIONAL SELECTIVITY) Positivity effect refers to the tendency of people, particularly older adults, to remember more positive than negative information "What's going on? Have you lost it?" Rooney exclaimed as he entered the greenhouse, Ellie's usual painting spot. The floor was strewn with torn sketches, and at the center, a paint-smeared easel stood over a shattered canvas.

"I'm just so frustrated," Ellie confessed, her voice tinged with sadness. "I feel like I'm not progressing as an artist. Everything seems to be getting worse."

"Don't talk like that!" Rooney said, picking up the broken canvas. "You're incredibly talented.

Where's your usual optimism? Your selfbelief?" "It feels like everything I do turns out wrong," Ellie lamented.

"We all have those moments of doubt, but we can't let pessimism win," Rooney encouraged.

Ellie's father then appeared at the doorway.

"What's this about nothing working out?"

"Hi, Dad," Ellie sighed. "I'm just stuck. No new ideas, and everything feels off."

"I think you're being too hard on yourself," her father reassured her. "Last year, you had only two exhibitions, but this year, you've had six. You've won three awards and even got featured in the local newspaper. I'm so proud of you!"

Ellie embraced her father. "You're right, Dad. And you too, Rooney. I need to be more positive."

"That's the spirit," Rooney smiled. "Let's clean up this mess."

"Thanks, both of you," Ellie said, her spirits lifting as they began to tidy the greenhouse.

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Airbnb focused on family reunions and heartwarming travel moments, resonating strongly with customers (particularly, those with older demographics). Similarly, healthcare and wellness brands frequently highlight comfort, longevity, and emotional satisfaction to appeal to people’s motivational goals. By aligning with the positivity effect, businesses can create targeted messaging that enhances emotional engagement and encourages brand loyalty.

About: The positivity effect refers to the tendency of people (particularly, older adults) to prioritize and remember positive information over negative information, a phenomenon central to socio-emotional selectivity theory. First articulated by Laura L. Carstensen in the 1990s, the theory posits that as individuals age, they perceive their time horizons as more limited, shifting their focus toward emotionally meaningful goals and experiences (Carstensen, 1992). This motivational shift enhances attention to positive stimuli and selective recall of positive memories, aiding emotional well-being.

Research has shown that the positivity effect is associated with improved quality of life and contributes to emotional resilience in older adults, shedding light on how aging influences cognition and emotion.

Reproducibility: The positivity effect varies across cultures, with evidence suggesting it is more pronounced in some cultures, such as the United States (Carstensen and Mikels, 2005; Mather and Carstensen, 2005), while in others, like East Asian cultures, the effect may not be as prevalent or may manifest differently (e.g., Zhou et al., 2024).

The nature of the positivity effect is influenced by goal- directed cognitive processing rather than solely by emotional regulation, highlighting the complexity of this phenomenon across populations.

Trivia Example: One example of the positivity effect is evident in how older adults reminisce about their lives, often focusing on joyous milestones and downplaying hardships. For instance, in a study

by Kennedy et al. (2004), older participants recalled vacation experiences by highlighting moments of beauty and relaxation while minimizing logistical challenges or disappointments. This phenomenon, similar to viewing life through “rose-tinted glasses,” demonstrates how the positivity effect shapes autobiographical memory (e.g., Kennedy et al., 2004). Such selective recall allows older adults to maintain a sense of emotional satisfaction, reinforcing their well-being even when reflecting on potentially stressful or complex life events.

Selected References

Carstensen, L. L. (1992). Social and emotional patterns in adulthood: Support fo socioemotional selectivity theory.

Psychology and Aging, 7(3), 331–338.

Carstensen, L. L., & Mikels, J. A. (2005). At the intersection of emotion and cognition: Aging and the positivity effect.

Current Directions in Psychological Science, 14(3), 117–121.

Charles, S. T., Mather, M., & Carstensen, L. L. (2003). Aging and emotional memory: The forgettable nature of negative images for older adults. Journal of Experimental Psychology: General, 132(2), 310–324.

Kennedy, Q., Mather, M., & Carstensen, L. L. (2004). The role of motivation in the age-related positivity effect in autobiographical memory. Psychological Science, 15(3), 208– 214.

Mather, M., & Carstensen, L. L. (2005). Aging and motivated cognition: The positivity effect in attention and memory.

Trends in Cognitive Sciences, 9(10), 496–502.

Zhou, J., West, T. N., Lee, S. H., Choi, I., Hitokoto, H., Otake, K., ... & Salvador, C. E. (2024). Do People From Different Cultures Vary in How Much Positive Emotions Resonate in Day-to-Day Social Interactions? Examining the Role of Relational Mobility.

Journal of Cross-Cultural Psychology, 55(4), 347-367.

Business Example: The positivity effect plays a significant role in marketing strategies. For example, companies often design advertisements that emphasize positive emotions, meaningful experiences, and personal connections. A recent campaign by 67

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PEAK-END RULE Peak-end rule is a psychological heuristic in which people judge an experience largely based on how they felt at its peak (i.e., its most intense point) and at its end.

Rooney wore a satisfied grin, but Ellie's expression couldn't have been more different.

"Nice zoo," Rooney commented, "I haven't been to one in ages. It was fantastic, wasn't it?"

Ellie responded with a sarcastic tone, "Fantastic?

I don't see what's so fantastic about it."

"What do you mean, not fantastic? Seriously?

You didn't enjoy it?" Rooney was taken aback.

"What's there to enjoy?" Ellie's mood seemed to worsen.

"But how? I got to hold a koala for the first time in my life! Remember, the koalas were right in the center of the park? And the orcas at the end? That show was amazing! I've never seen anything like it! It was so cool!"

Ellie replied in a calmer tone, "I just don't see any reason to be happy or surprised. Think about it: there were crowds of people everywhere, long lines, litter all around, and it was so noisy... You were even complaining about it yourself! But more importantly, animals should be in their natural habitats, not in zoos! Training them and putting them on display for profit is irresponsible, in my opinion."

"I see, the zoo wasn't a good idea. I thought you'd enjoy it. Alright, how about some lemonade? There's a great café nearby, just around the corner."

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customers tend to recall these key moments when evaluating their overall stay (Becker and Jaakkola, 2020). Companies in industries ranging from hospitality to retail use this insight to optimize customer satisfaction.

About: The peak-end rule explains how individuals evaluate experiences based on their most intense moment (the peak) and their conclusion (the end), rather than the total or average of every moment. The peak-end rule was introduced by Daniel Kahneman and Barbara Fredrickson, revealing that people’s recollections of events are disproportionately shaped by specific, impactful moments. This cognitive bias highlights the discrepancy between actual experiences and how they are remembered. Extensively studied in psychology and behavioral economics, the peakend rule offers valuable insights into memory, decision- making, and the evaluation of past experiences (Kahneman, 2000; Fredriskson and Kahneman, 1993).

Reproducibility: The peak-end rule has been consistently replicated across various experimental settings.

Research shows its influence in domains such as pain management, where patients often judge medical procedures based on their most painful moments and the way they conclude (Fredrickson and Kahneman, 1993). Similarly, studies in consumer behavior and emotional events confirm the robust nature of this phenomenon. However, the strength of the effect varies depending on factors like the type of experience, individual differences in memory processing, and the duration of the event.

Continued research aims to refine our understanding of the mechanisms and applications of the peak-end rule (Redelmeier and Kahneman, 1996; Shifei et al., 2024; Horowitz et al., 2024).

Trivia Example: A vivid example of the peak-end rule can be observed in vacation memories. A holiday with standout moments and a pleasant conclusion is often remembered more fondly than one that is uniformly good but lacks highlights. For instance, a family visiting Disneyland may primarily recall the thrill of a favorite roller coaster ride (the peak) and the fireworks display on the last evening (the end), even if they endured long queues or minor inconveniences during the trip. These emotionally charged moments heavily influence their overall evaluation of the experience (Do et al., 2008).

Selected References

Becker, L., & Jaakkola, E. (2020). Customer experience: Fundamental premises and implications for research.

Journal of the Academy of Marketing Science, 48, 630-648.

Do, A. M., Rupert, A. V., & Wolford, G. (2008). Evaluations of pleasurable experiences: The peak-end rule. Psychonomic Bulletin & Review, 15(1), 96-98.

Fredrickson, B. L., & Kahneman, D. (1993). Duration neglect in retrospective evaluations of affective episodes. Journal of Personality and Social Psychology, 65(1), 45-55.

Horwitz, A. G., McCarthy, K., & Sen, S. (2024). A review of the peakend rule in mental health contexts. Current Opinion in Psychology, 101845.

Kahneman, D. (2000). Evaluation by moments: Past and future. In D. Kahneman & A. Tversky (Eds.), Choices, values, and frames (pp. 693-708). Cambridge University Press.

Li, S., Sun, Y., & Liu, Z. (2024). Experimental verification and further reflection on the peak-end rule. American Journal of Applied Psychology, 13(4).

Redelmeier, D. A., & Kahneman, D. (1996). Patients’ memories of painful medical treatments: Real-time and retrospective evaluations of two minimally invasive procedures. Pain, 66(1), 3-8.

Business Example: The peak-end rule has significant applications in customer experience management. Businesses leverage this principle by focusing on creating memorable highlights and ensuring a positive conclusion. For example, a luxury hotel might offer a personalized welcome (the peak) and a thoughtful parting gift (the end) to ensure guests leave with a favorable impression. These strategic interventions enhance the likelihood of repeat business and positive reviews, as 69

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PICTURE SUPERIORITY EFFECT Picture superiority effect describes the phenomenon in which pictures and images are more likely to be remembered than words. shopping cart, while Ellie was pushing the baby stroller with Oliver inside.

"I think we've got everything," Rooney remarked, glancing at the cart filled with groceries.

"Are you sure? Nothing left behind? You should double-check before we exit the store," Ellie advised, scrutinizing the cart.

"Honestly, it's much smoother if you have a list in situations like this."

"Well, I didn't make a list..." Rooney responded with a hint of irritation. "I believe we've covered everything we need, but there's this nagging feeling that I forgot something. What could it be?"

"You know, in situations like this, it's often better to visualize it rather than trying to recall items from a list. Try to imagine your fridge. You might realize what we missed. I read somewhere that most people remember images and visuals better than lists. Maybe that'll help."

"Hey, that's a great idea. Let me think," Rooney said, taking a moment to reflect. "Got it! I forgot the milk. We need more milk. You're absolutely right; it's incredible! I spent the last 5 minutes racking my brain, and it was so simple.Thank you. I would've definitely forgotten the milk without you."

"Okay, you head to the checkout line," Ellie directed briskly, "Oliver and I will quickly grab the milk."

Rooney and Ellie had been strolling through the supermarket for an hour already. Rooney's mother was on another business trip, and Ellie had offered to assist Rooney with the shopping. Rooney was managing the 70

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associations with the brand’s identity and values.

The use of bright, engaging visuals on menus and advertisements also simplifies information for customers, making it easier to recall and process.

By leveraging strong visual elements, businesses ensure their brand stands out in competitive markets.

About: The picture superiority effect refers to the enhanced memory recall for images compared to words. This phenomenon gained scientific traction through Allan Paivio’s dual-coding theory in the 1970s. According to this theory, pictures are processed through both verbal and non-verbal systems, providing dual routes for encoding into memory, which enhances retrieval (Paivio, 1971). Pictures engage sensory and emotional processing more effectively than words, making them easier to remember.

Research by Shepard (1967) also demonstrated this effect through experiments where participants showed higher recall for pictures than for word lists, establishing the picture superiority effect as a fundamental concept in cognitive psychology (Shepard, 1967).

Reproducibility: The picture superiority effect is a robust phenomenon in memory research. It has been consistently replicated across contexts, such as in studies comparing recognition and recall rates for images versus words. For instance, Paivio’s experiments demonstrated that pictures yield significantly better memory performance across short and long intervals. However, the strength of the effect varies depending on factors such as the type of images, individual differences in visual processing, and the presentation context (e.g., Marschark and Cornoldi, 1991). Current research aims to refine our understanding of the mechanisms underlying this effect and its implications for fields such as education, user experience design, and marketing (e.g., Ensor et al., 2019).

Trivia Example: A practical example of the picture superiority effect is the use of flashcards in education. For instance, language learners often pair vocabulary with images, such as an illustration of an apple for the word “apple.” Studies have shown that associating words with visuals improves retention, as learners process the material using both visual and verbal pathways (Carney and Levin, 2002). This approach is particularly effective in early education and for individuals learning a second language.

Selected References

Carney, R. N., & Levin, J. R. (2002). Pictorial illustrations still improve students’ learning from text. Educational Psychology Review, 14(1), 5-26.

Childers, T. L., & Houston, M. J. (1984). Conditions for a picturesuperiority effect on consumer memory. Journal of Consumer Research, 11(2), 643-654.

Ensor, T. M., Bancroft, T. D., & Hockley, W. E. (2019). Listening to the picture- superiority effect: Evidence for the conceptual-distinctiveness account of picture superiority in recognition. Experimental Psychology, 66(2), 134–153.

Henderson, P. W., & Cote, J. A. (1998). Guidelines for selecting or modifying logos. Journal of Marketing, 62(2), 14-30.

Marschark, M., & Cornoldi, C. (1991). Imagery and verbal memory.

In C. Cornoldi & M. A. McDaniel (Eds.), Imagery and cognition (pp. 133-182). Springer-Verlag.

Paivio, A. (1971). Imagery and verbal processes. Holt, Rinehart & Winston. Shepard, R. N. (1967). Recognition memory for words, sentences, and pictures. Journal of Verbal Learning and Verbal Behavior, 6(1), 156-163.

Business Example: The picture superiority effect is extensively used in marketing and branding strategies (Childers and Houston, 1984). Visual logos such as Apple’s iconic apple or Nike’s swoosh are more memorable than company names alone.

Research demonstrates that visuals not only enhance recall but also create stronger emotional connections with consumers (Henderson and Cote, 1998). For instance, McDonald’s golden arches are instantly recognizable and evoke 71

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CHOICE-SUPPORTIVE BIAS Choice-supportive bias is the tendency to remember one's choices as better than they actually were, to justify past choices "I see your new backpack has arrived. Have you gotten used to it?" Ellie glanced at Rooney's brand-new blue backpack.

"What are you talking about?" asked Rooney.

"What do you mean? You spent two weeks choosing it."

"Not at all, I liked this backpack right away. It has many compartments, even a place for a tennis racket. It's small but spacious.

Everything fits in it. And most importantly, it's not black."

"That's strange," said Ellie. "You said yourself that it wasn't the perfect option. That the color wasn't quite right – you were looking for yellow, and you even said that if you couldn't find a yellow one, it'd better be black; that small backpacks were 'a waste of money,' and that it's silly to have one backpack 'for training and for life.' You even came up with a whole theory about it!"

"When was that? On the contrary, I was specifically looking for this backpack."

Rooney looked at Ellie, puzzled. "You must have mixed something up. I didn't want to buy a black one. Too bulky, and the color is just dull."

"Yes, yes, of course, 'I mixed something up,'" Ellie smiled skeptically. "But in any case, the backpack is cool. I like it."

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effect by reinforcing customers’ associations with their chosen brand.

About: Choice-supportive bias is a cognitive phenomenon where individuals misremember their decisions as better than they were, assigning more favorable attributes to chosen options and minimizing the positives of rejected ones. In memory and self-perception research, Mather, Shafir, and Johnson (2000) demonstrated how retrospective evaluations are shaped by this bias, influencing memory accuracy and emotional response to decisions.

For instance, individuals often rationalize choices to align with their self-image, thus skewing memories of past decisions (Roese and Olson, 1997).

positive

Reproducibility: Choice-supportive bias is robustly documented across contexts, including consumer behavior, relationship decisions, and political judgments.

Gilovich and Medvec (1995) highlighted how people reframe past decisions to minimize regret, which aligns with findings by Mather et al.

(2000), who noted biases in memory for chosen and rejected options. Experimental paradigms, such as choice-listing tasks and retrospective evaluations, consistently confirm this bias. Its strength varies with decision importance, the presence of close alternatives, and individual traits like cognitive style or need for closure (Kruglanski and Webster, 1996). Recent studies using eye-tracking and neuroimaging have begun exploring the neural correlates of choicesupportive bias, deepening our understanding of its mechanisms and real-world implications for decision-making and memory (e.g., Senftleben et al., 2024).

Trivia Example: Choice-supportive bias is common in sports fandom, where fans tend to glorify their favorite team’s achievements while minimizing failures.

For example, a Manchester United supporter might vividly recall championship wins while disregarding key losses or seasons of poor performance. This selective memory extends to how fans perceive rival teams, amplifying negative traits to justify loyalty. Similarly, political partisanship exemplifies this bias: supporters of a political candidate often overlook controversial decisions or scandals while emphasizing their accomplishments, creating a skewed narrative that reinforces allegiance (Haidt, 2012).

Selected References

Gilovich, T., & Medvec, V. H. (1995). The experience of regret: What, when, and why. Psychological Review, 102(2), 379– 395.

Haidt, J. (2012). The righteous mind: Why good people are divided by politics and religion. Pantheon.

Kruglanski, A. W., & Webster, D. M. (1996). Motivated closing of the mind: “Seizing” and “freezing.” Psychological Review, 103(2), 263–283.

Mather, M., Shafir, E., & Johnson, M. K. (2000). Misremembrance of options past: Source monitoring and choice.

Psychological Science, 11(2), 132– 138.

Roese, N. J., & Olson, J. M. (1997). Counterfactual thinking: The intersection of affect and function. Advances in Experimental Social Psychology, 29, 1– 59.

Senftleben, U., Schoemann, M., & Scherbaum, S. (2024). Choice repetition bias in intertemporal choice: An eye-tracking study. Journal of Behavioral Decision Making, 37(3), e2388.

Shiv, B., & Huber, J. (2000). The impact of anticipating satisfaction on consumer choice. Journal of Consumer Research, 27(2), 202–216.

Business Example: Choice-supportive bias may shape consumer loyalty and brand perception. For instance, an Apple customer may rationalize their purchase of an iPhone by emphasizing the device’s sleek design and ecosystem integration while downplaying drawbacks such as high costs. This bias sustains brand loyalty and drives repeat purchases, even when competitors offer superior features or better value (Shiv and Huber, 2000).

Marketing strategies often capitalize on this 73

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CONTRAST EFFECT Contrast effect occurs when the evaluation of a particular item is influenced by comparing it with recently encountered items of higher or lower quality.

"Why did you buy this? And what is it anyway?"

Rooney twirled a tin can filled with some gray substance in his hand. The can was small and flat.

"It's a toy. For stress relief," Ellie replied nonchalantly, "Look, it's a polymer. You can mold it into any object, like clay. For example, here's a ball," she said, rolling the gray mass into a sphere. "And then," she continued, "you just put the ball back in the can, and it melts and spreads along the can's walls, taking its shape. Cool, right?"

Rooney turned on his sarcasm and said: "Yeah, an indispensable household item. Why did you buy it? I don't understand."

"It was on a huge discount!" Ellie said excitedly, showing him the price tag on the can. "See? The price was $20, and I got it for $5. That's a 75 percent discount! I couldn't pass it up!

And if you don't like it, don't touch it!"

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model makes the mid-range TVs seem like a better deal, even if the consumer had no initial intent to spend at that price point. Similarly, subscription services often offer a “premium” option alongside a standard one to make the latter seem more reasonable by comparison. This deliberate framing exploits the contrast effect to drive sales and maximize perceived value (Haws and Bearden, 2006).

About: The contrast effect is a cognitive bias where the evaluation of an object, event, or person is influenced by a comparison with another object, event, or person of differing quality or value.

Early work by Edward Thorndike noted its role in biases in social and educational evaluations, such as the “halo effect” (Thorndike, 1920). Solomon Asch through his research on impression formation, demonstrating that the presence of certain traits can alter how other traits are perceived (Asch, 1946). Modern research continues to highlight the contrast effect’s relevance across fields such as marketing, hiring, and perception, demonstrating its central role in shaping judgments and decisions (e.g., Ledgerwood and Callahan, 2012).

Reproducibility: The contrast effect is supported by extensive research across domains, including perception, social judgment, and consumer decision-making.

Factors such as the magnitude of the contrast, the framing of alternatives, and individual differences in cognitive processing influence the effect’s strength. For example, Ledgerwood and Callahan (2012) showed that contrast effects are more pronounced in ambiguous or uncertain contexts, where comparison anchors provide a stronger reference point. Contrast effects, as demonstrated in Shi and Tang’s (2023) study, unconsciously influence financial analysts’ earnings forecasts, particularly among less experienced analysts.

Trivia Example: In entertainment, the contrast effect can influence audience perception. For instance, when comedic actor Jim Carrey starred in The Truman Show—a serious drama—critics and audiences praised his performance as exceptionally poignant, partly because it contrasted with his established comedic persona.

Conversely, actors known for serious roles are often judged more harshly when attempting comedy, as their performance is evaluated against their typical gravitas. This perceptual shift demonstrates how expectations set by past roles shape audience responses to new performances.

Selected References

Asch, S. E. (1946). Forming impressions of personality. Journal of Abnormal and Social Psychology, 41(3), 258–290.

Haws, K. L., & Bearden, W. O. (2006). Dynamic pricing and consumer fairness perceptions. Journal of Consumer Research, 33(3), 304–311.

Ledgerwood, A., & Callahan, S. P. (2012). The social side of abstraction: Psychological distance enhances conformity to group norms. Psychological Science, 23(8), 907–913.

Shi, H., & Tang, M. (2021). Contrast effects and analyst forecasts.

Retrieved from https://scholarspace.manoa.hawaii.edu/handle/10125/76 953 Thorndike, E. L. (1920). A constant error in psychological ratings.

Journal of Applied Psychology, 4(1), 25–29.

Business Example: The contrast effect is widely used in pricing and sales strategies to influence consumer behavior.

For example, many electronics stores display an extremely high-priced TV model next to midrange options. The presence of the expensive 75

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DECLINISM Declinism is the belief that a society or institution is tending towards decline, particularly the belief that a society's values and norms are in decline.

"Well, here we go," Rooney sighed and looked at Ellie. "They're closing our gym. Now it's going to be a grocery store. This is the second gym in our neighborhood in 4 months. I'm so tired of this! Before, you could just go outside to exercise. And now you have to go to the city center..."

"Don't exaggerate," Ellie smiled. "A couple of 'pump-iron' places closed, so what?"

"What do you mean, 'so what'? You can't even be dragged out of the house to the gym, even when it was just a stone's throw away, and now it's going to be even worse!"

"It's not going to be worse," Ellie calmly replied.

"We just need to change our plan a bit.

Here's what we'll do: on weekends, we'll go to the city center, work out at the gym, and on the other days, we'll go running in the park."

"Deal!" said Rooney. "But I warn you: excuses like 'I need to sleep' or 'I'm tired' won't fly.

If we’ve agreed to jog, we will jog!"

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its prime despite evidence of ongoing success.

For example, once-dominant brands like Nokia faced narratives of decline as market competition intensified, even when they introduced innovations or remained profitable. Such perceptions can undermine employee morale, erode investor confidence, and deter consumer loyalty. Addressing declinism requires proactive communication, emphasizing a company’s forward-thinking strategies and long-term vision to counteract unwarranted pessimism and maintain stakeholder trust.

About: Declinism refers to the belief that a society, institution, or entity is in a state of decline, often paired with the nostalgic perception that the past was better. It reflects a cognitive bias that distorts how individuals perceive societal trajectories and their own roles within them.

Historical narratives, from the Roman Empire’s fall to early 20th-century laments over industrialization, reveal that this bias has long shaped human thought. In modern psychology, declinism is linked to nostalgia and a pessimistic outlook, as individuals often romanticize past eras and exaggerate current challenges. This bias has been studied in politics, economics, and cultural discourse, where it influences how people respond to societal changes and uncertainties (e.g., Weber and Federico, 2013).

Reproducibility: Although declinism is a sociocultural phenomenon, its cognitive roots align with some psychological research, such as loss aversion and nostalgia. For example, Weber and Federico (2013) demonstrated how perceptions of societal decline influence attitudes and behaviors. The strength of declinism varies by cultural context, historical circumstances, and personal traits, such as openness to experience or futureoriented thinking. Future research could illuminate how declinism shapes group dynamics and decision-making processes in both public and private sectors (Tian et al., 2024)

Trivia Example: Declinism is vividly illustrated by the “Make America Great Again” slogan, a central theme of Donald Trump’s 2016 and 2024 presidential campaigns. The phrase invokes a nostalgic belief in an idealized past, appealing to those who perceive the United States as having declined in global influence or domestic prosperity. By invoking a nostalgic vision of a “golden age,” the slogan resonated with voters’ concerns about economic shifts, cultural changes, and political developments. This example illustrates how declinism can influence public sentiment and shape political discourse (e.g., Ralston, 2022).

Selected References

Weber, C. R., & Federico, C. M. (2013). Moral foundations and heterogeneity in ideological preferences. Political Psychology, 34(1), 107-126.

Tian, F., Fu, S., Yang, Y., Wang, Z., & Liu, D. (2024). Understanding nostalgia in historical and cultural districts: What can we learn from documentaries?. Tourism Management Perspectives, 54, 101302.

Ralston, R. (2022). Make us great again: The causes of declinism in major powers. Security Studies, 31(4), 667-702.

Business Example: In the corporate world, declinism often manifests when stakeholders perceive a company as past

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IMPLICIT ASSOCIATION Implicit association refers to the mental association between concepts without conscious awareness.

"How do you like our tennis club calendar? I worked on it for quite a while. Do you like it?" Rooney was pleased with his work.

"Since the calendar hasn't gone to print yet, I'm open to criticism!"

"Well, let me put it this way," Ellie replied. "The photos turned out really great. Well done.

And most of the shots are action shots. It's awesome! But I do have one comment."

"Curious, what's that?"

"Why are all the models either young girls or young guys? There are plenty of people in your club who are over 50. What's with the ageism? You have many players of a respectable age, and they play tennis exceptionally well. Why didn't any of them make it into the calendar?"

"You're right," Rooney pondered. "I didn't even think about that, but I didn't do it on purpose..."

"I know you didn't do it on purpose," Ellie patted Rooney on the shoulder. "I'm not saying you intentionally excluded these people.

But you need to fix this!"

"You're right, thanks! I will."

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minimalist designs and sustainability reinforces its implicit association with progress and ecofriendly luxury. Colors also play a significant role; brands like Coca-Cola leverage red for excitement and energy, while banks like Chase use blue to evoke trust and reliability (Henderson and Cote, 1998).

About: Implicit associations are automatic, unconscious connections that individuals form between concepts, often shaping attitudes, beliefs, and behaviors without conscious awareness. The study of implicit associations gained prominence with the development of the Implicit Association Test (IAT) in the 1990s. This tool measures the strength of associations, such as between race and positive or negative attributes, providing insights into unconscious biases. Research has shown how these biases influence social interactions, decision- making, and intergroup relations, revealing the significant role unconscious processes play in human cognition (Greenwald et al., 1998). The concept has broadened our understanding of prejudice, stereotype formation, and how deeply ingrained associations can impact behaviors and perceptions, even in individuals who consciously reject such biases (Payne et al., 2008). Studies have also explored how implicit biases can be mitigated through interventions like counterstereotypical training (Devine et al., 2012).

Reproducibility: The concept of implicit associations have been extensively replicated across a variety of domains, including race, gender, age, and consumer behavior (Greenwald et al., 1998; Nosek et al., 2007). While critics debate the IAT’s ability to predict behavior, studies have demonstrated its robustness in measuring unconscious biases that influence judgments and decisions (Payne et al., 2008). Interventions to reduce implicit biases have shown mixed results, with long-term efficacy still under investigation (e.g., Glaser, 2024). Nonetheless, the research on implicit associations continues to expand, exploring factors such as cultural differences and neurological underpinnings (Stanley et al., 2008).

Selected References

Trivia Example: Implicit associations are evident in consumer behavior. For example, individuals may unconsciously associate Starbucks with quality coffee and social status due to the brand’s marketing and ubiquity in urban culture. Such associations often guide preferences and decisions even when comparable alternatives exist. Similarly, research shows that implicit biases affect how individuals perceive job applicants based on stereotypical attributes in their names or accents, with applicants from dominant social groups receiving more favorable evaluations (Bertrand and Mullainathan, 2004).

Bertrand, M., & Mullainathan, S. (2004). Are Emily and Greg more employable than Lakisha and Jamal? A field experiment on labor market discrimination. American Economic Review, 94(4), 991–1013.

Devine, P. G., Forscher, P. S., Austin, A. J., & Cox, W. T. L. (2012).

Long-term reduction in implicit race bias: A prejudice habit-breaking intervention. Journal of Experimental Social Psychology, 48(6), 1267–1278.

Glaser, J. (2024). Disrupting the Effects of Implicit Bias: The Case of Discretion & Policing. Daedalus, 153(1), 151-173.

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998).

Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74(6), 1464–1480.

Henderson, P. W., & Cote, J. A. (1998). Guidelines for selecting or modifying logos. Journal of Marketing, 62(2), 14–30.

Nosek, B. A., Banaji, M. R., & Greenwald, A. G. (2007). The implicit association test at age 7: A methodological and conceptual review. Social Psychology and the Unconscious: The Automaticity of Higher Mental Processes, 265, 3–22.

Payne, B. K., Cheng, C. M., Govorun, O., & Stewart, B. D. (2008). An inkblot for attitudes: Affect misattribution as implicit measurement. Journal of Personality and Social Psychology, 94(3), 277–293.

Stanley, D. A., Phelps, E. A., & Banaji, M. R. (2008). The neural basis of implicit attitudes. Current Directions in Psychological Science, 17(2), 164–170.

Business Example: Luxury brands such as Chanel or Tesla cultivate associations with exclusivity, innovation, and environmental consciousness through carefully curated imagery, endorsements, and product designs. For instance, Tesla’s focus on sleek, 79

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NEGATIVITY BIAS OR NEGATIVITY EFFECT Negativity bias or Negativity effect is the tendency to give more weight to negative experiences or information than positive, in various psychological processes systems for 2 weeks," Ellie said sadly, looking at Rooney almost absentmindedly.

It even seemed to him that she was talking to herself rather than to him.

"I don't understand. What about your internship? You need a computer for work, right?"

"Not anymore! Now I'll have to go without a computer for two weeks!" Ellie sighed.

"Why? What happened?"

"I failed the practical cybersecurity test."

"What test are you talking about? Weren't you the one who said the cybersecurity training was easy? You were so happy that it was a breeze. You even mentioned passing the exam, I remember," Rooney said in surprise.

"I did complete the training. I passed the theory part. But the company where I'm interning occasionally conducts practical cyber tests.

This time, they sent an email with a link, and I accidentally clicked on it. Now I'm paying the price for my carelessness. It's a disaster," Ellie sighed again.

"Don't make it out to be so dramatic! It's definitely unpleasant, but now you'll know about these tests, and you won't make the same mistake next time. Come on, get ready. Let's go to the park. You need to unwind a bit."

"What's bothering you?" It had been 15 minutes since Rooney walked in on Ellie. During that time, he had been trying to talk to her, but it seemed like she wasn't listening.

"Could you tell me what's got you so upset?"

"They disabled the internet on my work computer and prohibited me from using all 80

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and loyalty.

About: Negativity bias refers to the psychological phenomenon where negative events, emotions, or information disproportionately influence an individual’s thoughts, emotions, and behaviors compared to neutral or positive stimuli. Early research by Paul Rozin and Edward Royzman demonstrated that negative stimuli tend to be more salient and memorable than positive ones due to their evolutionary significance for survival (Rozin & Royzman, 2001). Studies in social, cognitive, and evolutionary psychology have shown how negativity bias influences perception, memory, and decision-making, often causing people to prioritize threats and losses over opportunities and gains (Baumeister et al., 2001).

Reproducibility: Numerous studies have demonstrated the bias’s influence on attention, memory, and judgment across various domains, including emotional recall, decision-making, and interpersonal relationships. For instance, individuals more readily recall angry faces than neutral or happy ones in experiments (Hansen and Hansen, 1988).

The strength of negativity bias is influenced by factors such as the intensity of the stimulus, individual differences (e.g., personality traits like neuroticism), and cultural norms. Recent research has also explored interventions, such as gratitude practices, that can help mitigate its effects (Fredrickson, 2004). Resent research found that while positive intergroup contact reduces prejudice, negative contact has a significantly stronger detrimental effect, particularly when individuals are motivated and able to avoid contact (Paolini et al., 2024).

Trivia Example: Studies consistently show that individuals are more likely to remember and react to negative news than positive stories. For instance, during the COVID-19 pandemic, news coverage frequently focused on rising death tolls and outbreaks, which garnered more attention than stories about recoveries or community resilience (Soroka et al., 2019). Similarly, social media algorithms often amplify negative content because it generates higher engagement, perpetuating the cycle of negativity (Watson et al., 2024).

Selected References

Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good. Review of General Psychology, 5(4), 323–370.

Fredrickson, B. L. (2004). The broaden-and-build theory of positive emotions. Philosophical Transactions of the Royal Society B: Biological Sciences, 359(1449), 1367–1377.

Hansen, C. H., & Hansen, R. D. (1988). Finding the face in the crowd: An anger superiority effect. Journal of Personality and Social Psychology, 54(6), 917–924.

Paolini, S., Gibbs, M., Sales, B., Anderson, D., & McIntyre, K. (2024). Negativity bias in intergroup contact: Metaanalytical evidence that bad is stronger than good, especially when people have the opportunity and motivation to opt out of contact. Psychological Bulletin.

Park, C., & Lee, T. M. (2009). Information direction, website reputation, and eWOM effect: A moderating role of product type. Journal of Business Research, 62(1), 61–67.

Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion. Personality and Social Psychology Review, 5(4), 296–320.

Soroka, S., Fournier, P., & Nir, L. (2019). Cross-national evidence of a negativity bias in psychophysiological reactions to news. Proceedings of the National Academy of Sciences, 116(38), 18888–18892.

Watson, J., van der Linden, S., Watson, M., & Stillwell, D. (2024).

Negative online news articles are shared more to social media. Scientific Reports, 14(1), 21592.

Business Example: Research shows that a single negative review can significantly outweigh multiple positive ones in shaping consumer perceptions (Park and Lee, 2009). For example, a viral negative comment about poor customer service at a restaurant can deter potential patrons, even if the majority of reviews are favorable. To counter this, businesses prioritize addressing customer complaints swiftly and transparently. Companies like Amazon have invested heavily in customer service initiatives to mitigate the impact of negative feedback, recognizing its disproportionate influence on customer trust 81

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PROCESSING DIFFICULTY EFFECT Processing difficulty effect is the notion that information that is harder to process, or disfluent, is remembered less well than information that is easier to process, or fluent.

"Hey, why do you look so tired?" Rooney could see that Ellie was troubled by something.

"Yeah, I'm trying to learn my lines for Sunday's theater performance. It's driving me crazy. I can't seem to memorize them," Ellie sighed.

"How are you trying to memorize the lines?"

"See these cue cards? I've divided my monologue into sections. I read it in small parts and try to memorize the phrases."

"I think, in this case, it's better to spend more time trying to memorize the entire text. If you want, I can help you. Let's do this: I'll read the text to you, and you try to remember it. It might take more time than trying to memorize it in small bits, but I'm sure it will yield better results. You need to give your brain time to process and absorb the information. Otherwise, you'll only remember some phrases from the monologue but not the whole thing."

"Interesting!" Ellie perked up, handing Rooney the script. "Let's give it a try!"

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tutorials. By requiring greater cognitive effort, these training programs foster deeper learning and better application of skills. Similarly, marketing campaigns often use slightly ambiguous or thought-provoking advertisements to capture attention and improve recall (e.g., Alter et al., 2007).

About: The processing difficulty effect, The processing difficulty effect, also referred to as the disfluency effect, is a psychological phenomenon where information that is harder to process can lead to better long-term memory retention. Research in cognitive psychology demonstrated that material presented in harder-to-read fonts or with slight perceptual difficulty often enhances recall compared to easily processed material. The underlying mechanism is thought to involve deeper cognitive engagement: the extra effort required to process disfluent material leads to improved encoding and memory consolidation (e.g., Oppenheimer, 2008; Diemand-Yauman et al., 2011).

Reproducibility: The processing difficulty effect has been met with mixed evidence. For example, some studies indicate that while disfluent fonts increase perceived difficulty, they do not consistently improve retention and may even impair comprehension and confidence (e.g., Geller et al., 2020). Generally, the effect is context-dependent and influenced by factors such as the difficulty level, individual cognitive abilities, and the nature of the material. For instance, overly difficult material may hinder learning instead of facilitating it. Recent studies have explored boundary conditions, including whether the benefits of disfluency depend on learners’ motivation and prior knowledge (Sungkhasettee et al., 2011). While the processing difficulty effect offers valuable insights into learning and memory, further research is needed to determine its generalizability.

Trivia Example: The processing difficulty effect is frequently leveraged in education through the use of challenging study materials. For instance, researchers found that students who read educational content in a difficult-to-read font retained more information than those who read the same content in an easy- to-read font (Diemand-Yauman et al., 2011). Beyond academia, popular activities such as solving Sudoku puzzles or cryptic crosswords exploit this effect. The cognitive effort required to solve these puzzles enhances problem-solving skills and memory retention, providing not just entertainment but also cognitive benefits.

Selected References

Alter, A. L., Oppenheimer, D. M., Epley, N., & Eyre, R. N. (2007).

Overcoming intuition: Metacognitive difficulty activates analytic reasoning. Journal of Experimental Psychology: General, 136(4), 569–576.

Diemand-Yauman, C., Oppenheimer, D. M., & Vaughan, E. B. (2011). Fortune favors the bold (and the italicized): Effects of disfluency on educational outcomes. Cognition, 118(1), 111–115.

Geller, J., Davis, S. D., & Peterson, D. J. (2020). Sans Forgetica is not desirable for learning. Memory, 28(8), 957–967.

Oppenheimer, D. M. (2008). The secret life of fluency. Trends in Cognitive Sciences, 12(6), 237–241.

Sungkhasettee, V. W., Friedman, M. C., & Castel, A. D. (2011).

Memory and metamemory for inverted words: Illusions of competency and desirable difficulties. Psychonomic Bulletin & Review, 18(5), 973–978.

Business Example: The processing difficulty effect may be used to design more effective corporate training programs. For example, companies increasingly employ interactive simulations or scenariobased problem-solving exercises that challenge employees to apply new knowledge in realistic contexts. A technology firm might train its software developers using complex debugging simulations rather than straightforward 83

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SOURCE CONFUSION Source confusion is a memory distortion that occurs when the source of a memory is incorrectly attributed to some specific recollected experience. handed him a ten-dollar bill.

"Thank you!" he said. "But you didn't quite understand me. We have plenty of corporate sponsors, but we need volunteers for the marathon."

"What do you mean by 'volunteers'?" Rooney asked.

"Well, in order to maximize the funds we can raise from our sponsors, we have to keep jumping on this trampoline continuously for 48 hours. That's why we're looking for volunteers who can help us out. You could jump for 10 or 15 minutes, and it would greatly assist us. During that time, we can take a short break."

Ellie shrugged and said, "Sure, we can help.

We're not in a hurry to go anywhere."

Then she felt Rooney tug at her arm. "What are you doing?" he said. "Have you forgotten how you hurt your back the last time you jumped on a trampoline? You pulled a muscle and couldn't straighten up for a week!"

"That's not true," Ellie replied, heading towards the trampoline with the acrobat. "I hurt my back, but it wasn't because of the trampoline. It happened earlier that day when I was carrying a heavy easel. The doctor explained it to me. It had nothing to do with the trampoline. So, let's not be lazy, and let's start jumping! It's for the children!"

"Fine, fine," Rooney said, untying his sneakers.

"But I'll go first, and then you can take your turn. That way, the guys can rest a bit longer."

In the park, Rooney and Ellie stopped in front of a large trampoline. Two acrobats were simultaneously bouncing on it, performing intricate pirouettes in the air. Then one of them jumped down to the ground and started talking to Ellie.

"Hey! We're organizing a 48-hour charity marathon for the local children's hospital!"

The tall, handsome blonde acrobat said, winking at Ellie.

Ellie immediately reached into her purse and 84

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business decisions (e.g., Keller, 1993). A notable example occurred in the early 2000s when consumers often confused the McDonald’s “I’m Lovin’ It” jingle with rival fast-food brands, benefiting competitors indirectly.

Misattributions can also occur in advertising when memorable slogans or jingles become disassociated from their original brand, diluting campaign effectiveness. To mitigate source confusion, businesses strive to create unique and consistently reinforced brand elements, such as visually distinct logos or taglines closely tied to the brand.

About: Source confusion, or source misattribution, occurs when individuals misidentify the origin of a memory, leading to inaccuracies in recall.

Elizabeth Loftus’s influential work on eyewitness testimony demonstrated how suggestive questioning could lead individuals to misattribute the source of their memories, significantly shaping the field of legal psychology (Loftus, 1979). Subsequent research has shown that source confusion is a common aspect of memory reconstruction, arising from the brain’s integration of details from various events. It highlights the fallibility of memory and demonstrates how external factors such as suggestion, media, and time delays can distort memory recall (Johnson et al., 1993).

Understanding source confusion is critical for fields like law, education, and marketing, where memory accuracy is important.

Reproducibility: Source confusion has been replicated in psychological research, with studies confirming its prevalence in various domains, including eyewitness testimony, consumer behavior, and personal memory recall. Factors such as the similarity of sources, the delay between exposure and recall, and individual cognitive differences influence its likelihood. For example, Johnson et al. (1993) found that source confusion is more likely when memories are encoded under stress or distraction. While the phenomenon’s mechanisms are well-supported, ongoing research continues to explore its implications for legal processes, education, and marketing, emphasizing the importance of context in mitigating its effects (e.g., Rubínová and Kontogianni, 2023).

Trivia Example: A well-known example of source confusion is the persistent attribution of the phrase “Let them eat cake” to Marie Antoinette, Queen of France.

Historians agree there is no evidence she ever said this, and the phrase likely originated from earlier writings or other figures. Yet, this misattribution has endured, shaping public perception of Marie Antoinette as disconnected from the struggles of the French people. This example illustrates how misinformation and repeated misattributions can alter historical narratives and reinforce stereotypes.

Selected References

Johnson, M. K., Hashtroudi, S., & Lindsay, D. S. (1993). Source monitoring. Psychological Bulletin, 114(1), 3–28.

Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1–22.

Loftus, E. F. (1979). Eyewitness testimony. Harvard University Press.

Rubínová, E., & Kontogianni, F. (2023). Sources and destinations of misattributions in recall of instances of repeated events.

Memory & Cognition, 51(1), 188-202.

Business Example: Source confusion frequently impacts consumer behavior and market research. For instance, customers may misattribute a positive experience with one brand to a competing brand, skewing market research results and influencing 85

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SUFFIX EFFECT Suffix effect refers to the impairment of the recall of the final items in a spoken list when a new, meaningless sound item (the suffix) is added to the end of the list.

"What's troubling you?" Ellie inquired.

Rooney sighed, "Well, you see, my mom went on a business trip yesterday and asked me to check the delivery schedule for a package. I can't remember the last two digits of the tracking number, and I've been struggling with it for half an hour."

"You 'can't remember'?" Ellie was puzzled.

"Couldn't you have just written down the number?"

"Yeah, I thought I'd remember it," Rooney replied, "I'm usually good with numbers. I had the whole number in my head, but then my mom mentioned something about the package being due two days ago at 8:00 PM. That's when the number 20 got stuck in my mind. But I can't recall the last two digits of the tracking number. I'm not sure what to do."

"Why even hesitate? Just call your mom."

Rooney hesitated, "I didn't want to bother her unnecessarily, but you're right. I'll have to give her a call," he said, determined, as he picked up his smartphone.

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suffix effect, businesses can end meetings with a concise summary of key points or provide written follow-ups. Companies that implement structured agendas and clear closing statements can enhance the retention of important information among employees.

About: The suffix effect is a memory phenomenon in which an irrelevant sound (the “suffix”) presented immediately after a list of items impairs the recall of the last few items in the sequence. Identified by Donald Crowder in the late 1960s, the effect occurs due to auditory processing interference rather than semantic interference (Crowder and Morton, 1969).

Crowder’s studies revealed that the suffix effect affects auditory memory by disrupting the recency advantage for the final items in a list.

This research has expanded our understanding of short-term and working memory, particularly how auditory stimuli are encoded and retrieved.

The suffix effect is a valuable concept in cognitive psychology, shedding light on the vulnerability of auditory memory to extraneous input.

Reproducibility: The suffix effect is a well-documented and consistently replicated phenomenon in cognitive psychology. Early studies by Crowder and Morton (1969) demonstrated the impairment of final-item recall due to irrelevant auditory input.

Subsequent research has validated the effect across various experimental paradigms, including immediate and delayed recall tasks.

The magnitude of the suffix effect varies based on factors such as the nature of the suffix (e.g., speech vs. non-speech sounds), list length, and individual auditory processing abilities. While robust, ongoing research investigates its broader implications for auditory memory and practical applications in education, communication, and workplace productivity. (Greene, 1989) (Pisoni and Tash, 1974). The suffix effect, which impairs recall of final items in a spoken list, is influenced by both structural and conceptual factors, challenging the traditional view that the effect is restricted to terminal items and suggesting it arises from perceptual grouping(Bloom, 2006)

Trivia Example: A practical example of the suffix effect occurs during everyday tasks such as recalling a grocery list. If someone interrupts with an unrelated comment right after the list is recited, this “suffix” can disrupt the recall of the last few items. For example, hearing someone ask, “Do you want anything else?” immediately after listing the groceries could impair the ability to remember “milk” or “bread” at the end of the list.

This demonstrates how irrelevant auditory information can interfere with memory in reallife scenarios.

Selected References

Bloom, L. C. (2006). Two-component theory of the suffix effect: Contrary evidence. Memory & cognition, 34(3), 648-667.

Crowder, R. G., & Morton, J. (1969). Precategorical acoustic storage (PAS). Perception & Psychophysics, 5(6), 365–373.

Greene, R. L. (1986). Spacing effects in memory: Evidence for a two-process account. Journal of Experimental Psychology: Learning, Memory, and Cognition, 12(3), 371– 377.

Pisoni, D. B., & Tash, J. (1974). Reaction times to comparisons within and across phonetic categories. Perception & Psychophysics, 15(2), 285–290

Business Example: The suffix effect is relevant during verbal communication, such as meetings or presentations. For instance, if a manager ends a meeting by mentioning unrelated topics, such as upcoming social events, the team’s ability to recall critical action items from the meeting may be diminished. To minimize the impact of the 87

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SPOTLIGHT EFFECT Spotlight effect is the phenomenon in which people tend to believe they are noticed more than they really are. puzzled.

"Do you see that coffee stain? Just imagine, the security guard accidentally spilled coffee on me. How can I attend like this?

Everyone will be pointing and laughing," Ellie exclaimed.

"To be honest, the stain is tiny and near the collar. If you hadn't mentioned it, I probably wouldn't have noticed," Rooney remarked.

"You never pay attention to details!" Ellie retorted.

"Come on, it's barely noticeable there. Nobody will notice," Rooney insisted.

"They'll notice, and they'll make fun of me!" Ellie remained resolute.

"I'll ask one more time: are you coming?"

"No!" "Alright, I understand, but it's really not a big deal."

"It's not just a minor issue!"

"Okay. Wait here – I'll be right back," Rooney vanished into the depths of the gallery.

Upon his return, he was carrying a bright red scarf.

"What's this?" Ellie asked.

"It's a scarf. Stand up – I just bought it at the gallery store. We'll tie it over your shirt, and the stain will be completely hidden.

There you go!"

Ellie brightened up – the scarf was large and effectively concealed the coffee stain that had been bothering her.

"Enough of sitting around," Rooney declared.

"Let's go! And don't forget to smile. Stop sulking."

"Why are you hiding out here?" Rooney found Ellie by the gallery entrance. "I've been searching for you everywhere! Come on, it's time to display your paintings." Rooney had intentionally visited the exhibition where Ellie had two of her artworks.

"I'm not going," Ellie sat despondently on the steps in front of the building.

"Why? What's wrong?" Rooney inquired.

"Look," Ellie pointed at the top of her shirt.

"What am I supposed to see?" Rooney was 88

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reality, most colleagues are unlikely to dwell on such minor errors. Managers can address this bias by fostering a culture that normalizes mistakes and emphasizes collective growth. For instance, emphasizing feedback as a learning tool rather than a critique can help employees feel less self-conscious and more focused on their contributions. Companies can also provide training on self- awareness and resilience to mitigate the negative effects of the spotlight bias.

About: The spotlight effect refers to the cognitive bias where individuals overestimate how much their actions, appearance, or mistakes are noticed by others. Coined by Thomas Gilovich and colleagues in the late 1990s (e.g., Hagger et al., 2010), the phenomenon arises from egocentric thinking, where individuals project their heightened self-awareness onto others (Gilovich et al., 2000). This bias has been studied in various social contexts, including public speaking, social anxiety, and self-esteem, revealing that most people pay far less attention to others than is commonly assumed. By understanding the spotlight effect, individuals can reduce unnecessary self-consciousness and improve their social interactions. This concept has practical implications for mental health, highlighting strategies to manage feelings of embarrassment and improve self-perception in interpersonal and professional settings (Schlenker & Leary, 1982).

Reproducibility: The spotlight effect has been extensively studied and replicated in diverse contexts, demonstrating its robustness in social psychology. For example, Gilovich et al. (2000) found that participants wearing an embarrassing T- shirt significantly overestimated how many others noticed it. Subsequent studies, such as those by Savitsky et al. (2001), confirmed similar findings in situations involving public speaking and social evaluation. The intensity of the effect varies based on factors such as individual levels of self-consciousness, situational stakes, and cultural norms. Ongoing research explores its broader implications for social behavior and interventions to alleviate its impact on mental health and performance.

Trivia Example: A common illustration of the spotlight effect occurs when someone spills coffee on their shirt before entering a meeting. They may feel that everyone is focused on the stain, but in reality, most people are likely preoccupied with their own concerns. This bias also explains why individuals often feel overly scrutinized in social settings, such as walking into a crowded room, even when others are unlikely to notice or remember their actions.

Selected References

Gilovich, T., Medvec, V. H., & Savitsky, K. (2000). The spotlight effect in social judgment: An egocentric bias in estimates of the salience of one’s own actions and appearance.

Journal of Personality and Social Psychology, 78(2), 211– 222.

Hagger, M. S., Wood, C., Stiff, C., & Chatzisarantis, N. L. (2010). Ego depletion and the strength model of self-control: a metaanalysis. Psychological bulletin, 136(4), 495.

Savitsky, K., Epley, N., & Gilovich, T. (2001). Do others judge us as harshly as we think? Overestimating the impact of our failures, shortcomings, and mishaps. Journal of Experimental Social Psychology, 37(3), 221–229.

Schlenker, B. R., & Leary, M. R. (1982). Social anxiety and selfpresentation: A conceptualization and model.

Psychological Bulletin, 92(3), 641–669.

Business Example: The spotlight effect frequently affects workplace dynamics. For example, an employee who stumbles over a word during a presentation may feel that the entire audience is fixated on their mistake, undermining their confidence. In 89

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SPACING EFFECT Spacing effect is the phenomenon whereby learning is greater when studying is spread out over time, as opposed to studying the same amount of content in a single session. where sketches were spread out. It was clear she was diligently working on them.

"I'm currently working on an advertising project. I need to create 12 variations of online ads for web banners."

"12 of them?" Rooney widened his eyes. "Why so many? I thought advertising concepts were developed once, and then they were repeatedly shown to potential clients to make the brand memorable, you know, to 'hammer it in.'"

Ellie chuckled. "You're quite old-fashioned.

That's a thing of the past! Recent studies show that people remember information better when it's spread out over time.

When potential clients see ads in the same style but slightly different formats and in a non-intrusive manner, they remember the brand better. So, one company has commissioned us to create advertising that will be spread out over 12 months. They want the art concept to be the same, but with variations. You see, this way, they can show slightly different ads every month throughout the year, all in the same style."

"I see. That's clever. How's the assignment coming along for you?"

"You know, it's an interesting project, and I quite like it. But, of course, it's challenging..."

Ellie trailed off in thought.

"I'm sure you'll handle it. I won't keep you. I'll give you a call on Saturday."

"Hi, Ellie, how are you?" Rooney was thrilled to see Ellie. Spotting her at the cafe, he couldn't help but wonder why they hadn't met for so long—since the beginning of summer. "It feels like I haven't seen you in ages! Lately, we've only been talking on the phone. How's your internship going?"

"Hey, Rooney," Ellie looked up from her table, 90

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workshops and follow-up activities to reinforce key concepts over time. This strategy ensures that employees retain knowledge and skills, leading to enhanced performance and long-term productivity. Businesses can also implement digital tools like spaced repetition software to support ongoing professional development and ensure that critical information is retained.

About: The spacing effect is a well-established psychological phenomenon demonstrating how distributed learning over time enhances memory retention compared to cramming information into a single session. First identified by Hermann Ebbinghaus in the late 19th century, his experiments revealed that spacing repetitions of material led to more efficient learning and better long-term recall (Ebbinghaus, 1885/1964).

Subsequent research (e.g., Dempster, 1989) has confirmed the robustness of this effect, providing insights into how memory consolidation benefits from intervals between study sessions (Cepeda et al., 2006). The spacing effect is widely applicableBy understanding and applying this principle, educators and trainers can design more effective learning interventions that maximize retention and minimize cognitive overload.

Reproducibility: The spacing effect is one of the most robust and replicable phenomena in cognitive psychology (e.g., Rohrer and Taylor, 2006, Weinstein et al., 2018). Studies have consistently demonstrated its efficacy across a variety of contexts, including verbal learning, motor skill acquisition, and classroom settings (Cepeda et al., 2006; Dempster, 1989). However, factors such as the optimal spacing interval, the complexity of the material, and individual learner differences influence its effectiveness. For example, longer intervals between sessions are more effective for long-term retention, whereas shorter intervals work better for immediate recall. Ongoing research continues to explore these nuances, ensuring that the spacing effect remains a cornerstone of evidence-based educational and training practices.

Trivia Example: A practical illustration of the spacing effect is the “Leitner System,” a flashcard-based learning method developed by Sebastian Leitner in the 1970s. This system structures reviews at increasing intervals for items successfully recalled, while incorrect responses are reviewed more frequently. Language learners and students worldwide use adaptations of this method to memorize vocabulary, historical dates, and technical terms more effectively. The system’s success highlights the importance of timing in retaining information and shows the broader benefits of spaced repetition in learning.

Selected References

Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380.

Dempster, F. N. (1989). Spacing effects and their implications for theory and practice. Educational Psychology Review, 1(4), 309–330.

Ebbinghaus, H. (1964). Memory: A contribution to experimental psychology (H. A. Ruger & C. E. Bussenius, Trans.). Dover.

(Original work published 1885) Leitner, S. (1972). So lernt man lernen. Freiburg: Herder.

Rohrer, D., & Taylor, K. (2006). The effects of overlearning and distributed practice on the retention of mathematics knowledge. Applied Cognitive Psychology, 20(9), 1209– 1224.

Weinstein, Y., Madan, C. R., & Sumeracki, M. A. (2018). Teaching the science of learning. Cognitive Research: Principles and Implications, 3(1), 2.

Business Example: In the workplace, the spacing effect is often applied to employee training programs. For instance, companies design learning modules spread over several weeks, interspersed with review sessions and practical applications. A notable example is Google’s leadership development program, which integrates spaced 91

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SELF-RELEVANCE EFFECT Self-relevance effect occurs when information related to the self is more easily processed and remembered than other types of information.

"What happened again? I've sent you four emails today, and there's been no response," Rooney's voice sounded annoyed through the phone.

"Well, I forgot my password again," Ellie sounded upset. "You see, I forgot my email password, tried to log in with the wrong one several times, and they've locked me out. Now I have to call IT support."

"Then call them – what are you waiting for?

Listen, this isn't the first time this has happened to you!"

"Exactly. It's a constant issue for me," Ellie said, her voice even more downcast.

"How do you remember your passwords? Do you use a password manager?"

"No, I don't use one," Rooney replied. "You see, I encrypt personal information into my passwords. Important dates, meanings, names..." "I see," Ellie brightened up. "I'll try your method now." "Alright, sort out your email, and then give me a call!"

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algorithms to recommend content based on individual viewing histories, making suggestions personally relevant to each user. This personalization increases engagement and retention, as users are more likely to remember and act upon recommendations that resonate with their own preferences and experiences.

Such self-referential marketing approaches have been shown to enhance consumer response and brand loyalty (Choice Hacking, 2020).

About: The self-reference effect is a psychological phenomenon where individuals exhibit enhanced memory for information related to themselves. First identified in the 1970s, researchers such as Rogers, Kuiper, and Kirker (1977) demonstrated that self-referential processing leads to superior recall compared to other encoding methods. This effect arises because linking information to oneself involves deeper, more elaborate encoding, leveraging the well-organized and accessible self- schema.

Subsequent studies have reinforced these findings, highlighting the self’s unique role in memory enhancement (Symons and Johnson, 1997). Understanding the self-reference effect has significant implications for educational strategies, therapeutic interventions, and marketing practices, as it emphasizes the importance of personal relevance in information retention.

Reproducibility: The self-reference effect is a robust and wellreplicated phenomenon in psychological research. Meta-analyses have confirmed its consistency across various contexts and populations, demonstrating that self- referential encoding enhances memory performance more than other encoding strategies (Symons and Johnson, 1997). However, factors such as cultural differences, individual self-concept, and the nature of the material can influence the magnitude of the effect. Ongoing research continues to explore these moderating variables to better understand the underlying mechanisms and applications of the self-reference effect in diverse settings.

Trivia Example: A practical illustration of the self-reference effect is evident when individuals remember their own birthdays more readily than those of others. This phenomenon occurs because one’s birthday is inherently self-relevant, leading to deeper cognitive processing and, consequently, better recall. In contrast, remembering others’ birthdays often requires deliberate effort, as these dates lack the same personal significance and thus do not benefit from the self-reference effect.

Selected References

Choice Hacking. (2020). Self-Reference Effect in Marketing: Proven Personalization Tactics to Boost Engagement.

Retrieved from https://www.choicehacking.com/2020/08/14/selfreference-effect/ Rogers, T. B., Kuiper, N. A., & Kirker, W. S. (1977). Self-reference and the encoding of personal information. Journal of Personality and Social Psychology, 35(9), 677–688.

Symons, C. S., & Johnson, B. T. (1997). The self-reference effect in memory: A meta-analysis. Psychological Bulletin, 121(3), 371–394.

Business Example: In marketing, the self-reference effect is harnessed through personalized advertising strategies. For instance, Netflix utilizes 93

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SUGGESTIBILITY Suggestibility is a psychological effect characterized by the tendency to accept and act on the suggestions of others.

"Of course, I'll help, but what's wrong with you?

Should we visit a pharmacy on the way?"

"I don't know, but it's something serious."

"Can you explain properly? Maybe we should call a doctor?"

"I don't know, this morning my throat started itching. I searched the internet but didn't find anything useful. Then I went through my mom's medical encyclopedia. In short, it's something between tonsillitis, whooping cough, measles, and scarlet fever. I'm afraid of infecting my brother."

"What about your temperature?" Ellie asked.

"It's normal," Rooney replied hesitantly. Ellie laughed.

"You sang songs with the guitar at Rita's birthday party yesterday!"

"Yeah, I did. So what?"

"That's it! You probably just overdid it, and now your throat is itchy. Reading a medical encyclopedia and diagnosing yourself with all those illnesses is an old story."

"Why is that?" Rooney wondered.

"Believe me," Ellie said, her tone more serious.

"Half of my family are doctors. When my brother and I used to read our grandfather's medical encyclopedia as kids, we'd diagnose ourselves with all sorts of diseases!" ”Sure?" ”Positive! But I'll come over today. I'll have breakfast first and I will see you later."

”Hi, sorry for calling so early in the morning.

Listen, can you come over to my place?"

Rooney's voice sounded concerned. It didn't happen often, and Ellie began to worry too.

"What's happened?" she asked.

"Well, you see, my mom has gone on a business trip again, and I've fallen ill. Basically, I need help with my little brother. Will you help?"

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and confidence-evoking phrases—can shape consumer attitudes and increase purchase likelihood. Suggestibility also plays a role in consumer reviews; positive reviews often prime buyers to perceive subsequent purchases more favorably, regardless of intrinsic quality (Chevalier and Mayzlin, 2006).

About: Suggestibility refers to the tendency of individuals to integrate external information— such as suggestions, leading questions, or even indirect cues—into their beliefs, memories, and decisions. This concept has its foundations in early psychological studies on hypnosis and memory. One of the most notable contributions was by Elizabeth Loftus, whose seminal research in the 1970s and 1980s on eyewitness testimony and memory distortions demonstrated how suggestive questioning could implant false memories (Loftus and Palmer, 1974). More recent studies have explored the neurobiological underpinnings of suggestibility, revealing its ties to cognitive processes like attention and executive control (Scoboria et al., 2002).

Reproducibility: Suggestibility is one of the most reliably documented phenomena in psychological research, evidenced across diverse populations and settings. Seminal experiments like Loftus and Palmer’s (1974) study showed that altering a single word in a question—e.g., “smashed” versus “hit”—could significantly influence eyewitness memory of an event. Subsequent work has replicated these findings across varied paradigms, including studies on misinformation effects and false memories (Loftus, 2005).

However, suggestibility varies based on individual traits (e.g., cognitive flexibility or age), the nature of the suggestion, and the context (Scoboria et al., 2002). Emerging research explores its neural correlates (Csifcsák et al., 2019).

Trivia Example: The “War of the Worlds” radio broadcast of 1938 offers a historical illustration of suggestibility.

Directed by Orson Welles, this dramatization of H.G. Wells’ novel mimicked live news reports, leading many listeners to believe that an alien invasion was genuinely underway. The panic was fueled by contextual factors such as the plausibility of the scenario, the realism of the presentation, and the timing during an era of heightened global anxiety. Modern parallels include the rapid spread of misinformation on social media, where suggestible audiences may accept false or misleading news as credible due to its authoritative tone or corroborative appearance (Vosoughi et al., 2018).

Selected References

Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345-354.

Csifcsák, G., Boayue, N. M., Aslaksen, P. M., Turi, Z., Antal, A., Groot, J., Hawkins, G. E., Forstmann, B. U., Opitz, A., Thielscher, A., & Mittner, M. (2019). Commentary: Transcranial stimulation of the frontal lobes increases propensity of mind-wandering without changing metaawareness. Frontiers in Psychology, 10, Article 130.

Loftus, E. F. (2005). Planting misinformation in the human mind: A 30-year investigation of the malleability of memory.

Learning & Memory, 12(4), Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 13(5), 585-589.

Scoboria, A., Mazzoni, G., Kirsch, I., & Milling, L. S. (2002).

Immediate and persisting effects of misleading questions and hypnosis on memory reports. Journal of Experimental Psychology: Applied, 8(1), 26–32.

Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146-1151.

Business Example: The phenomenon of “anchoring” highlights suggestibility in pricing strategies: when retailers display a higher “original” price alongside a discounted price, consumers are more likely to perceive the deal as valuable, even if the original price is inflated. Similarly, suggestive language in advertisements— such as testimonials, scarcity cues (“limited time only”), 95

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STEREOTYPICAL BIAS Stereotypical bias is the tendency to believe certain stereotypes about different groups of people, which can affect both perception and memory.

"So, what time are we going to the gym tomorrow?" Ellie asked.

"Sorry, but tomorrow won't work. Relatives are coming from Germany. We'll be stocking up on beer," Rooney replied.

"Why do you have such strange stereotypes?

Just because your relatives are Germans doesn't mean they drink a lot of beer. Are you going to say that Americans always shout, the French wear berets, and Scots are all stingy?" Ellie retorted.

"You're right," Rooney admitted apologetically.

"I said something silly. I won't repeat it.

Don't be mad; I didn't mean it."

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About: Stereotypical (or stereotype) bias, refers to the inclination to form generalized beliefs about groups of people, which can shape perceptions, judgments, and actions. Walter Lippmann first introduced the concept in Public Opinion (1922), describing stereotypes as “pictures in our heads” that simplify complex realities. In 1954, Gordon Allport expanded on this idea in The Nature of Prejudice, identifying stereotypes as a foundation for prejudice and discrimination.

Research highlights how stereotypes are automatically activated in social interactions and influence cognition, often without conscious awareness (Devine, 1989). Stereotypical bias has been widely studied. More recently, studies have examined how digital platforms and algorithms can perpetuate and amplify stereotypical biases (Noble, 2018).

Trivia Example: Stereotypical bias appears in entertainment.

Villains often speak with foreign or regional accents, reinforcing stereotypes associating “foreignness” with malevolence (Dobrow and Gidney, 1998). Such portrayals can reinforce implicit biases, shaping perceptions of outgroups as untrustworthy or threatening.

Similarly, media representations of women in science, technology, engineering, and math (STEM) often reinforce stereotypes of these fields as male-dominated, discouraging women from pursuing STEM careers (Cheryan et al., 2015).

Business Example: The “glass ceiling” phenomenon is partly rooted in stereotypical bias (Eagly and Karau, 2002). For example, women leaders are often evaluated more harshly than their male counterparts for displaying assertiveness, a behavior stereotypically associated with men. Many organizations now employ implicit bias training, structured interviews, and blind recruitment processes to mitigate these biases (Dobbin and Kalev, 2016). The rise of AI tools for recruitment has also highlighted concerns about algorithms perpetuating biases, as they may learn and replicate historical patterns of discrimination (Binns, 2020).

Reproducibility: Stereotypical bias is among the most rigorously studied topics in social psychology. Classic studies, such as Tajfel’s (1970) minimal group experiments, demonstrated how social categorization based on arbitrary characteristics could foster in-group favoritism and out-group bias. Implicit Association Tests (IAT) have consistently revealed implicit biases across diverse populations and contexts (Greenwald et al., 1998). Research also demonstrates that stereotypes influence memory, causing people to remember stereotype- consistent information more accurately (Macrae et al., 1994). However, individual and contextual factors, such as motivation to control prejudice or exposure to counter-stereotypical exemplars, can moderate these effects (Devine et al., 2002). Continuing advancements in neuroscience and behavioral science aim to elucidate the cognitive and neural mechanisms underlying stereotypical bias.

Selected References Allport, G. W. (1954). The nature of prejudice. Reading, MA: Addison-Wesley. Binns, R. (2020). On the apparent conflict between individual and group fairness.

Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 514–524.

Cheryan, S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: Increasing girls’ interest in computer science and engineering by diversifying stereotypes. Frontiers in Psychology, 6, 49.

Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5–18.

Devine, P. G., Forscher, P. S., Austin, A. J., & Cox, W. T. L. (2002).

Long-term reduction in implicit bias: A prejudice habitbreaking intervention. Journal of Experimental Social Psychology, 48(6), 1267–1278.

Dobbin, F., & Kalev, A. (2016). Why diversity programs fail.

Harvard Business Review, 94(7), 52–60.

Dobrow, J. R., & Gidney, C. L. (1998). The good, the bad, and the foreign: The use of dialect in children’s animated television. The Annals of the American Academy of Political and Social Science, 557(1), 105–119.

Eagly, A. H., & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological Review, 109(3), 573–598.

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998).

Measuring individual differences in implicit cognition: The Implicit Association Test. Journal of Personality and Social Psychology, 74(6), 1464–1480.

Macrae, C. N., Milne, A. B., & Bodenhausen, G. V. (1994).

Stereotypes as energy-saving devices: A peek inside the cognitive toolbox. Journal of Personality and Social Psychology, 66(1), 37–47.

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York, NY: NYU Press.

Tajfel, H. (1970). Experiments in intergroup discrimination.

Scientific American, 223(5), 96–102.

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TESTING EFFECT Testing effect is the finding that long-term memory is increased when some of the learning period is devoted to retrieving the to-be- remembered information through testing with proper feedback.

"Good thing you stopped by, come in," Rooney opened the door for Ellie. "Are you here to quiz me? I'm studying Chinese."

"Why on earth are you learning Chinese?" Ellie asked with a smile. "Yanzhen invited me to her birthday party. Her whole family will be there, so I thought learning Chinese would be useful," Rooney explained.

"Yanzhen? Well, that explains a lot," Ellie chuckled as she settled on the couch.

"Listen, don't make fun of me. Will you help or not?" Rooney wasn't thrilled that Ellie didn't take his intention to learn Chinese seriously. "Alright, alright, what do I need to do?"

"Well," Rooney proudly handed Ellie a stack of flashcards, "I made flashcards. Quiz me?"

"Wow, quite organized," Ellie continued to tease, "and what are the flashcards for?"

"If you're going to keep this up, I might as well do it myself," Rooney tried to take the flashcards back. "I learn better this way.

You see, when I'm asked questions, it's like a test. I learn faster."

"Okay, okay," Ellie put on a serious expression and, taking the first flashcard, asked, "How do you say 'Good day, how are you?' in Chinese?"

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workplace safety protocols, companies implement short quizzes or scenario-based tests to encourage retrieval of key information.

Research indicates that these active recall practices significantly improve retention and application of knowledge in real-world settings (Sitzmann and Ely, 2011).

About: The testing effect, also known as retrieval practice or test-enhanced learning, refers to the improvement of long-term memory retention through active retrieval of information rather than passive review. Early educational theorists like William James and John Dewey emphasized the benefits of active engagement with material, but systematic exploration of the phenomenon began with experiments by researchers like Hermann Ebbinghaus and Arthur Gates.Ebbinghaus’ pioneering work on forgetting curves demonstrated the advantages of spaced repetition and retrieval. Subsequent research (e.g., Roediger and Karpicke 2006) firmly established the testing effect as a key principle in cognitive psychology, demonstrating its broad applicability in educational and training settings.

Reproducibility: The testing effect is a robust finding in cognitive psychology, consistently replicated across a wide range of studies and contexts. Roediger and Karpicke (2006) demonstrated that students who practiced retrieval by taking tests performed better on delayed assessments compared to those who simply restudied the material.

Subsequent research has shown the testing effect applies across various materials, including text, visuals, and practical skills, and in diverse settings, such as classrooms, online courses, and professional training (e.g., Dunlosky et al., 2013).

Variables like test format, feedback, and the timing of practice influence the magnitude of the effect, and ongoing research continues to refine our understanding of how to optimize retrieval practices for maximum learning.

Trivia Example: The testing effect is vividly illustrated in language learning through the use of flashcards.

For example, students learning Spanish vocabulary who actively test themselves by recalling word meanings or conjugations from flashcards tend to retain the information more effectively than those who merely review word lists repeatedly. Studies show that retrieval practice enhances the encoding of material into long-term memory, making the information more accessible for future use (Kang, 2016). This method has become a staple in language acquisition and other domains where memory plays a critical role, showcasing the practical utility of the testing effect.

Selected References

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology.

Psychological Science in the Public Interest, 14(1), 4-58.

Kang, S. H. K. (2016). Spaced repetition promotes efficient and effective learning: Policy implications for instruction.

Policy Insights from the Behavioral and Brain Sciences, 3(1), 12-19.

Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention.

Psychological Science, 17(3), 249-255.

Sitzmann, T., & Ely, K. (2011). A meta-analysis of self-regulated learning in work- related training and educational attainment: What we know and where we need to go.

Psychological Bulletin, 137(3), 421-442.

Business Example: The effect is increasingly used in corporate training programs to boost employee learning.

For instance, after training employees on new 99

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TELESCOPING EFFECT Telescoping effect is a temporal distortion phenomenon in which people tend to perceive recent events as being more remote than they are and distant events as being more recent.

“Hey, Rooney, listen, can you come over tomorrow?"

Rooney, not yet fully awake and not realizing it was Ellie calling, asked, "Come over where?

Who is this?"

"Wake up, sleepyhead, it's almost noon! It's Ellie.

Please come over tomorrow, I need your help," Ellie figured that Rooney had decided to sleep in this Saturday.

"Alright, I'll come," Rooney said, stretching.

"What's going on?"

"You see, I need to replant the orchids in the greenhouse. I can't do it on my own."

"Wait, didn't we just replant some flowers a couple of weeks ago? Are we doing it again?" Rooney asked with a more awake voice.

"Firstly, we replanted roses, not orchids, and that was back in March, not a couple of weeks ago. It's already September outside!"

Ellie chuckled.

"Seriously? It feels like we just replanted something there not long ago!" Rooney scratched his head. "Alright, don't worry.

I'll help you. See you tomorrow!"

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consumer behaviors and trends, complicating efforts to design effective marketing strategies or forecast demand (e.g., Sudman & Bradburn, 1974).

To counteract this effect, companies increasingly use transaction records or behavioral data alongside self- reported surveys to improve the accuracy of customer insights.

About: The telescoping effect refers to the cognitive distortion where individuals perceive recent events as occurring further in the past and distant events as happening more recently than they did. This phenomenon was first studied in the mid-20th century in the context of memory research. Pioneers like Norman E. Bradburn and Seymour Sudman (1982) identified this bias during their investigations into survey accuracy, highlighting how individuals often compress or expand timelines when recalling past events.

Subsequent studies have connected this effect to cognitive processes such as episodic memory encoding and retrieval, as well as temporal schemata that influence how people mentally organize time (Rubin and Baddeley, 1989; Shiffman et al., 1997). The effect is particularly relevant in fields such as forensic psychology, where accurate recall of timelines is critical, and in consumer research, where reliable selfreported data is essential.

Reproducibility: The telescoping effect is a consistently observed phenomenon in psychological research.

Bradburn et al. (1978) demonstrated that individuals systematically misestimate the timing of past events, compressing recent events backward and extending distant ones forward.

Similar findings have been replicated in studies of autobiographical memory (Rubin and Baddeley, 1989). Other research has shown that age and cognitive decline can exacerbate the telescoping effect, with older adults often displaying greater distortions in temporal judgment (Janssen et al., 2005; Peterson et al., 2024). While the effect is robust, contextual factors like event familiarity and estimation methods can modulate its strength, making it a critical area of ongoing exploration in cognitive and applied psychology.

Trivia Example: Many individuals perceive landmark events such as the fall of the Berlin Wall (1989) or the September 11 terrorist attacks (2001) as having occurred more recently than they actually did.

Conversely, personal milestones like weddings or graduations may feel more distant than the actual timeline suggests. This bias reflects the difficulty individuals face in accurately gauging temporal distance, often influenced by the emotional salience or frequency of recalling the event (Janssen et al., 2005). Such distortions demonstrate how the effect reshapes not only personal memory but also collective recollections of history.

Selected References

Bradburn, N. M., Rips, L. J., & Shevell, S. K. (1978). Answering autobiographical questions: The impact of memory and inference on surveys. Science, 236(4796), 157-161.

Janssen, S. M., Chessa, A. G., & Murre, J. M. (2005). The reminiscence bump in autobiographical memory: Effects of age, gender, education, and culture. Memory, 14(6), 658-671.

Peterson, C., Wang, Q., Hallett, D., Bartlett, S., Ma, A. Y., MacKay, M. M., E. J. Pretty, L. Viscarra, & Wang, E. Y. (2024). Dating early memories: When did events really happen?.

Cognitive Development, 71, 101489.

Rubin, D. C., & Baddeley, A. D. (1989). Telescoping is not time compression: A model of the dating of autobiographical events. Memory & Cognition, Shiffman, S., Stone, A. A., & Hufford, M. R. (1997). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1-32. https://doi.org/10.1146/annurev.clinpsy.3.022806.091415 Sudman, S., & Bradburn, N. M. (1974). Response effects in surveys: A review and synthesis. Chicago, IL: Aldine

Business Example: When customers participate in surveys asking how long ago they purchased or used a product, their responses may be distorted by telescoping.

Such inaccuracies can mislead businesses about 101

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TACHYPSYCHIA Tachypsychia is a neurological condition that alters the perception of time, usually experienced in high-stress or life-threatening situations, often making events seem to slow down.

"So, did you like the online photography course?

It's amazing, isn't it? I managed to complete all the assignments in 24 hours; I couldn't tear myself away. Time just flew by," Ellie recently came across an online course and sent the link to Rooney.

"Oh, it was so boring," unexpectedly stated Rooney. "I kept waiting for it to end. I wasted almost a week of my life and didn't learn much. It was stretched out and the lecturer just kept droning on. You could die of boredom."

"You're kidding," Ellie was surprised. "I actually liked it! I thought it was an excellent course.

I'd sign up for something similar again."

"Feel free to, but count me out!"

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complex data and predict outcomes in what feels like an extended moment of time. This altered perception allows for rapid, yet deliberate, decision-making. Studies in organizational psychology suggest that time perception under stress can significantly impact performance, with experienced leaders leveraging this phenomenon to navigate crises more effectively (Driskell et al., 1999).

About: Tachypsychia is a psychological phenomenon characterized by distortions in time perception, typically experienced during high-stress or lifethreatening situations. Individuals undergoing tachypsychia often report a sensation of time slowing down or speeding up, enabling heightened focus or accelerated reactions. The term combines Greek roots: “tachy” (fast) and “psych” (mind). Although William James described subjective time dilation in his early writings on human consciousness, the systematic study of tachypsychia gained prominence later, particularly in fields like emergency medicine, law enforcement, and military psychology. More recent research explores its physiological correlates, such as the role of adrenaline and stress-induced changes in attentional processes (Stetson et al., 2007). This phenomenon highlights how subjective experiences of time are closely tied to cognitive and emotional states, particularly under duress.

Reproducibility: Tachypsychia (e.g., Phillips et al., 2020) is supported by anecdotal accounts and qualitative studies across diverse domains, but its scientific reproducibility is limited by methodological challenges. Experimental studies attempting to replicate time distortion often rely on controlled stress induction through methods like simulated emergencies or virtual reality scenarios (Stetson et al., 2007). While these studies provide evidence of stress-induced time perception alterations, individual variability, and the influence of memory biases pose limitations. For example, people with heightened adrenaline responses are more likely to report significant time distortion, suggesting that physiological differences affect the phenomenon’s consistency.

Trivia Example: During penalty shootouts in soccer, players and goalkeepers report a sense of time dilation, which allows for an intense focus on movement and execution. Similarly, elite athletes in fast-paced sports like Formula 1 racing describe perceiving split-second decisions in an expanded timescale, enabling them to anticipate and react more effectively. These experiences are supported by research suggesting that heightened arousal during critical moments enhances attention and alters the subjective flow of time (Hancock and Weaver, 2005).

Selected References

Driskell, J. E., Salas, E., & Johnston, J. (1999). Does stress lead to a loss of team perspective? Group Dynamics: Theory, Research, and Practice, 3(4), 291–302.

Hancock, P. A., & Weaver, J. L. (2005). On time distortion under stress. Theoretical Issues in Ergonomics Science, 6(2), 193–211.

Phillips, I., Upadhyayula, A., & Flombaum, J. (2020).

Tachypsychia—the subjective expansion of time— happens in immediate memory, not perceptual experience. Journal of Vision, 20(11), 1466-1466.

Stetson, C., Fiesta, M. P., & Eagleman, D. M. (2007). Does time really slow down during a frightening event? PLoS ONE, 2(12), e1295.

Business Example: During a market crash, financial decision-makers often report a heightened ability to process 103

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TRAVIS SYNDROME Travis syndrome refers to the belief that things were better in the past, particularly in reference to relationships or social situations. interested.

"You can't even imagine! My brother proposed to his girlfriend, and now they're getting married!" Ellie joyfully announced, not waiting for a response. "There's so much to do now! We need to make a guest list, choose a date and a venue, arrange all the flowers, pick out dresses! It's going to be amazing! I think it's going to be a super wedding! We'll have around 150 guests just from our family! I can already picture the bridesmaids' dresses! And the wedding cake."

"Ellie, come back down to earth. Firstly, they'll probably postpone the wedding! Due to the coronavirus, gathering in large groups has been prohibited, so a big wedding under these conditions is unlikely. Secondly, it's not your wedding, it's your brother's and his bride's, so it would be good to ask them what they want. Maybe they don't need a big wedding. Besides, I understand that it's exciting, but it's not certain that they'll need your help. You're getting ahead of yourself!"

There was silence on the other end of the line.

"You sure know how to dampen the mood," Ellie finally replied. "But you're right about one thing. I might be getting ahead of myself.

Nevertheless, I'm really happy."

"I'm happy too – pass on my greetings and congratulations to your brother!"

"I have some incredible news!" From Ellie's voice on the phone, Rooney understood that she was about to share some sensational information.

"I already know the news is important," Rooney said, yawning. "You're aware it's only 7 AM right now! I hate being woken up early on a Sunday."

"You'll sleep your life away!" Ellie continued, paying no attention to the early hour and Rooney's sarcasm.

"Alright, what's the news?" Rooney asked, now 104

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counteract this bias through clear communication, highlighting the tangible benefits of change while acknowledging the value of past contributions.

About: The tendency to view the past more favorably than the present is a well- documented psychological phenomenon. Known as “rosy retrospection,” this bias leads individuals to remember past events more positively than they were actually experienced (e.g., De Vos and Sullivan, 2025). A related concept, “declinism,” reflects the belief that society or institutions are in decline, often idealizing a perceived “golden age.” These phenomena are deeply tied to memory processes, where positive elements of past experiences are more vividly retained than negative aspects (Mitchell et al., 1997). Cognitive and cultural factors play key roles in shaping this bias, with nostalgia often serving as a coping mechanism for present dissatisfaction.

Reproducibility: Rosy retrospection is a robust and reproducible phenomenon in psychological research. Studies consistently demonstrate that individuals recall past experiences, such as vacations or social events, more positively over time, even when the events were stressful or unpleasant (Mitchell et al., 1997; Skowronski et al., 1991). This positivity bias has been observed across cultures and contexts, reinforcing its generalizability.

However, the degree of rosy retrospection can vary based on individual traits, such as optimism or coping style, and cultural influences that shape collective memory ((Wildschut et al., 2006). Ongoing research explores neural mechanisms and contextual moderators, aiming to understand why the brain selectively amplifies positive memories, thereby distorting perceptions of the past.

Trivia Example: Rosy retrospection is frequently observed in romantic relationships, where individuals idealize past partners by recalling only the positive moments and minimizing or forgetting conflicts. For instance, after a breakup, a person might remember their ex-partner’s affectionate gestures while overlooking incompatibilities or arguments. This selective recall can hinder emotional closure and lead to skewed comparisons with current relationships (Wildschut et al., 2006).

Selected References

De Vos, A., & Sullivan, S. E. (2025). Applying three theoretical lenses to further explore the boomerang career transition. Applied Psychology, 74(2), e70010.

Mitchell, T. R., Thompson, L., Peterson, E., & Cronk, R. (1997).

Temporal adjustments in the evaluation of events: The “rosy view.” Journal of Experimental Social Psychology, 33(4), 421–448.

Ramesh, P., Bhavikatti, V., Omnamasivaya, B., Chaitanya, G., Tejaswini, Hiremath, S., ... & Kameswari, J. (2023).

Organisational Adaptability: A Study of the Mediating Role of Leadership in the Influence of Strategies, Complexity, and Technology. International Journal of Innovation Management, 27(07n08), 2350036.

Skowronski, J. J., Betz, A. L., Thompson, C. P., & Shannon, L. (1991). Social memory in everyday life: Recall of selfevents and other-events. Journal of Personality and Social Psychology, 60(3), 362–371.

Wildschut, T., Sedikides, C., Arndt, J., & Routledge, C. (2006).

Nostalgia: Content, triggers, functions. Journal of Personality and Social Psychology, 91(5), 975–993.

Business Example: Employees often perceive prior processes or leadership styles as superior, even when evidence suggests otherwise. For example, during the implementation of new technologies, workers might resist adoption, arguing that legacy systems were “better.” This resistance stems from the comfort of familiarity and the tendency to overstate the effectiveness of previous practices (Ramesh et al., 2023). Leaders addressing such challenges need to actively 105

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TIP OF THE TONGUE Tip-of-the-tongue phenomenon is the feeling that one knows a piece of information (often a word or a name) but is temporarily unable to recall it, with a sense that retrieval is imminent.

"What are you up to?" It had been raining for two weeks straight, and Rooney called Ellie on a Sunday to check in. "What a weather! Not much you can do. I've been shuttling between home and the store, from the store back home, and from home to the gym and back. Feels like Groundhog Day." "I'm not up to anything," Ellie sighed. "I wanted to watch a movie, but I can't seem to find anything good. I've been trying to pick one for half an hour."

"Listen, just last week, I watched this great movie... What's it called again? Let me think... The title's on the tip of my tongue...

There's this famous English actor in it...

What's his name... Come on... Nope, I can't remember."

"Who else is in the movie?" Ellie asked, trying to help Rooney recall. "No, I can't remember – the title just slipped my mind. Wait, I'll check my viewing history and call you back! I'll be quick!"

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professionals often rely on visual aids (slides), notes, or rehearsal techniques to reinforce memory retrieval. Studies suggest that repeated exposure and practice can reduce TOT frequency.

About: The “tip-of-the-tongue” (TOT) phenomenon is a temporary cognitive state in which an individual cannot recall a familiar word or name, despite a strong feeling of its imminence. Roger Brown and David McNeill were among the first researchers to study TOT systematically in the 1960s, describing it as a form of retrieval failure. Their work revealed insights into the disconnect between memory access and retrieval. More recent research has expanded on this foundation, exploring how semantic and phonological connections in the brain contribute to TOT experiences (Schwartz, 1999). The phenomenon highlights the complexities of language processing and memory retrieval, shedding light on the interplay between knowledge storage and access in the human mind.

Reproducibility: The TOT phenomenon is a well-replicated phenomenon in psychological research, observed across languages, cultures, and age groups. Cross-linguistic studies reveal that TOT is not confined to English, suggesting that it arises from universal cognitive mechanisms.

However, individual differences, such as bilingualism and working memory capacity, can influence TOT frequency and recovery success (Gollan and Silverberg, 2001). Advances in neuroimaging have further illuminated the neural basis of TOT, linking it to activity in the prefrontal cortex and temporal lobes, areas critical for language processing and memory retrieval (e.g., Maril et al., 2001, Pournaghdali et al., 2025).

Trivia Example: A striking example of the TOT phenomenon occurred during an episode of Jeopardy!, where a contestant struggled to recall a well-known historical figure’s name despite evident familiarity with the details. The contestant eventually recovered the name after the allotted time, illustrating the frustrating yet transient nature of TOT. Such public moments show how even highly prepared individuals are susceptible to retrieval lapses. These occurrences are often triggered by stress or high stakes, factors known to exacerbate TOT states (Schwartz, 2002).

Selected References

Brown, R., & McNeill, D. (1966). The “tip of the tongue” phenomenon. Journal of Verbal Learning and Verbal Behavior, 5(4), 325–337.

Burke, D. M., MacKay, D. G., Worthley, J. S., & Wade, E. (1991). On the tip of the tongue: What causes word finding failures in young and older adults? Journal of Memory and Language, 30(5), 542–579.

Gollan, T. H., & Silverberg, N. B. (2001). Tip-of-the-tongue states in Hebrew- English bilinguals. Bilingualism: Language and Cognition, 4(1), 63–83.

Maril, A., Wagner, A. D., & Schacter, D. L. (2001). On the tip of the tongue: An event-related fMRI study of semantic retrieval failure and cognitive conflict. Neuron, 31(4), 653– 660.

Pournaghdali, A., Schwartz, B. L., & Soto, F. A. (2025). Tip-of-theTongue and Feeling-of-Knowing Experiences Enhance Metacognitive Sensitivity of Confidence Evaluation of Semantic Memory. Journal of Cognition, 8(1).

Schwartz, B. L. (1999). Sparkling at the end of the tongue: The etiology of tip-of- the-tongue phenomenology.

Psychonomic Bulletin & Review, 6, 379- 393.

Schwartz, B. L. (2002). Tip-of-the-tongue states: Phenomenology, mechanism, and lexical retrieval. Mahwah, NJ: Lawrence Erlbaum Associates.

Business Example: In the business world, the TOT phenomenon can disrupt presentations and negotiations. A project manager may experience a TOT moment while presenting quarterly performance data, struggling to recall specific statistics despite knowing the content. This temporary lapse can undermine confidence and derail communication. To address such challenges, 107

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REMINISCENCE BUMP Reminiscence bump is a phenomenon where people tend to recall more personal events from adolescence and early adulthood than from other periods of their lives.

"Alright, youngsters," Ellie's father was in high spirits. "Dad, we're heading to the park on our bikes," Ellie said.

"We'll be on our way shortly," added Rooney, who was tinkering with Ellie's bike.

"Just need to inflate the tire, and we're good to go."

"Biking sounds fantastic! I remember in my youth; I used to ride my bike all the time.

So many different adventures," her father reminisced. "Dad, we know, you've told us," Ellie smiled.

"Did I ever tell you about the time your Uncle Arthur and I had a race? I was on a bike, and he was in a car."

"Yes, Dad, you've told us. And how he took the highway, and you cut through the woods, winning the bet."

"Oh, I did? How about the time both my tires went flat, and I had to carry my bike for six miles?"

"You've told that story a hundred times," Ellie rolled her eyes. "And the one about how you met Mom while she was biking, and how you found that injured crow and took care of it for six months. You've told them all. Alright, Dad, we've got to go."

"Imagine that. Alright, bye, sweetheart. Rooney, keep an eye on her!"

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Similarly, tech brands like Nintendo have revitalized retro gaming consoles, tapping into formative experiences from their customers’ adolescence to drive sales and emotional engagement.

About: The reminiscence bump (e.g., Janssen, 2020) refers to the psychological tendency for individuals to recall a disproportionately high number of autobiographical memories from adolescence and early adulthood, typically between ages 10 and 30. First identified by researchers like Rubin, Rahhal, and Poon (1998), this phenomenon has been extensively studied as a cornerstone of autobiographical memory research. These years often coincide with critical developmental milestones such as identity formation, peak neuroplasticity, and culturally significant life events, which contribute to the heightened memorability of this period (Conway et al., 2005). Subsequent studies have further explored the neurocognitive and cultural influences on the reminiscence bump, demonstrating its interplay with emotional salience and the distinctiveness of events during this life stage (Janssen et al., 2005). This phenomenon offers insights into memory processes and the construction of the self across diverse populations.

Reproducibility: The reminiscence bump is a robust and wellreplicated phenomenon.

Studies have consistently observed it across diverse cultures, including Western, Asian, and Middle Eastern populations (e.g., Janssen et al., 2007). Methods such as free recall tasks, cue word techniques, and life narrative studies have reliably reproduced the effect. However, nuances exist; for instance, cultural variations influence the content of the reminiscence bump, with Western individuals emphasizing personal achievements and Eastern individuals recalling familial or collective events (Matsumoto and Yoo, 2006). Additionally, individual differences, such as trauma or atypical life trajectories, can modulate the effect. Future research aims to refine our understanding of the neurocognitive and cultural mechanisms underpinning this phenomenon.

Trivia Example: A compelling real-life illustration of the reminiscence bump is the enduring emotional resonance of first-time experiences, such as hearing a favorite song from adolescence. Studies show that older adults often rank music from their late teens and early twenties as the most emotionally impactful, regardless of later musical exposure (Schulkind et al., 1999). This helps explain the widespread success of retrothemed music tours, where older audiences relive emotionally charged memories from their youth.

Selected References

Conway, M. A., Wang, Q., Hanyu, K., & Haque, S. (2005). A crosscultural investigation of autobiographical memory: On the universality and cultural variation of the reminiscence bump. Journal of Cross-Cultural Psychology, 36(6), 739–749.

Janssen, S., Chessa, A., & Murre, J. (2005). The reminiscence bump in autobiographical memory: Effects of age, gender, education, and culture. Memory, 13(6), 658-668.

Janssen, S. M., Chessa, A. G., & Murre, J. M. (2007). Temporal distribution of favourite books, movies, and records: Differential encoding and re- sampling. Memory, 15(7), 755-767.

Janssen, S. M. (2020). Introduction to the cognitive abilities account for the reminiscence bump in the temporal distribution of autobiographical memory. Psychological Reports, 123(1), 12-42.

Matsumoto, D., & Yoo, S. H. (2006). Toward a new generation of cross-cultural research. Perspectives on Psychological Science, 1(3), 234–250.

Rubin, D. C., Rahhal, T. A., & Poon, L. W. (1998). Things learned in early adulthood are remembered best. Memory & Cognition, 26(1), 3–19. https://doi.org/10.3758/BF03211366 Schulkind, M. D., Hennis, L. K., & Rubin, D. C. (1999). Music, emotion, and autobiographical memory: They’re playing your song. Memory & Cognition, 27(6), 948–955. https://doi.org/10.3758/BF03201225

Business Example: In marketing, the reminiscence bump is a valuable tool for targeting nostalgia-based campaigns. For example, Coca-Cola’s “Share a Coke” campaign leveraged popular names and cultural references from the 1980s and 1990s to resonate with Generation X and millennials, evoking personal and collective memories.

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VON RESTORFF EFFECT von Restorff effect (isolation effect) occurs when an item that "stands out like a sore thumb" (is atypical or isolated) is more likely to be remembered than other items.

"Come in, Ellie, Rooney will be here soon. I sent him to the store," Rooney's mother said as she let Ellie in and went to the kitchen.

Ellie had just stepped in when Rooney appeared at the entrance.

"Hi," he greeted. "Just a moment, I'll put these bags in the kitchen and then we can go to the café. The weather is lovely. So sunny!"

A minute later, Rooney came back, lacing his shoes, when suddenly his mother's voice echoed from the kitchen: "Rooney, where's the milk? And the berries I asked you to buy for the baby? Did you get the honey?"

"I got the honey," Rooney called back. "But I forgot the berries and milk." Rooney's mother emerged into the hallway: "Listen, where's the list I gave you?"

"Well," Rooney said sheepishly, "I lost the list.

The minced meat and honey were marked with a green highlighter – I remembered those clearly. I tried to recall the rest from memory."

His mother shook her head. "I thought as much.

I didn’t ask for cookies and cake. Alright, I'll write you a new list – you would have to go to the store again. Ellie, could you make sure he doesn't lose the list this time?"

"Sure," Ellie said. "Let's go – first to the store, and then to the café," she told Rooney.

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crowded markets.

Reproducibility: The von Restorff effect is a well-replicated and robust phenomenon in memory research.

Numerous studies across diverse populations and contexts demonstrate its reliability (Hunt, 1995; Schmidt, 1991). Distinctiveness, whether visual, semantic, or auditory, consistently enhances recall across paradigms like free recall, recognition tasks, and visual attention experiments (Fabiani and Donchin, 1995).

However, individual cognitive factors, such as working memory capacity and attentional control, as well as the degree of distinctiveness, can modulate the effect. Neuroimaging studies also support its replicability, showing consistent activation patterns in brain regions associated with attention and memory processing (Kafkas and Montaldi, 2018). Future research aims to explore its applications in diverse fields, from virtual environments to AI-based learning systems (e.g., Thiyagarajan and Swathi, 2025).

Selected References

About: The von Restorff effect (e.g., Jisha and Excelce, 2024), or isolation effect, refers to the psychological tendency to better remember an item that stands out from its context. Identified

by German psychiatrist Hedwig von Restorff in 1933, her seminal experiments revealed that participants recalled distinctive items in homogeneous lists more frequently than nondistinctive ones (von Restorff, 1933). This phenomenon highlights the impact of salience on memory encoding and retrieval and has been extensively studied in cognitive psychology.

More recent research has expanded on von Restorff’s findings, examining the neural correlates of distinctiveness and its influence on memory, suggesting that the effect is linked to enhanced activation in the hippocampus and prefrontal cortex (Quent et al., 2021). This fundamental principle has applications in education, advertising, and information design, where capturing attention and enhancing recall are critical.

Trivia Example: The von Restorff effect is evident in the design of warning labels on products. For instance, warnings about hazardous substances often appear in bright colors like red or yellow and bold text, helping them stand out from the rest of the packaging. Research indicates that individuals are more likely to recall these warnings due to their visual distinctiveness (Argo and Main, 2004). This practical use highlights how perceptual salience can enhance memory in everyday contexts.

Argo, J. J., & Main, K. J. (2004). Meta-analyses of the effectiveness of warning labels. Journal of Public Policy & Marketing, 23(2), 193–208.

Fabiani, M., & Donchin, E. (1995). Encoding processes and memory organization: a model of the von Restorff effect.

Journal of Experimental Psychology: Learning, Memory, and Cognition, 21(1), 224.

Hunt, R. R. (1995). The subtlety of distinctiveness: What von Restorff really did. Psychonomic Bulletin & Review, 2(1), 105–112.

Jisha, V. G., & Excelce, A. J. (2024). Von Restorff Effect—A Psychological Impact of the Customers. In Harnessing AI, Machine Learning, and IoT for Intelligent Business: Volume 1 (pp. 765-773). Cham: Springer Nature Switzerland.

Lisińska-Kuśnierz, M. (2017). The value of brand image and design in seasonal packaging. Studia Oeconomica Posnaniensia, 5(7), 177-189.

Schmidt, S. R. (1991). Can we have a distinctive theory of memory? Memory & Cognition, 19(6), 523–542.

Kafkas, A., & Montaldi, D. (2018). How do memory systems detect and respond to novelty?. Neuroscience letters, 680, 60-68.

Quent, J. A., Henson, R. N., & Greve, A. (2021). A predictive account of how novelty influences declarative memory.

Neurobiology of Learning and Memory, 179, 107382.

Thiyagarajan, G. & Y. Swathi (2025, March). Temporal Dynamics of Consumer Engagement in E-Commerce. In 2025 International Conference on Computing for Sustainability and Intelligent Future (COMP-SIF) (pp. 16). IEEE. von Restorff, H. (1933). Über die Wirkung von Bereichsbildungen im Spurenfeld. Psychologische Forschung, 18(1), 299–342.

Business Example: In the retail industry, the von Restorff effect plays a critical role in product promotion. A striking example is Coca-Cola’s limited-edition holiday packaging, such as its distinctive polar bear designs. These unique visuals diverge from regular branding, attracting consumer attention and boosting seasonal sales (e.g., LisińskaKuśnierz, 2017). Similarly, luxury brands often use unconventional materials or minimalist designs to create a memorable packaging experience that distinguishes their products in 111

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VERBATIM EFFECT Verbatim effect refers to the tendency to remember the gist of an experience or a message, while the exact details are forgotten over time. "but the main thing is whether the client likes it. What were their specific requests?

What do they want?"

"They insisted everything be on one page, with space for a blog, and a feature for clients to book consultations through the website," Ellie explained.

"Got it," Rooney nodded. "Did they mention any specific details? Like, no red colors, or no illustrated elements in the design, only photos?"

Ellie paused, a bit worried, "You're right. They did mention some specifics, but I can't remember the details."

"Didn't you take notes?" Rooney inquired.

"No... What should I do now?" Ellie was visibly anxious.

"Don't worry," Rooney tried to reassure her, realizing he might have added to her stress.

"Was anyone else at the meeting with this company?" "Yes, my boss and his secretary," Ellie recalled after a moment.

"There you go," Rooney said encouragingly.

"Maybe the secretary took notes?"

"You're right," Ellie perked up, "she did take notes. I'll call her right now."

"Great idea! Don't worry," Rooney comforted her, "everything will be fine." "Next time, I'll make sure to record all the details. I remember their general requests, but not the specifics," Ellie said as she picked up the phone to find the secretary's number.

"How do you like the website?" Ellie asked. She had been interning at an IT company for two weeks and was proud to have been trusted with designing a website for a client, a small consulting firm. She had enthusiastically worked on the website prototype for three days.

"I like it," said Rooney, looking at Ellie's work, 112

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phrase. Similarly, employee training programs focus on key takeaways rather than exhaustive manuals, aligning with how memory naturally functions.

About: The verbatim effect describes the tendency for individuals to recall the general meaning or gist of information rather than its exact wording.

Originally explored in memory research, it has roots in the script theory proposed by Schank and Abelson (1977), which emphasized the importance of understanding the underlying meaning of events. Subsequent work by Kintsch and van Dijk (1978) advanced this understanding by distinguishing between surface-level representation (exact wording) and semantic processing (gist). Recent research supports these findings, highlighting the role of working memory and cognitive schemas in prioritizing semantic over verbatim details, especially in situations involving complex or lengthy material (Radvansky, 2012). This phenomenon is fundamental to understanding human memory and has far-reaching implications for education, communication, and decision-making.

Reproducibility: Studies consistently demonstrate that individuals better recall the gist of information than its verbatim details across a variety of contexts, including story recall, text comprehension, and eyewitness testimony (Brainerd and Reyna, 1990; Reyna and Brainerd, 1995). However, the effect is influenced by factors such as the complexity of the material, prior knowledge, and the passage of time since exposure (Radvansky and Zacks, 2014 and 2017).

Neuroimaging studies also provide evidence for differential activation of memory-related brain regions during verbatim versus gist recall (Abe et al., 2013). Current research also looks at verbatim memorization in large language models (e.g., Huang et al., 2024)

Trivia Example: An everyday example of the verbatim effect is seen in how people retell news stories. While most individuals cannot recall the exact phrasing of an article or broadcast, they often remember and share the main events or conclusions. For example, someone might summarize a political speech by focusing on its central themes, even if the precise language is forgotten. This reflects the natural tendency to prioritize meaning over detail in memory.

Selected References

Abe, N., Fujii, T., Suzuki, M., Ueno, A., Shigemune, Y., Mugikura, S., ... & Mori, E. (2013). Encoding-and retrieval-related brain activity underlying false recognition. Neuroscience Research, 76(4), 240-250.

Brainerd, C. J., & Reyna, V. F. (1990). Gist is the grist: Fuzzy-trace theory and the new intuitionism. Developmental Review, 10(1), 3–47.

Huang, J., Yang, D., & Potts, C. (2024). Demystifying verbatim memorization in large language models. arXiv preprint arXiv:2407.17817.

Kintsch, W., & van Dijk, T. A. (1978). Toward a model of text comprehension and production. Psychological Review, 85(5), 363–394.

Radvansky, G. A. (2012). Across the event horizon. Current Directions in Psychological Science, 21(4), 269–272.

Radvansky, G. A., & Zacks, J. M. (2014). Event cognition. Oxford University Press.

Radvansky, G. A., & Zacks, J. M. (2017). Event boundaries in memory and cognition. Current opinion in behavioral sciences, 17, 133-140.

Reyna, V. F., & Brainerd, C. J. (1995). Fuzzy-trace theory: An interim synthesis. Learning and Individual Differences, 7(1), 1–75. https://doi.org/10.1016/1041-6080(95)90031-4 Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. Erlbaum.

Business Example: In the corporate environment, the verbatim effect influences how messages are crafted for maximum retention. For instance, marketing campaigns often rely on concise slogans or core ideas rather than extensive detail, as audiences are more likely to remember the overarching message. Apple’s “Think Different” campaign exemplifies this strategy, distilling complex brand identity into a memorable, gist-oriented 113

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ZEIGARNIK EFFECT Zeigarnik effect is the tendency to remember uncompleted tasks better than completed ones. 'treasures' were kept in the attic, where cities and continents of bricks would emerge over time. Recently, his uncle had brought him a model of the Apollo Saturn V rocket, and Rooney had been assembling it for two days. "See?" he enthused, showing the parts laid out on the table.

"There are 1,900 pieces!

When it's done, it'll be almost a meter tall and 17 cm in diameter. Can you imagine?"

Ellie looked around. She wondered why Rooney was so excited about this rocket when there were more interesting things around.

In a corner of the attic, she spotted a Lego castle: "Hey, is that Hogwarts from Harry Potter? How many pieces does it have?" she asked.

"Oh, that old thing? I built it ages ago. I don't remember how many pieces. Does it matter? Look at this beauty - the Saturn V one of the most powerful rockets ever successfully flown. NASA used it to send people to the Moon, even to launch the Skylab space station!"

Ellie noticed a box from the castle on the attic floor. "Look, it says here the Lego Hogwarts model has 6,000 pieces. How long did it take you to assemble? You even have the character figurines," she said, picking up a Harry Potter figure.

"I told you, I don't remember how long it took.

But this Apollo Saturn V, I think I'll finish it this weekend!" Rooney replied, his enthusiasm undiminished.

"Hey, come check out my new Lego project," Rooney said with excitement. He had always loved Lego, building various creations since childhood. His Lego 114

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with progress bars. This design taps into the psychological discomfort of uncompleted tasks, motivating users to return and finish their lessons. Similarly, sales funnels often leave potential customers with unresolved calls to action, such as “Complete your purchase,” fostering a sense of urgency to finalize the transaction.

About: The Zeigarnik effect (e.g., Denmark, 2010) describes the psychological tendency to remember uncompleted tasks more vividly than completed ones. First identified by Bluma Zeigarnik in the 1920s under the mentorship of Kurt Lewin, the effect arose from observations of restaurant waiters who recalled active orders more accurately than fulfilled ones. Zeigarnik’s experiments confirmed that interrupted tasks create a state of cognitive tension, prompting better recall compared to completed tasks (Zeigarnik, 1927). This phenomenon has since been studied extensively in cognitive psychology, particularly in relation to memory, attention, and motivation. Contemporary research links the effect to goal-oriented behaviors and the cognitive mechanisms underlying task completion, suggesting that the incomplete state of a task activates mental resources that prioritize its recall (Elliot and Maier, 2014).

Reproducibility: The Zeigarnik effect has been consistently replicated across various studies and contexts.

Early experiments confirmed that interrupted tasks are recalled better than completed ones (Zeigarnik, 1927), while subsequent research supported these findings using memory recall paradigms (Baumeister and Heatherton, 1996).

Modern studies demonstrate that the strength of the effect depends on factors such as task complexity, individual differences in working memory, and motivation (e.g., MacLeod, 2020).

Despite its robust replicability, nuances exist; tasks perceived as unimportant or emotionally neutral show weaker effects. Ongoing research aims to disentangle these moderating factors, shedding light on the cognitive and emotional mechanisms behind task salience.

Trivia Example: The Zeigarnik effect explains why cliffhangers in TV shows are so effective. Viewers are left with unresolved storylines that linger in their minds, driving a strong desire to watch the next episode.

This psychological tactic keeps audiences engaged and ensures high retention rates for serialized content, demonstrating how unresolved tasks maintain cognitive salience.

Selected References

Baumeister, R. F., & Heatherton, T. F. (1996). Self-regulation failure: An overview. Psychological Inquiry, 7(1), 1–15.

Denmark, F. L. (2010). Zeigarnik effect. The Corsini encyclopedia of psychology, 1-1.

Elliot, A. J., & Maier, M. A. (2014). Color psychology: Effects of perceiving color on psychological functioning in humans.

Annual Review of Psychology, 65, 95–120.

MacLeod, C. M. (2020). Zeigarnik and von Restorff: The memory effects and the stories behind them. Memory & Cognition, 48, 1073-1088.

Zeigarnik, B. (1927). Das Behalten erledigter und unerledigter Handlungen. Psychologische Forschung, 9(1), 1–85.

Business Example: In marketing, the Zeigarnik effect is harnessed to improve engagement through interactive campaigns. For example, companies like Duolingo use gamification to encourage language learning by leaving lessons incomplete 115

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ANCHORING OR FOCALISM Anchoring or focalism is a bias that describes the common human tendency to rely too heavily on the first piece of information offered (the "anchor") when making decisions. their mutual friend Tom's birthday, and he had invited all his friends to the ice palace for skiing and snowboarding.

"Don't be mad," Ellie said. "My bike broke down, so I had to take a taxi." She was holding a large rectangular package.

"Is that your gift?" Rooney asked in surprise.

"Yes, it's a painting," Ellie replied proudly. "I don't understand why Tom had to invite us all the way out here. The taxi ride alone cost me 80 dollars."

"Eighty? Why so much?" Rooney exclaimed. "A taxi from your house here should cost at most 30 dollars!" "Thirty?"

"Yes, thirty. Did the driver even turn on the meter?" asked Rooney.

"No. But he initially asked for 120 dollars, and I bargained down to 80. I thought it was a good deal since it's a third less than his starting price!"

"You didn't note the driver’s license number or get a receipt, did you?" Rooney pondered.

"No," Ellie said, feeling dejected as she realized she had been tricked. "Next time, if you're unsure about taxi fares, call me. And always insist the driver uses the meter and gives you a receipt.

Anyway, we'll go home together later. For now, let's go wish Tom a happy birthday.

Have you ever snowboarded before?"

Rooney asked as he opened the door to the ice palace for Ellie.

"No! But I hope to learn today!" Ellie replied, her spirits lifting.

"I was starting to think you wouldn't come," Rooney said, having waited for Ellie for 40 minutes near the ice palace. They had agreed to meet at the entrance. Today was 116

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Understanding such tactics enables businesses to shape customer decisions effectively while maximizing perceived value.

About: Anchoring, or focalism (e.g., Bang, 2024), refers to a cognitive bias where individuals rely disproportionately on an initial piece of information (the “anchor”) when making judgments or decisions. First identified by Amos Tversky and Daniel Kahneman in the 1970s, their pioneering work revealed how arbitrary anchors could significantly influence estimations and choices (Tversky & Kahneman, 1974). For instance, when asked to estimate the number of countries in Africa, participants provided higher or lower estimates depending on a random number presented beforehand. Anchoring plays a critical role in decision-making under uncertainty, affecting diverse areas such as consumer behavior, legal judgments, and financial forecasting. Modern research delves into the mechanisms underlying this bias, exploring its relationship with cognitive load, motivation, and individual differences (Epley and Gilovich, 2001).

Reproducibility: The anchoring effect is one of the most robust and consistently replicated biases in psychology and behavioral economics. Experimental studies across domains such as courtroom decisions, consumer behavior, and negotiations demonstrate its pervasive influence (Furnham and Boo, 2011; Chapman and Johnson, 2002).

However, the effect’s magnitude can vary based on factors like individual expertise, cognitive capacity, and task relevance. For instance, experts in a specific domain may show reduced susceptibility to irrelevant anchors, though not immunity (Wegener et al., 2004). Neuroimaging studies suggest that anchoring involves activation in brain regions associated with numerical processing and decision-making, offering insights into its cognitive and neural foundations (e.g., Orr and Guthrie, 2005).

Trivia Example: The anchoring effect is evident in real estate pricing. A high initial listing price often leads buyers to make offers closer to that anchor, even if the property is overvalued. This is why sellers strategically set asking prices to create a perceived value baseline that influences potential buyers’ offers.

Selected References

Chapman, G. B., & Johnson, E. J. (2002). Incorporating the irrelevant: Anchors in judgments of belief and value.

Heuristics and biases: The psychology of intuitive judgment, 120, 153–184.

Epley, N., & Gilovich, T. (2001). Putting adjustment back in the anchoring and adjustment heuristic: Differential processing of self-generated and experimenter-provided anchors. Psychological Science, 12(5), 391–396.

Furnham, A., & Boo, H. C. (2011). A literature review of the anchoring effect. The Journal of Socio-Economics, 40(1), 35–42.

Orr, D., & Guthrie, C. (2005). Anchoring, information, expertise, and negotiation: New insights from meta-analysis. Ohio St. J. on Disp. Resol., 21, 597.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Wegener, D. T., Smoak, N. D., Petty, R. E., & Fabrigar, L. R. (2004).

Multiple routes to resisting attitude change. In Resistance and persuasion (pp. 13-38). Psychology Press.

Business Example: In advertising, anchoring is frequently used to guide consumer perceptions. For example, subscription services often present three pricing tiers, with the most expensive plan acting as an anchor. This positioning makes the mid-tier option seem more reasonable and appealing, even if it exceeds the consumer’s initial budget.

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ATTENTIONAL BIAS Attentional bias is the tendency for perception to be influenced by recurring thoughts, leading one to notice related things more frequently.

"Something sweet?" Rooney was exasperated.

"First, you asked me to help you avoid sweets; second, instead of thinking about sweets, tell me about interference."

Looking up at the ceiling, Ellie tried to recall what she had just been taught.

"Interference is... it's one of the manifestations of the wave nature of light.

It's related to the redistribution of light energy in space when... when..."

"When what?" Rooney interjected.

"I can't remember!" Ellie exclaimed. "I need a break. Look at those amazing cakes! And the pastries... Can I at least have that little croissant?"

"Which croissant?" Rooney felt like he was about to explode but took a deep breath and counted to ten. Calmer, he said, "I see the mistake now."

"What mistake?" Ellie asked.

"This mistake! Bringing you to a café was a bad idea. Everything here distracts you – cakes, macarons, chocolate, waffles, pastries, croissants! How can you concentrate? Your attention is all on the sweets. This won't work."

"I can't help it. I just want something sweet," Ellie sighed.

Rooney realized, "You don't want to study optics; you want sweets! No way.

Let's go."

"Where to?"

"Where? To the library! No food allowed there, and nothing will distract you from optics!"

Rooney said, taking Ellie's hand decisively.

"Got it?" Rooney had been sitting with Ellie in a café for several hours, explaining the basics of optics because she had a physics exam coming up. However, progress was slow as Ellie kept getting distracted. Initially patient, Rooney found the last 15 minutes especially challenging.

"I think so," Ellie shrugged. "Hey, can I buy a pastry? I really want something sweet."

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Similarly, supermarkets strategically place highmargin products at eye level, ensuring they capture attention more effectively than other items on the shelves.

About: Attentional bias is the tendency for individuals’ attention to be disproportionately influenced by their emotional states, recurring thoughts, or goals. Originating from cognitive psychology research in the late 20th century, early work by Michael W. Eysenck (1992) highlighted how anxiety and mood disorders can skew attentional processes. Experimental paradigms such as the dot-probe task and the emotional Stroop task have since become critical tools for studying attentional bias. These methods revealed how emotionally salient or personally relevant stimuli capture attention more effectively than neutral stimuli. More recent research has extended these findings to areas such as addiction, decision-making, and social interactions, emphasizing attentional bias as a key mechanism underlying various cognitive and behavioral patterns (Yiend, 2010).

Reproducibility: Attentional bias has been robustly replicated across diverse contexts and populations. Early studies, such as MacLeod, Mathews, and Tata (1986), demonstrated how anxious individuals show heightened attention to threatening stimuli, a finding that has since been reproduced using various methodologies. Contemporary research using neuroimaging highlights the activation of brain regions like the amygdala and prefrontal cortex in processing emotionally salient stimuli (Cisler and Koster, 2010).

However, the strength and direction of attentional bias are influenced by factors such as individual differences (e.g., anxiety levels or goals) and the salience of stimuli. Ongoing research focuses on refining experimental paradigms and understanding the interplay between attentional bias and other cognitive mechanisms (e.g., Yuan et al., 2025).

Trivia Example: Attentional bias is apparent when people focus on specific stimuli aligned with their interests or concerns. For instance, a person trying to eat healthily might frequently notice advertisements for fast food, highlighting how their goal creates a bias in their attention to certain cues.

Selected References

Cisler, J. M., & Koster, E. H. W. (2010).Mechanisms of attentional biases towards threat in anxiety disorders: An integrative review. Clinical Psychology Review, 30(2), 203–216.

Eysenck, M. W. (1992). Anxiety: The cognitive perspective.

Lawrence Erlbaum Associates.

MacLeod, C., Mathews, A., & Tata, P. (1986). Attentional bias in emotional disorders. Journal of Abnormal Psychology, 95(1), 15–20.

Yiend, J. (2010). The effects of emotion on attention: A review of attentional processing of emotional information.

Cognition and Emotion, 24(1), 3– 47.

Yuan, J., Chen, Y., Yuan, X., Zhang, Y., Wang, Y., & Liu, Z. (2025).

Attentional bias in older adults with non-clinical depression: an eye-tracking study. Experimental Aging Research, 51(2), 220-231.

Business Example: Marketers frequently exploit attentional bias to enhance product visibility. For example, online retail platforms use personalized recommendations and targeted ads based on a user’s browsing history. These tailored suggestions align with the user’s interests, leveraging attentional bias to increase engagement and likelihood of purchase.

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FOCUSING EFFECT Focusing effect occurs when people place too much importance on one aspect of an event, potentially leading to an error in accurately predicting the utility of a future outcome.

"What's that on your head?" Rooney asked, looking at Ellie. "What do you mean?" Ellie replied.

"That thing on your head?" Rooney pointed to the enormous structure atop Ellie's head, resembling a crown made of bright flowers. "It's my 'lucky' headband," Ellie declared seriously. "What?"

"My 'lucky headband'!" she repeated. "Don't laugh. Last time I wore it, I got the highest score on my physics presentation. And I have an important test tomorrow!"

"You didn't get the highest score because of the headband, but because you were wellprepared!" Rooney laughed.

"You don't understand. This headband brings me luck."

"Alright, if it brings luck, then so be it. If you feel more comfortable in it, then I understand. But honestly, it doesn’t look very comfortable to me!" Rooney said.

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influence consumer purchasing decisions.

About: The focusing effect, also known as the focusing illusion, is a cognitive bias where individuals disproportionately emphasize specific aspects of a situation while neglecting others. Introduced

by Daniel Kahneman and Amos Tversky in the 1970s, this bias highlights the tendency to overvalue certain details, often distorting overall judgment (Kahneman and Tversky, 1979). For instance, in evaluating happiness, people may focus solely on one factor, such as income, while undervaluing other contributors like relationships or health (Schkade and Kahneman, 1998). This phenomenon has been pivotal in understanding decision- making processes, particularly in psychology and behavioral economics, revealing how cognitive shortcuts can lead to suboptimal outcomes in both individual and collective decisions.

perception

and

drive

Reproducibility: The focusing effect is a well-documented and reliably replicated bias in psychological research.

Studies have consistently demonstrated its influence across diverse contexts, including financial decision-making, health evaluations, and subjective well-being assessments (Schkade and Kahneman, 1998; Wilson et al., 2000). The effect’s strength varies with factors like information salience, emotional context, and individual cognitive tendencies. For instance, people in heightened emotional states may exhibit stronger focusing biases, as their attention narrows to the most prominent stimuli. Ongoing research explores the neurological and contextual factors that modulate this bias, enhancing our understanding of its implications for decision-making and behavior (e.g., Cherubini et al., 2003).

Trivia Example: The focusing effect is evident in public discussions about work- life balance. People often focus on having more free time as a key to happiness, overlooking how they might use that time. Research shows that simply having leisure does not guarantee satisfaction unless it aligns with fulfilling activities (Kahneman et al., 2006).

Selected References

Cherubini, P., Mazzocco, K., & Rumiati, R. (2003). Rethinking the focusing effect in decision-making. Acta psychologica, 113(1), 67-81.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Kahneman, D., Krueger, A. B., Schkade, D., Schwarz, N., & Stone, A. A. (2006). Would you be happier if you were richer? A focusing illusion. Science, 312(5782), 1908–1910.

Schkade, D. A., & Kahneman, D. (1998). Does living in California make people happy? A focusing illusion in judgments of life satisfaction. Psychological Science, 9(5), 340–346.

Wilson, T. D., Wheatley, T., Meyers, J. M., Gilbert, D. T., & Axsom, D. (2000).

Focalism: A source of durability bias in affective forecasting.

Journal of Personality and Social Psychology, 78(5), 821– 836.

Business Example: In marketing, the focusing effect is frequently exploited to emphasize product features likely to capture consumer attention. For instance, smartphone advertisements often highlight camera quality, assuming it to be a decisive factor for buyers, while downplaying other aspects like battery life or durability. By drawing attention to a single, highly valued feature, companies can 121

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FREQUENCY ILLUSION OR BAADER-MEINHOF EFFECT Frequency illusion or Baader-Meinhof phenomenon: After noticing something for the first time, there is a tendency to notice it more often, leading someone to believe that it has an increased frequency of occurrence.

Rooney spotted Ellie from a distance, struggling with heavy bags.

"Let me help," he said, grabbing both bags by the handles. "You scared me," Ellie said, surprised to see Rooney. "What's in these heavy bags?" Rooney asked.

"They're cans and other food for the food bank," Ellie replied. "Why's that?" Rooney wondered.

"What do you mean 'why'? Firstly, many families are struggling with hunger, and there are plenty of homeless people in the city who have nothing to eat." "I've never noticed," Rooney admitted.

"How could you not? In the city center, you can find homeless people everywhere. Like the old man in front of the cinema. Haven't you ever seen him?"

"No," Rooney paused, thoughtful. "I never really thought about it."

"Just because you haven’t noticed homeless people doesn’t mean they aren’t there."

Later that evening, Rooney called Ellie: "I've been thinking – you're right, there are many homeless people in the city. I saw eight on my way back from practice today. They're literally everywhere!

What does the food bank accept? I want to help too."

"I'll send you a link," Ellie responded. "They have a full list on their website."

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occurs when someone decides to purchase a particular car model. After researching it, they suddenly seem to see that model everywhere on the road. The actual number of cars hasn’t changed, but their heightened awareness creates a perception of increased frequency.

About: The frequency illusion, or Baader-Meinhof phenomenon, occurs when an individual encounters a specific word, concept, or item and suddenly perceives it as appearing more frequently. While the term originated from a St. Paul Pioneer Press commenter in the 1990s, the psychological underpinnings relate to selective attention and confirmation bias. The term “Baader-Meinhof effect” originated from a curious anecdote involving a user on the St. Paul Pioneer Press online discussion board in the 1990s. The commenter shared their experience of hearing the name “Baader-Meinhof” — referring to a German left-wing terrorist group active in the 1970s — twice within a short span of time, despite never having encountered the term before. They described the strange coincidence of repeatedly encountering this previously unfamiliar term, prompting a discussion among other users. This phenomenon of suddenly noticing something everywhere after encountering it for the first time resonated with many, leading to the coining of the term “Baader-Meinhof effect” on that forum. While the name reflects the original anecdote, the phenomenon itself has little to do with the group and is more accurately described in psychology as the frequency illusion, tied to cognitive processes like selective attention and confirmation bias. After noticing a novel stimulus, people tend to pay more attention to instances involving it, reinforcing the illusion of increased frequency. For example, encountering an unfamiliar term like “confirmation bias” might lead to heightened recognition of its presence in articles, conversations, or media. The phenomenon is particularly relevant in understanding how perception can be shaped by attentional shifts and cognitive biases, influencing decision-making and awareness in everyday life (Chabris and Simons, 2010).

Business Example: In advertising, the frequency illusion is used to enhance brand recall. For instance, after seeing an online ad for a smartwatch, consumers may begin to notice similar ads across platforms or spot the product in stores. This illusion can reinforce the perception that the product is ubiquitous and in high demand, subtly influencing purchase decisions. Brands also use retargeting strategies to intensify this effect, increasing perceived relevance and visibility.

Reproducibility: The frequency illusion has been widely replicated in psychological research, particularly in studies examining selective attention and memory.

Experiments show that individuals disproportionately notice and recall stimuli aligned with recent exposures, often leading to an overestimation of their prevalence (Sloman et al., 2003; Chabris and Simons, 2011). Research in marketing and linguistics demonstrates its applicability, such as in heightened awareness of newly learned words or frequently advertised products. However, factors like emotional salience, distinctiveness, and the individual’s cognitive focus can influence the intensity of the illusion. Ongoing studies aim to deepen our understanding of how attentional shifts create this effect and its implications for cognition and consumer behavior.

Selected References

Chabris, C., & Simons, D. (2011). The invisible gorilla: How our intuitions deceive us. Harmony.

Sloman, S. A., Over, D., Slovak, L., & Stibel, J. M. (2003). Frequency illusions and other fallacies. Organizational behavior and human decision processes, 91(2), 296-309.

Trivia Example: A common experience of the frequency illusion 123

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SELECTION BIAS Selection bias refers to the bias introduced by the selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analyzed.

"What do you think?" Rooney had been rehearsing for 40 minutes. He was preparing for a presentation to the girls at a physics and mathematics lyceum about the robotics club he was part of, focusing on automation and the use of robots in various fields.

"It won't work," Ellie said seriously. "Why not?"

"Your examples aren't suitable," Ellie continued confidently. "They're all about fashion or cosmetics."

"What's wrong with that? Girls are interested in these topics. I surveyed all my female friends, and they chose these themes."

"Rooney, it's not about what girls are interested in generally or those you know. You need to engage the girls studying at the lyceum.

So, you need to discard these stereotypes and assumptions from your conversations.

Why not talk about Formula 1 or rocket science instead?"

"So, I should drop fashion completely?" Rooney looked perplexed.

"Let's do this: include one example about fashion, but the rest should focus on what specifically interests these girls. Why not ask their teachers for insights?"

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those with strong opinions, excluding others who are less motivated to respond. This can result in an overly optimistic or pessimistic assessment of customer satisfaction, leading to flawed strategies. A case study of employee feedback systems revealed similar challenges, where voluntary surveys disproportionately reflected views of dissatisfied employees (Baruch and Holtom, 2008). To address this, businesses often employ stratified random sampling or incentives to ensure broader participation.

About: Selection bias occurs when the sample used in a study is not representative of the population being analyzed, leading to results that may not be generalizable. This phenomenon is recognized across disciplines, including psychology, epidemiology, and statistics. It became prominent in the mid-20th century, especially after researchers emphasized the need for sample representativeness to ensure valid and reliable conclusions. Selection bias can arise from several sources, such as non-random sampling, participant self- selection, or exclusion criteria that systematically omit certain groups. For example, studies that recruit participants from urban settings may inadvertently exclude rural populations, limiting the generalizability of their findings. In psychology, selection bias is particularly significant when interpreting clinical trial outcomes or survey data, as these often depend on participant availability and willingness to participate.

Reproducibility: Selection bias has been extensively studied, with its impact on research validity widely acknowledged. Classic studies such as Berkson’s (1946) work on hospital records and Heckman’s (1979) model of sample selection highlighted how biases distort inferences. Replicability is challenging because selection bias is contextdependent; it manifests differently across fields, from clinical trials to market research. For example, trials with rigid inclusion criteria often fail to represent real-world populations (Korn et al., 2013). Strategies to mitigate selection bias include random sampling, oversampling underrepresented groups, and statistical corrections such as inverse probability weighting. These methods have been rigorously tested, although their effectiveness varies across settings.

Trivia Example: One everyday example of selection bias is seen in online reviews. Typically, individuals with extreme experiences—either very positive or very negative—are more likely to leave reviews than those with neutral opinions. Consequently, the ratings of a product or service may not accurately reflect the average customer experience.

This phenomenon was demonstrated in a study on Yelp reviews, which found that extreme ratings tend to dominate, skewing perceptions (Luca and Zervas, 2016).

This issue highlights the importance of considering bias when interpreting aggregated review data.

Selected References

Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational research. Human relations, 61(8), 1139-1160.

Berkson, J. (1946). Limitations of the application of fourfold table analysis to hospital data. Biometrics Bulletin, 2(3), 47-53.

Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica: Journal of the Econometric Society, 47(1), 153–161.

Korn, E. L., Freidlin, B., Abrams, J. S., & Halabi, S. (2012). Design issues in randomized phase II/III trials. Journal of Clinical Oncology, 30(6), 667-671.

Luca, M., & Zervas, G. (2016). Fake it till you make it: Reputation, competition, and Yelp review fraud. Management science, 62(12), 3412-3427.

Business Example: Selection bias significantly affects market research and business decision-making. For instance, a company conducting a customer satisfaction survey may inadvertently gather data only from highly engaged customers or 125

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PART 3 JUDGEMENT

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EVERYTHING IS RELATIVE

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DURATION NEGLECT Duration neglect is the disregard of the duration of an episode in determining its value. It is often observed in people's retrospective evaluation of painful or pleasant experiences.

"It's awesome that we're out skiing! I haven't been to a ski resort in ages," Rooney said, gripping his brand-new snowboard and adjusting his goggles.

"Well, not a hundred years," Ellie corrected, checking her boots and skis.

"You've only been away for two years. And for a good reason!" "So, shall we tackle 'Devil's Descent'?"

"You never learn from experience, do you?" Ellie grumbled. "Remember how you fell there two years ago? You broke your leg and couldn't do anything for four months."

"No way! Four months? You must be mixing things up!"

"Can't believe you've forgotten. You couldn't play tennis - missed competitions and everything…"

"What? Seriously? Four months? I remember falling, sure, and recovering. I went straight back to training and even won the tennis club championship. I remember that. But I thought my leg healed in like six weeks."

"I'm certain it was four months. Even if it was six weeks, we're still not going on 'Devil's Descent'. Let's start with this trail. See? It's safer."

"Oh, you don't understand skiing at all! Fine, let's start with your 'safe' descent.

Let's head to the lift.

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displays. Even if visitors endure long wait times, their overall memory of the experience is shaped more by these standout moments and how their visit ends, aligning with findings from Fredrickson and Kahneman (1993).

About: Duration neglect is a cognitive bias in which individuals emphasize the quality of specific moments in an experience—particularly its peak (most intense) and end—while largely disregarding the experience’s overall duration.

First articulated by Kahneman et al. (1993), this phenomenon highlights how people recall past experiences based on selective emotional highs or lows, rather than a comprehensive evaluation of time. Duration neglect has been studied in healthcare, leisure activities, and consumer behavior, where impactful moments outweigh longer, less intense durations in shaping memory and decisions (Fredrickson and Kahneman, 1993; Redelmeier and Kahneman, 1996).

Reproducibility: Duration neglect has been robustly replicated across diverse domains. In Kahneman et al.’s (1993) cold-water immersion studies, participants consistently rated a longer but less painful experience more favorably than a shorter, equally painful one due to differences in peak and end moments. Healthcare studies, such as those

by Redelmeier and Kahneman (1996), confirm the same bias: patients’ retrospective evaluations depend more on the intensity and quality of peak and end experiences rather than total procedure duration. These findings have also been observed in consumer behavior and education, further underscoring the universal nature of this bias.

Trivia Example: A clear example of duration neglect occurs in healthcare settings. Patients undergoing medical procedures often recall their experience based on moments of peak pain and how the procedure ended, rather than its total length. For instance, a procedure that ends gently is often remembered more favorably than one of shorter duration but with a painful conclusion (Redelmeier and Kahneman, 1996).

Selected References

Fredrickson, B. L., & Kahneman, D. (1993). Duration neglect in retrospective evaluations of affective episodes. Journal of Personality and Social Psychology, 65(1), 45–55.

Kahneman, D., Fredrickson, B. L., Schreiber, C. A., & Redelmeier, D. A. (1993). When more pain is preferred to less: Adding a better end. Psychological Science, 4(6), 401–405.

Redelmeier, D. A., & Kahneman, D. (1996). Patients’ memories of painful medical treatments: Real-time and retrospective evaluations of two minimally invasive procedures. Pain, 66(1), 3–8.

Schreiber, C. A., & Kahneman, D. (2000). Determinants of the remembered utility of aversive sounds. Journal of Experimental Psychology: General, 129(1), 27–42.

Business Example: Duration neglect plays a pivotal role in customer experience strategies. Disney theme parks, for instance, craft memorable peak moments, such as exhilarating rides and dazzling parades, and ensure a positive conclusion with fireworks

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GAMBLER’S FALLACY Gambler’s fallacy is the belief that if something happens more frequently than normal during some period, it will happen less frequently in the future, or vice versa. card and get free groceries for a year. Cool, right? They gave me ten tickets today!"

"Firstly, there's always a limit, and secondly, I know you like contests and lotteries, but when will you understand that there's no such thing as a free lunch?" Rooney said.

"You're no fun, where's your sense of adventure?

I believe in my luck," Ellie said, taking a coin and starting to scratch off the top layer of a ticket. However, the first, second, third, fourth, fifth, and sixth tickets were all losers. When Ellie reached for the seventh ticket, Rooney remarked, "See? All these tickets are losers. You should've taken the vouchers. They would've been of some use." "On the contrary," Ellie countered, "six losing tickets mean the next one is more likely to be a winner! It's like life – a string of bad luck followed by sudden fortune."

"Not at all," Rooney replied. "It’s a game of probability. Among thousands, maybe millions of tickets, there's only one winner.

If the winning chance is one in a million, the fact that the first six tickets were losers doesn’t bring you any closer to winning.

It’s like flipping a coin and guessing heads or tails. The probability remains 50 percent each time, regardless of previous outcomes." "You'll see, the next ticket will be a winner," Ellie persisted.

But the seventh ticket was also a loser, and so were the remaining ones.

Disappointed, Ellie sighed, "I'm just unlucky."

"It's not about you. Let's go to a café – I'll treat you to ice cream," Rooney suggested.

"You're right. I may not be lucky in lotteries, but I've always been lucky with friends," Ellie smiled, tossing the stack of lottery tickets into the trash.

"What's this?" Rooney asked, noticing Ellie sitting at a table with a stack of cards.

"What does it look like?" she responded. "They're instant lottery tickets."

"I see they're tickets. Where did you get them? I hope you didn't buy them?" "I didn’t buy them," Ellie said, a bit offended. "I got them at the supermarket – they're having a promotion."

"What kind of promotion?"

"For every $10 spent, you get a lottery ticket. I could've chosen discount vouchers instead, but I thought the lottery tickets were better. Imagine, I could win an unlimited 132

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is imminent, leading them to buy prematurely.

Research by Chen (2022) shows that such biases can contribute to mispricing in financial markets, as traders act based on the fallacy rather than actual market fundamentals.

About: The Gambler’s Fallacy is a cognitive bias where individuals erroneously believe that future probabilities are influenced by past events, even when the events are independent. This fallacy often arises in situations involving random chance, such as gambling or lotteries. For example, people may think a coin is “due” to land on heads after several consecutive tails, despite each flip being an independent event. First identified in the late 19th century, this fallacy has been widely studied in behavioral economics and psychology due to its implications for decisionmaking under uncertainty (Tversky and Kahneman, 1971).

Reproducibility: The Gambler’s Fallacy has been consistently replicated in experimental studies. Tversky and Kahneman (1971) demonstrated that individuals often expect sequences of random events to “balance out” over short runs, a misconception known as the “law of small numbers.” Similarly, Croson and Sundali (2005) observed this bias in casino gamblers, who frequently adjust their bets based on perceived streaks, despite understanding the randomness of outcomes. The fallacy’s persistence across diverse contexts suggests its robustness as a cognitive bias and its relevance in real-world decision-making.

Trivia Example: A classic example of the Gambler’s Fallacy occurred in 1913 at the Monte Carlo Casino.

During a roulette game, the ball landed on black 26 times in a row, prompting players to bet heavily on red, assuming it was “overdue.” This belief led to massive losses when black continued to come up, demonstrating how the fallacy can lead to irrational decision-making.

Selected References

Chen, S. (2022). Information and dynamic trading with the Gambler’s fallacy. Mathematics and Financial Economics, 16(3), 399-446.

Croson, R., & Sundali, J. (2005). The Gambler’s Fallacy and the Hot Hand: Empirical data from casinos. Journal of Risk and Uncertainty, 30(3), 195–209.

Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105–110.

Sundali, J. A., & Croson, R. (2006). Biases in casino betting: The hot hand and the gambler’s fallacy. Judgment and Decision Making, 1(1), 1–12.

Business Example: The Gambler’s Fallacy affects financial decisionmaking. Investors often make poor decisions based on perceived “patterns” in stock market trends. For instance, after a series of declining stock prices, an investor might assume a reversal

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HYPERBOLIC DISCOUNTING Hyperbolic discounting refers to the tendency for people to increasingly choose a smaller-sooner reward over a larger-later reward as the delay occurs sooner rather than later in time week. You already missed Wednesday's session," Rooney realized Ellie wasn't keen on going to the gym.

"Oh, not today, please. I had physics yesterday and stayed up all night studying. I'm really tired. How about I get some rest today and definitely go next week? I just don't have the energy for the gym this week," Ellie said, yawning.

"No way – come on, get ready," Rooney was not swayed by her excuses. Ellie realized her trick hadn't worked and resigned herself to the workout. Half an hour later, they were on their way to the gym, Rooney carrying both his and Ellie's bags.

"Wait," Ellie suddenly said, stopping in front of a café window displaying tempting pastries, donuts, and chocolates. "Can I at least buy a chocolate? I really don't have the energy for the gym right now."

"Chocolate? How about I buy you a fruit salad instead?" Rooney remained firm.

"Let's do this: I'll buy a chocolate just for today as an exception, and next week I'll switch to fruit salads. I'll start living healthily, I swear!" Ellie tried one last time to negotiate.

"No chocolate. You made the same promise last week and ended up buying a 'last' chocolate then too. It's either a fruit salad or nothing.

We had an agreement. No more 'next week'..."

"Fine," Ellie finally conceded, "I'll take the fruit salad." "But only after the workout," Rooney insisted.

"Alright, alright, after the workout," Ellie agreed reluctantly and followed Rooney to the gym.

"Are you ready?" Rooney stood at the door in his workout clothes, holding a gym bag.

"Ready? For what?" asked Ellie.

"What do you mean 'for what'? It's Saturday. We agreed to go to the gym at least twice a 134

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upfront costs, even when the latter would be cheaper in the long run. A study by Laibson (1997) highlights how this bias contributes to undersaving for retirement, with individuals favoring current consumption over future financial security.

About: Hyperbolic discounting is a cognitive bias where individuals disproportionately prefer smaller, immediate rewards over larger, delayed ones, even when waiting would provide a greater benefit. This bias arises because people perceive the value of future rewards as diminishing disproportionately with time, a departure from the rational predictions of exponential discounting models. First systematically studied

by Ainslie (1975), hyperbolic discounting explains behaviors such as procrastination, impulsive purchases, and under-saving for retirement. It is a foundational concept in behavioral economics and psychology, with significant implications for understanding human decision-making over time.

Reproducibility: Hyperbolic discounting has been reliably reproduced across various studies and contexts.

Ainslie’s (1975) foundational experiments established the phenomenon, and subsequent research has confirmed its cross-cultural validity.

For instance, Frederick et al. (2002) demonstrated that people consistently show steep discounting for short-term delays but more rational decisionmaking for long-term horizons. Neural imaging studies, such as those by McClure et al. (2004), provide further evidence, showing distinct brain activity patterns when individuals choose between immediate and delayed rewards. The reproducibility of hyperbolic discounting makes it a cornerstone of research on intertemporal choice.

Trivia Example: A common example of hyperbolic discounting is choosing to eat a dessert now rather than adhering to a long-term diet goal. Although people often commit to eating healthier in the future, the immediate gratification of indulging overrides the delayed reward of improved health.

Research by Read and van Leeuwen (1998) demonstrates that individuals are more likely to select “tempting” foods when they anticipate consuming them immediately rather than later.

Selected References

Ainslie, G. (1975). Specious reward: A behavioral theory of impulsiveness and impulse control. Psychological Bulletin, 82(4), 463–496.

Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time discounting and time preference: A critical review.

Journal of Economic Literature, 40(2), 351–401.

Laibson, D. (1997). Golden eggs and hyperbolic discounting.

Quarterly Journal of Economics, 112(2), 443–478.

McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2004). Separate neural systems value immediate and delayed monetary rewards. Science, 306(5695), 503–507.

Read, D., & van Leeuwen, B. (1998). Predicting hunger: The effects of appetite and delay on choice. Organizational Behavior and Human Decision Processes, 76(2), 189–205.

Business Example: Hyperbolic discounting significantly affects financial decision- making and marketing. For example, credit card companies exploit this bias by offering rewards programs that encourage immediate spending despite long-term debt consequences. Similarly, subscription-based services capitalize on consumers’ tendency to prefer small monthly payments over larger 135

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LICENCING EFFECT The licensing effect is when people feel justified to act indulgently after doing something good.

Rooney looked around the gym café and spotted Ellie. She was sitting at the table. Right in front of her on a white plate was a large piece of cake. Rooney knew he would find her here.

“I hope you’re not planning to eat all that,” he said, sitting down next to her. “You’ve only just finished your circuit training class.”

“Exactly!” Ellie was annoyed. “That’s it, I’ve just finished it, so I definitely earned a piece of cake!”

“Hey, hang on a minute. Who said only two days ago, ‘I’m going to lead a healthy lifestyle’ and ‘no more sugar’? And, hmm, oh yes…

‘I’m starting a new life.’ I’m sorry, but I’m not going to let you have cake right after your gym session.” Rooney took the plate with the cake and put it on the neighboring table. “Let’s go! We’ll take a walk.”

“Oh no… my cake… Rooney! Can I at least have a milkshake?”

“No.” “Smoothie?”

“No.” “I deserve it!”

“No. You deserve better!” Rooney grabbed Ellie by the hand and dragged her towards the exit.

“All right then,” she said. “But in that case, I’m taking the elevator.”

“Are you kidding me? It’s the second floor! We’re taking the stairs.”

“No, you’re taking the stairs and I’m taking the elevator. I definitely earned it!”

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arrangements for one employee might later feel licensed to deny similar flexibility to others, believing their prior generosity absolves them of future bias. Likewise, employees who exceed performance targets may justify skipping minor ethical guidelines, such as misreporting time or resources. In both cases, prior “good” acts serve to rationalize decisions that deviate from ideal ethical standards (Merritt et al., 2010).

About: The licensing effect, also known as self-licensing or moral licensing, is a cognitive bias in which individuals who engage in a morally positive or virtuous act subsequently feel justified in behaving in ways that may contradict those standards. This psychological mechanism allows people to “balance out” their behavior, perceiving prior good deeds as credentials that reduce the moral cost of later indulgent or unethical actions (Merritt et al., 2010). Often unconscious, this bias influences decisions in domains such as health, consumption, and ethics, shaping how people rationalize inconsistencies in their behavior.

Reproducibility: The licensing effect has been widely replicated across experimental and real-world settings.

Studies by Khan and Dhar (2006) demonstrated that consumers who made virtuous choices (e.g., buying environmentally friendly products) were more likely to later indulge in morally questionable purchases. Merritt, Effron, and Monin (2010) further showed that people who established their moral identity were more likely to engage in biased or indulgent behavior later on. These findings have been confirmed in domains ranging from consumer behavior to ethical leadership, highlighting the reliability and broad applicability of the effect.

Trivia Example: An everyday example of the licensing effect is seen in fitness behavior. A person who completes a challenging workout may feel entitled to reward themselves with high-calorie food shortly afterward. Although the initial action aligns with health goals, the follow-up indulgence is often rationalized as “earned,” even if it undermines overall progress. This reflects how prior effort can serve as moral justification for behavior that would typically be seen as counterproductive (Khan and Dhar, 2006).

Selected References

Khan, U., & Dhar, R. (2006). Licensing effect in consumer choice.

Journal of Marketing Research, 43(2), 259–266.

Merritt, A. C., Effron, D. A., & Monin, B. (2010). Moral selflicensing: When being good frees us to be bad. Social and Personality Psychology Compass, 4(5), 344–357.

Business Example: The licensing effect can influence managerial decisions and workplace dynamics. For instance, a supervisor who approves flexible working

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MORAL CREDENTIAL EFFECT Moral credential effect occurs when a person's track record of non-prejudice increases subsequent prejudice because they believe they have earned moral credentials as a non- prejudiced person "Are you seriously planning to go hiking in the mountains tomorrow?" Ellie asked in surprise.

"Yeah, why not?" Rooney nodded.

"But today is Sunday. A mountain hike with an overnight stay requires at least two days.

Are you planning to skip all your classes on Monday?"

"I'm not 'skipping'; I'm planning to ‘call in sick'," Rooney said with a sly smile.

"What do you mean 'sick'?" Ellie understood but couldn't believe what she was hearing.

"Literally. I'll be 'sick' tomorrow and not go anywhere."

"Brilliant idea!" Ellie said sarcastically.

"Especially since we have math tomorrow.

It's the first time I've heard of you missing math."

"You see, I've been thinking – all I do is solve problems and work part-time. I've never missed a single class or taken a sick day in my life. So, I thought, why can't I allow myself to skip just once? My mom and brother went to grandma's, and my uncle, who's visiting us – I told you about him – invited me to the mountains."

"That's foolish," Ellie remarked. "You'll need a doctor's note to skip a whole day.

But that's not the point. No one will believe you were sick for just one day." "Why would they believe others and not me?" Rooney pondered.

"Others are others, but you are you," Ellie said with a smile.

"You're right," Rooney admitted regretfully. "It's foolish. Goodbye, mountains. I'll go some other time.

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instance, such as hiring a minority candidate, may subsequently feel justified in making discriminatory decisions in later scenarios. This bias poses risks in workplaces where diversity efforts may unintentionally serve as credentials for justifying biased behaviors, underscoring the importance of ongoing accountability measures.

About: The moral credential effect is a cognitive bias where individuals who have previously acted in a morally praiseworthy manner feel licensed to act in ways that may contradict those moral standards. First introduced by Monin and Miller (2001), this phenomenon explains why people who establish themselves as “good” or “ethical” in one context often feel justified in taking actions that might otherwise be perceived as morally questionable. It reflects how prior good deeds can psychologically reduce the perceived need to maintain consistent ethical behavior, influencing decisions in areas such as discrimination, consumption, and workplace ethics.

Reproducibility: The moral credential effect has been consistently replicated in experimental and applied settings.

Monin and Miller’s (2001) seminal study demonstrated how participants who established their moral credentials were more likely to make prejudiced statements afterward. Subsequent research has validated these findings across diverse contexts, such as environmental behavior (Mazar and Zhong, 2010) and political decision-making (Effron et al., 2009). This replicability highlights its relevance in understanding moral licensing and ethical decision-making.

Trivia Example: A classic example of the moral credential effect is seen in environmental behavior. Someone who donates to environmental charities or participates in recycling initiatives might later feel justified in taking actions that harm the environment, such as driving a gas-guzzling car or taking frequent flights. Research shows that such prior “good” behaviors serve as moral credentials, reducing guilt associated with later decisions (Mazar & Zhong, 2010).

Selected References

Effron, D. A., Cameron, J. S., & Monin, B. (2009). Endorsing Obama licenses favoring Whites. Journal of Experimental Social Psychology, 45(3), 590– 593.

Mazar, N., & Zhong, C.-B. (2010). Do green products make us better people? Psychological Science, 21(4), 494–498.

Miller, D. T., & Effron, D. A. (2010). Psychological license: When it is needed and how it functions. Advances in Experimental Social Psychology, 43, 115– 155.

Monin, B., & Miller, D. T. (2001). Moral credentials and the expression of prejudice. Journal of Personality and Social Psychology, 81(1), 33–43.

Business Example: The moral credential effect is evident in hiring practices. Monin and Miller (2001) found that individuals who make inclusive decisions in one

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RECENCY ILLUSION Recency illusion is the belief or impression that a word or language usage is of recent origin when it is long-established. ”Hey, Ellie! Love your new haircut! It really suits you," Rooney winked playfully at Ellie.

"Firstly, it's not a haircut, I just straightened my hair with a flat iron. And secondly, I've been wearing it like this for four months – since my birthday!" Ellie said, visibly offended, pouting her lips.

"Seriously?" Rooney's eyes widened in surprise. "I just noticed!

Really? Four months? No way – you must be joking!"

"I'm not joking at all. And you know, you should pay attention to these things!" Ellie shook her head.

"I'm sorry," Rooney said guiltily. "I didn't mean to overlook it. I really didn't notice before. It does look great on you! Please don't be upset."

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Early prototypes, such as Ivan Sutherland’s headmounted display system, were developed over half a century ago (Sutherland, 1968). Businesses can capitalize on this bias by marketing products as novel, even when their underlying technologies have long histories.

About: The recency illusion is a cognitive bias where people mistakenly believe that a phenomenon, term, or trend is new when, in fact, it has existed for a considerable time. This illusion often arises due to an individual’s increased awareness of the phenomenon or its recent adoption in popular discourse. Zwicky (2005) first described the recency illusion in linguistic contexts, noting how speakers often attribute novelty to longestablished terms or structures. The illusion is prevalent in various fields, including technology and culture, where trends are perceived as recent despite their historical roots.

Reproducibility: The recency illusion has been validated in multiple contexts, particularly in linguistics and cultural studies. Zwicky (2005) observed that speakers often perceive linguistic innovations as recent due to their personal exposure, even when these changes have been documented for decades. Studies on consumer psychology also support the phenomenon, showing that perceived novelty is influenced by individual awareness rather than objective timelines (Pinker, 1994). This bias remains reproducible and relevant across disciplines, emphasizing its significance in shaping perceptions of change and innovation.

Trivia Example: A common linguistic example of the recency illusion involves “uptalk,” the rising intonation at the end of declarative sentences. While many believe it is a modern trend among younger speakers, research by Ladd (2008) shows that uptalk has been documented for decades in English-speaking communities. The perceived newness of this speech pattern stems from its increased prominence in media and linguistic discussions.

Selected References

Ladd, D. R. (2008). Intonational phonology (2nd ed.). Cambridge University Press.

Pinker, S. (1994). The language instinct: How the mind creates language. HarperCollins.

Sutherland, I. E. (1968). A head-mounted three-dimensional display. Proceedings of the Fall Joint Computer Conference, 33, 757–764.

Zwicky, A. M. (2005). Just between Dr. Language and I: Avoiding the recency illusion. Language Log.

Business Example: The recency illusion frequently impacts perceptions of technological innovation. Virtual reality (VR), for instance, is often regarded as a new technology, despite its origins in the 1960s.

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PROJECTION BIAS Projection bias is the tendency to project current preferences onto a future event, underestimating how much one's tastes or preferences may change over time.

"I'm hungry," Ellie said. "Let's order some food, my fridge is empty." They had been sitting together in the kitchen for two hours, working on physics assignments. Ellie felt her brain was about to overheat.

"Maybe we shouldn't?" Rooney replied. "You'll end up overeating again, then you'll complain about your figure."

"I won't overeat. I'll just order a little bit of food.

Aren't you going to eat anything?"

"I'm not hungry. How about this: you order for yourself, and I'll go out to the porch for some fresh air."

An hour later, there was a knock at the door.

"Can you open it, please?" Ellie asked. "I need to wash my hands, my pen leaked."

Rooney opened the door. A lively courier stood there with a huge bag and two boxes in his hands.

"Delivery!" he shouted.

"Are you sure all this is for us?" "Absolutely!" the courier yelled again.

After paying the delivery boy, Rooney spread out the food in the kitchen.

"How much food did you order?" he asked Ellie.

"There are two large pizzas, two pasta dishes, nuggets, fries, lasagna, and even ice cream. Are you sure you won't feel sick?"

"Oh," Ellie said, looking at the spread on the table.

"I was really hungry when I ordered. Maybe I got a bit carried away…"

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the facilities more often than they actually do.

Businesses that offer “future-proof” products or services often exploit this bias, encouraging consumers to commit to long-term plans based on unrealistic projections of their future behavior.

About: Projection bias is a cognitive bias in which individuals assume that their future preferences, tastes, or behaviors will closely mirror their current state. This bias often leads to errors in decision-making, as people fail to account for how their preferences or circumstances might change over time. First formally described by Loewenstein et al. (2003), projection bias explains why individuals overestimate the importance of their current emotions or needs in shaping future choices, often resulting in regret or suboptimal decisions. It has wide-ranging implications for fields such as behavioral economics, consumer psychology, and public policy.

Reproducibility: Projection bias has been extensively replicated in laboratory and field settings. Loewenstein et al.

(2003) demonstrated this bias in decisions involving consumption and utility, with participants consistently overestimating the relevance of their current preferences to future situations. Further studies, such as those by Gilbert and Wilson (2000), have shown how projection bias influences emotional forecasting, leading individuals to mispredict how they will feel about future events. This robust body of evidence confirms the replicability of projection bias across diverse contexts, including financial decision-making, health behavior, and consumer purchases.

Trivia Example: A classic example of projection bias is grocery shopping while hungry. Shoppers often purchase more food, especially high-calorie items, under the assumption that their current hunger will persist. Research by Read and van Leeuwen (1998) confirmed this phenomenon, showing that people make different food choices based on their immediate hunger level, even when the food is intended for later consumption.

Selected References

DellaVigna, S., & Malmendier, U. (2006). Paying not to go to the gym. American Economic Review, 96(3), 694–719.

Gilbert, D. T., & Wilson, T. D. (2000). Miswanting: Some problems in the forecasting of future affective states. Thinking & Reasoning, 5(4), 321– 344.

Loewenstein, G., O’Donoghue, T., & Rabin, M. (2003). Projection bias in predicting future utility. Quarterly Journal of Economics, 118(4), 1209– 1248.

Read, D., & van Leeuwen, B. (1998). Predicting hunger: The effects of appetite and delay on choice. Organizational Behavior and Human Decision Processes, 76(2), 189–205.

Business Example: Projection bias significantly affects product design and marketing. For instance, gym memberships often capitalize on people overestimating their future motivation to exercise. DellaVigna and Malmendier (2006) found that consumers frequently overpay for gym memberships because they anticipate using

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PRESENT BIAS Present bias is the tendency to overvalue immediate rewards at the expense of long-term intentions. ”Hey, Ellie!"

"Hi, Rooney. What’s up?" Ellie could tell from his voice over the phone that he was in a bad mood.

"Nothing special. Just had an argument with my mom." "About what?"

"Suppose you're offered $10 now or $15 in three days. What would you choose?" Rooney asked.

"Not this again!" Ellie groaned, not wanting to solve puzzles. "You and your riddles!"

"It's not a riddle, just a simple question. So, what's your choice?" "$10 now," Ellie replied, followed by silence on the other end.

"Okay," Rooney continued suddenly. "Now, suppose you're offered $10 in a year or $15 in a year and three days. What would you choose?" "$15 in a year and three days!"

"Why???" Rooney exclaimed. "My mom thinks the same, but it's irrational!"

"It's simple," Ellie explained. "I need money now, so it's better to take $10 immediately than wait. But if I have to wait anyway, I might as well wait a bit longer for a bit more.

Understand?"

"No! I don't get it!"

"Listen, I answered your question, okay? That's enough!"

"Alright," Rooney said. "I might never understand it, but thanks for listening!"

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subscription services, such as streaming platforms, capitalize on present bias by allowing customers to access benefits immediately, with payment deferred to a later date. Soman et al.

(2005) highlighted how these strategies appeal to consumers’ tendency to discount future costs in favor of immediate rewards.

About: Present bias is a cognitive bias in which individuals disproportionately prioritize immediate rewards over larger, delayed benefits, even when delaying would result in a better outcome. This bias explains why people often struggle with long-term planning and selfcontrol, leading to behaviors such as procrastination, impulsive spending, and undersaving for retirement. First extensively discussed

by Thaler (1981) in behavioral economics, present bias challenges the rational models of intertemporal choice proposed by traditional economics. It has since become a cornerstone concept in understanding human decisionmaking, particularly in contexts involving delayed gratification.

Reproducibility: Present bias has been consistently replicated across diverse experimental and real-world contexts. Thaler (1981) demonstrated the bias through experiments in which participants showed a clear preference for smaller, immediate rewards over larger, delayed ones. Subsequent studies, such as those by Laibson (1997), further established its universality, with individuals across cultures exhibiting this preference in financial, health, and educational decisions.

Neuroimaging studies, including McClure et al.

(2004), have provided biological evidence for present bias, revealing heightened activation in brain regions associated with immediate gratification when people face intertemporal choices.

Trivia Example: A common example of present bias is delaying exercise in favor of leisure activities. Even though individuals may value long-term health benefits, the immediate comfort of skipping a workout often takes precedence. Research by Milkman et al. (2011) shows that framing exercise as a source of immediate enjoyment, such as pairing workouts with entertaining activities like listening to audiobooks, can mitigate present bias and improve consistency in health-related behaviors.

Selected References

Laibson, D. (1997). Golden eggs and hyperbolic discounting.

Quarterly Journal of Economics, 112(2), 443–478.

McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2004). Separate neural systems value immediate and delayed monetary rewards. Science, 306(5695), 503–507.

Milkman, K. L., Minson, J. A., & Volpp, K. G. (2011). Holding the hunger games hostage at the gym: An evaluation of temptation bundling. Management Science, 60(2), 283– 299.

Soman, D., & Lam, V. M. (2005). The effects of prior spending on future spending decisions: The role of acquisition liabilities and mental accounting. Journal of Consumer Research, 32(1), 90–98.

Thaler, R. (1981). Some empirical evidence on dynamic inconsistency. Economics Letters, 8(3), 201–207.

Business Example: Present bias significantly impacts financial decision-making and marketing strategies. For instance, credit card companies exploit this bias by promoting “buy now, pay later” schemes, encouraging consumers to prioritize immediate gratification over long-term financial responsibility. Similarly, companies offering 145

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TIME-SAVING BIAS Time-saving bias is a tendency to underestimate the time that could be saved (or overestimate the time that could be lost) when increasing (or decreasing) speed. about it," Rooney explained.

"What's so terrible about that? Now you can get to her faster!"

"No, it's not that simple. Many people think increasing average car speeds from 70 to 110 km/h will save more time than increasing it from 30 to 40 km/h. But actually, the time saved in the second case is greater. Understand?"

"No, why?" Ellie asked, puzzled. "Isn't the first case faster by 40 km/h, and the second only by 10 km/h?"

"Look, suppose you travel 10 km at 30 km/h.

How long will it take?"

"Well, if I drive 30 km in an hour, then 10 km would take a third of that time, so 20 minutes," Ellie calculated.

"Right! Now, imagine traveling 10 km at 40 km/h."

"Then it would be four times faster, so 15 minutes!"

"Exactly. So, by increasing from 30 to 40 km/h, you save 5 minutes. Agreed?" "Yes." "Now, what if you travel 10 km at 70 km/h?

That's 60 divided by 7, about 8.5 minutes.

And at 110 km/h, it's 60 divided by 11, roughly 5.45 minutes. So, the difference is 3.05 minutes."

"So, in the first case, it's a 5-minute saving, but in the second, just over 3 minutes?" Ellie pondered.

"That's my point. The highway brings more harm than good. Construction is costly, time-saving is questionable, and it brings no benefit to the town as it's just a throughway between major cities. It will only mar the charm of the small town.

That's why grandma is worried."

"What can be done?"

"Not sure yet. The plan is already approved, so changes are unlikely. But the town's residents plan to protest," Rooney explained.

"Hi, what’s up?" Ellie asked, noticing Rooney deep in thought.

"I was talking to my grandma today. Can you believe the government is planning to build a new highway right through the center of her small town? She's really upset 146

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often focus on marginal gains in high-efficiency areas, even though larger time savings could be achieved by optimizing less efficient tasks. This misallocation of resources can lead to suboptimal outcomes in project management and operational planning.

About: Time-saving bias is a cognitive bias where individuals misjudge the time saved by increasing speed or efficiency. This bias often leads to errors in decision- making, particularly when evaluating improvements in transportation, productivity, or workflow.

People tend to overestimate time saved by small increases in speed when the original speed is low and underestimate time saved when the original speed is high (Svenson, 2008). This bias has significant implications for personal decisionmaking and policy-making, especially in contexts such as travel planning and workplace efficiency improvements.

Reproducibility: Time-saving bias has been consistently reproduced in experimental and applied settings.

Svenson (2008) conducted a series of experiments that demonstrated the persistence of this bias in judgments about driving speed and time savings. Subsequent research by Fuller et al.

(2009) confirmed the bias in real-world contexts, such as travel and workflow efficiency. Sussman and Olivola (2011) extended these findings to organizational decision- making, revealing how this bias influences resource allocation in businesses. These studies highlight the reproducibility and universality of the timesaving bias across different domains.

Trivia Example: A common example of the time-saving bias occurs in driving. Drivers often believe that increasing their speed from 20 to 30 mph saves as much time as increasing their speed from 60 to 70 mph over the same distance. Research shows that the actual time saved diminishes as speed increases, highlighting the non-linear nature of time savings (Fuller et al., 2009).

Selected References

Fuller, R., Tsimhoni, O., & Regev, S. (2009). The time-saving bias: Judgments, cognition, and decision-making in transportation and travel. Transportation Research Part F: Traffic Psychology and Behaviour, 12(5), 389–401.

Sussman, A. B., & Olivola, C. Y. (2011). Axe the tax: Taxes are disliked more than equivalent costs. Journal of Marketing Research, 48(SPL), S91– S101.

Svenson, O. (2008). Decisions among time-saving options: When intuition is strong and wrong. Acta Psychologica, 127(2), 501–509.

Business Example: Time-saving bias affects workplace productivity strategies. For instance, organizations may invest heavily in improving the efficiency of already fast tasks while neglecting slower, more time-consuming processes. A study by Sussman and Olivola (2011) found that decision-makers

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ATTRIBUTE SUBSTITUTION Attribute substitution occurs when a person has to make a judgment (of a target attribute) that is computationally complex and instead substitutes a more easily calculated heuristic attribute.

"Did you like the museum?" Ellie asked.

"It was fascinating," Rooney replied, pausing. "I particularly liked the optical illusions room. Remember the Shepard tables? I thought one was wider than the other, but you were spot on! You immediately realized they were the same size. I had never heard about it before. I was so sure they were different!"

"Actually, I didn't know either," Ellie admitted.

"I've been into drawing since I was a child, and all artists have an eye for such things."

"That's cool! Maybe I should start drawing too?"

Rooney said cheerfully.

"Oh no, please don't!" Ellie closed her eyes. "I still remember the birthday card you gave me when we were six. That's something best not repeated!"

"Come on, I was just kidding!"

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simpler attribute, such as the attractiveness of the packaging or the perceived brand reputation.

A study by Hagtvedt and Patrick (2008) showed that visually appealing packaging led consumers to rate products as higher quality, even when the actual product performance was identical. This substitution demonstrates how businesses can influence consumer perceptions by emphasizing easily accessible attributes.

About: Attribute substitution is a cognitive bias where individuals replace a complex judgment with an easier, more accessible attribute. This substitution often occurs unconsciously when people face difficult decisions, leading to judgments that are quicker but potentially less accurate. First conceptualized by Kahneman and Frederick (2002), attribute substitution explains why people often rely on heuristics or mental shortcuts when making decisions under uncertainty. For example, when asked to evaluate a person’s intelligence, one might substitute the judgment with an easier attribute, such as how articulate or confident the person seems.

Reproducibility: Attribute substitution has been extensively validated through experimental research.

Kahneman and Frederick (2002) documented the phenomenon across a range of contexts, from probability judgments to moral reasoning. The robustness of the Linda problem, replicated in diverse populations and settings, further confirms the generalizability of this bias (Tversky and Kahneman, 1983). Additionally, studies on consumer behavior, such as those by Hagtvedt and Patrick (2008), highlight how substitution effects persist in real-world decision-making, emphasizing the reliability of this bias across domains.

Trivia Example: A classic example of attribute substitution occurs in the “conjunction fallacy,” demonstrated in the famous Linda problem.

When participants were asked whether Linda, described as a politically active and outspoken individual, was more likely to be a bank teller or a bank teller active in the feminist movement, many chose the latter. This substitution of representativeness for logical probability illustrates how people replace complex probabilistic reasoning with simpler heuristic cues (Tversky and Kahneman, 1983).

References

Frederick, S., & Kahneman, D. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment (pp. 49– 81). Cambridge University Press.

Hagtvedt, H., & Patrick, V. M. (2008). Art and the brand: The role of visual art in enhancing brand extendibility. Journal of Consumer Research, 35(2), 212–225.

Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90(4), 293–315.

Business Example: Attribute substitution significantly impacts marketing and consumer behavior. For instance, when evaluating the quality of a product, consumers often substitute the judgment with a

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AUTOMATION BIAS Automation bias is a tendency to depend excessively on automated systems, which can lead to erroneous automated information overriding correct decisions.

"I don't get it," Rooney said, dismounting his bike and studying his phone's screen closely. "According to the navigator, the café should be right here," he said, looking around.

Ellie, who was already tired from cycling around the same area for 40 minutes, also got off her bike: "I'm telling you, this is an industrial zone, near the old airport – there are no cafés here.

Your navigator is just wrong."

"The navigator can't be wrong," Rooney insisted confidently. "The café must be around here somewhere. Maybe we got the address wrong?"

"Navigators are not always right," Ellie countered. "If we keep this up, we'll definitely miss Alice's birthday. Besides, this area doesn't seem safe, and it's going to get dark soon."

"But that's ridiculous," Rooney persisted. "The navigator should be accurate." "It should be, but it isn't!" Ellie shook her head.

"Here's what we'll do – let's go back to the fork near the gas station and call Alice. My phone's barely getting a signal here. We'll find out the exact directions or ask someone to pick us up by car."

"Alright. You're right," Rooney agreed, climbing back onto his bike. "Let's head to the gas station!"

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automation bias in electronic prescribing systems often results in medication errors, as clinicians overlook warnings or fail to notice system-generated mistakes. Similarly, in financial trading, over-reliance on automated systems can lead to significant losses if algorithms fail to account for sudden market shifts.

About: Automation bias refers to the tendency of individuals to over-rely on automated systems, often disregarding their own judgment or critical thinking. This bias leads to errors when automated systems provide incorrect recommendations or when people fail to notice issues the system overlooks. First identified in the context of aviation and healthcare, automation bias has gained increasing relevance with the proliferation of AI and machine learning technologies. Parasuraman and Riley (1997) defined automation bias as part of a broader spectrum of automation-related errors, which include both over-reliance and distrust of automation.

Reproducibility: Automation bias has been robustly demonstrated in both experimental and applied settings. Early work by Parasuraman and Riley (1997) established its theoretical foundations, and subsequent studies have confirmed the bias across domains such as healthcare, aviation, and consumer technology. Research by Lyell et al.

(2018) and Goddard et al. (2012) further supports the reproducibility of this phenomenon, showing consistent patterns of over-reliance on automation, even among highly trained professionals. These findings show the importance of designing systems that encourage critical engagement rather than blind trust.

Trivia Example: A striking example of automation bias is the reliance on GPS navigation systems. Drivers often follow GPS directions unquestioningly, even when the routes suggested are illogical or incorrect, such as leading them into closed roads or bodies of water. A study by Pettitt et al. (2005) highlighted how over-reliance on navigation systems contributes to dangerous driving decisions, especially in unfamiliar environments.

Selected References

Goddard, K., Roudsari, A., & Wyatt, J. C. (2012). Automation bias: A systematic review of frequency, effect mediators, and mitigators. Journal of the American Medical Informatics Association, 19(1), 121–127.

Lyell, D., Magrabi, F., & Coiera, E. (2018). The effect of cognitive load and task complexity on automation bias in electronic prescribing. Human Factors, 60(7), 1008–1021.

Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors, 39(2), 230–253 Pettitt, M., Burnett, G., & Stevens, A. (2005). Defining driver distraction. Proceedings of the 12th World Congress on Intelligent Transport Systems.

Business Example: Automation bias is particularly impactful in industries like finance and healthcare. For instance, in healthcare, reliance on automated diagnostic tools can lead to errors if practitioners accept system recommendations without verifying them. Lyell et al. (2018) found that

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BERKSON’S PARADOX Berkson’s Paradox is a statistical phenomenon that occurs when two independent variables are falsely found to be negatively correlated in a certain sample when they are actually not correlated "Why is it always like this: if a café has great pastries, the coffee is terrible? And vice versa: if the coffee is delicious, the pastries are inedible," Ellie mused, sitting at a café table. In front of her were two tempting cream puffs, but it was clear she didn’t like the coffee. The cup sat next to the pastries, almost full.

Rooney hung his backpack on the chair and sat down, saying: "Firstly, that's not entirely true. I'm sure there are plenty of places in the city where both the coffee and pastries are dreadful. We just don't go to those places, like most people. That's why you might think that if the coffee is bad, the pastries must be good, and vice versa."

"And secondly?"

"What do you mean 'secondly'?"

"You said 'firstly', so there should be a 'secondly', right?" Rooney laughed: "Oh, secondly, who was it again that promised not to eat pastries?"

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applicant pool, those with exceptional technical skills might appear to lack interpersonal skills, and vice versa, even though no true negative correlation exists. This bias occurs because only the candidates who excel in at least one area are selected for evaluation, creating an illusion of trade-offs where none may exist (Heckman, 1979).

About: Berkson’s paradox, also known as Berkson’s bias, is a statistical phenomenon that occurs when two independent variables appear to be negatively correlated due to a selection bias in the sampled population. Introduced by Joseph Berkson in 1946, this paradox often arises in casecontrol studies or other observational research where data are collected from a subpopulation rather than the general population. It has significant implications for research in fields such as epidemiology, social sciences, and economics, where selection bias can distort causal inferences.

Reproducibility: Berkson’s original study (1946) demonstrated the effect in medical case studies, and subsequent research in social sciences and economics has confirmed its broader applicability. For example, Heckman (1979) explored selection biases in labor economics, showing how sampling from specific subpopulations can distort statistical relationships. This paradox is particularly prevalent in datasets with restricted inclusion criteria, underscoring the importance of accounting for selection bias in statistical analysis.

Trivia Example: A common example of Berkson’s paradox occurs in hospital studies. Patients with two independent conditions, such as diabetes and heart disease, may appear to have a negative correlation in hospital records because individuals are more likely to be hospitalized when they have either condition, making cooccurrence seem less frequent than it actually is (Berkson, 1946). This bias arises because the sample is limited to hospitalized patients rather than the general population.

Selected References

Berkson, J. (1946). Limitations of the application of fourfold table analysis to hospital data. Biometrics Bulletin, 2(3), 47–53.

Elwert, F., & Winship, C. (2014). Endogenous selection bias: The problem of conditioning on a collider variable. Annual Review of Sociology, 40, 31– 53.

Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47(1), 153–161.

Pearl, J. (2009). Causal inference in statistics: An overview.

Statistics Surveys, 3, 96–146

Business Example: Berkson’s paradox can influence hiring decisions in corporate settings. For instance, when evaluating candidates from a highly competitive

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BASE RATE FALLACY OR BASE RATE NEGLECT Base rate fallacy or Base rate neglect is when people ignore the base rate (general prevalence) of an event and focus on specific information over general probabilities.

"What have you decided about tomorrow's theater trip?" Ellie asked. "I completely forgot. Maybe we shouldn't go?" Rooney suggested.

"That would be awkward. After all, Daniel will be playing the lead role. He invited me."

"Really?" Rooney coughed in surprise. "Daniel?

The lead role? In a theater? He's so shy, always blushing. I'd say he's more likely to become an accountant than an actor.

"Why specifically an accountant?"

"Well, okay, not an accountant, maybe an acupuncturist. He seems more like a needle therapist."

"Stop it! Do you seriously think there are more shy people among acupuncturists than actors? On the contrary, I read that most famous actors are very shy in real life!"

Rooney pondered: "Okay, let's say we have 1,000 acupuncturists in our city, and 80 percent of them are shy.

That's 800 shy acupuncturists. And suppose there are 10,000 actors, with 20 percent being shy. That's 2,000 shy actors.

2,000 is more than 800, so…"

"Enough with your math! I'm asking you one last time, will you come with me or not?"

"Alright, you've convinced me. Maybe there are more shy people among actors than acupuncturists. Let's go see the play tonight. Perhaps I'm wrong about Daniel, and he'll turn out to be a good actor. We'll see!"

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candidate over someone with consistent qualifications, assuming that confidence predicts success. Research by Highhouse (2008) reveals that organizations frequently rely on intuition instead of base rate data, leading to suboptimal hiring decisions. Similarly, in financial forecasting, traders may overreact to recent market events, ignoring historical trends and probabilities, resulting in poor investment strategies (Tetlock, 2006).

About: The base rate fallacy, or base rate neglect, occurs when people disregard or undervalue the base rate (general probability) of an event in favor of specific but less relevant information. Tversky and Kahneman (1974) described it as a systematic error in probabilistic reasoning, where vivid or detailed anecdotes outweigh statistical facts.

This bias often leads to flawed judgments, particularly in decisions involving uncertainty.

For example, when assessing the likelihood of someone belonging to a particular group, individuals often over-rely on stereotypes and ignore population statistics. The base rate fallacy is pervasive in fields like medical diagnostics, legal reasoning, and business forecasting, making it a critical area of study for understanding human decision-making errors (Koehler, 1996).

Reproducibility: Tversky and Kahneman’s (1974) foundational experiments demonstrated its prevalence in probabilistic reasoning, and their findings have been replicated across diverse cultural and professional contexts. Studies in medicine, such as those by Casscells et al. (1978), show that even experienced physicians often neglect base rates in interpreting diagnostic tests. Recent research highlights its persistence in legal decisionmaking, where jurors undervalue statistical evidence in favor of anecdotal testimony (Koehler and Shaviro, 1993).

Trivia Example: A classic illustration of the base rate fallacy is the “blue taxi problem.” In this scenario, participants are told about a city with 85% blue taxis and 15% green taxis, alongside a witness’s identification of a green taxi involved in an accident with 80% accuracy. Despite the overwhelming base rate of blue taxis, many people overestimate the likelihood that the green taxi caused the accident. The actual probability, derived using Bayes’ theorem, shows the green taxi is far less likely than assumed (Bar-Hillel, 1980). This example demonstrates how base rate neglect leads to intuitive but statistically incorrect conclusions.

Selected References

Bar-Hillel, M. (1980). The base-rate fallacy in probability judgments. Acta Psychologica, 44(3), 211–233.

Casscells, W., Schoenberger, A., & Grayboys, T. (1978).

Interpretation by physicians of clinical laboratory results.

New England Journal of Medicine, 299(18), 999–1001.

Highhouse, S. (2008). Stubborn reliance on intuition and subjectivity in employee selection. Industrial and Organizational Psychology, 1(3), 333–342.

Koehler, J. J. (1996). The base rate fallacy reconsidered: Descriptive, normative, and methodological challenges.

Behavioral and Brain Sciences, 19(1), 1–53.

Koehler, J. J., & Shaviro, H. (1993). Misuse of statistical evidence in criminal trials: The importance of statistical literacy.

Psychological Bulletin, 111(3), 489–502.

Tetlock, P. E. (2006). Expert political judgment: How good is it?

How can we know? Princeton University Press.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Business Example: Base rate neglect often undermines hiring practices and risk assessments. In recruitment, managers may focus on candidates’ recent performance or standout traits while ignoring historical success rates of similar profiles. For instance, a company might hire a charismatic

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CLUSTERING ILLUSION Clustering illusion is the tendency to see patterns in random events. This is a type of cognitive bias which refers to the human tendency to perceive patterns where none actually exist.

“Hey, how are you? Have you packed your suitcase yet?" Rooney was excited for Ellie.

She had won a contest and was preparing for a two-month internship in New York at the School of Visual Arts.

"Hi, Rooney," Ellie said thoughtfully, "yeah, I'm getting ready. I'm looking for accommodation."

"Didn't you say yesterday that you found a suitable and affordable hotel?" Rooney was surprised.

"It's not as simple as I thought. I checked the crime statistics in New York and found out that the hotel I wanted to stay in is located in one of the city's six most dangerous areas. I don't know what to do. I'm looking for other options. I don’t want to live somewhere unsafe... Imagine the kind of people that might be there…"

"You might be overthinking it. I recently did a project on crime statistics in New York, and I can tell you that the overall crime rates are randomly distributed across the city without any statistically significant difference in the number of crimes registered between districts."

"It's easy for you to talk about statistics. You're not the one who has to live there!"

"Listen, how about this – I'll come over now, and we can check it all together.

Maybe you shouldn’t give up on the hotel you already found?"

"Okay, come over," Ellie said, sounding more confident. "I promise not to make any 'rash decisions' before you get here."

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such misinterpretations contribute to speculative bubbles and market crashes. This bias also affects predictive analytics, where analysts might overweight temporary data clusters while ignoring broader, more relevant patterns. Companies leveraging machine learning systems must account for the clustering illusion to prevent misinformed business strategies based on random noise.

About: The clustering illusion is a cognitive bias where people perceive patterns or clusters in random data, incorrectly assuming that randomness should be evenly distributed. This bias stems from a natural tendency to seek order in chaos, leading to over-interpretation of random sequences. First explored systematically by Gilovich, Vallone, and Tversky (1985), the clustering illusion explains why individuals often see patterns in unrelated events, such as streaks in gambling or sports. It has significant implications for decision-making in contexts where randomness plays a key role, including finance, sports, and risk assessment.

Reproducibility: The clustering illusion has been extensively replicated in experimental and applied contexts.

Gilovich et al.’s (1985) foundational work on basketball performance has been consistently validated, though nuanced interpretations continue to emerge (Miller and Sanjurjo, 2018).

Tversky and Kahneman (1971) also demonstrated this bias in coin toss experiments, where participants erroneously perceived patterns in sequences of random events. Further studies in finance and sports, such as those by Barberis et al.

(1998), confirm its universality across domains, emphasizing its robustness as a cognitive bias.

Trivia Example: A classic example is the “hot hand” fallacy in basketball. Fans and players believe a player who scores several consecutive baskets is “on fire” and will likely continue scoring. However, Gilovich et al. (1985) found that such streaks align with statistical randomness. While the perception of streaks is compelling, actual shooting performance typically remains independent from prior outcomes. More recently, Miller and Sanjurjo (2018) revisited the hot hand phenomenon, offering evidence that certain conditions might amplify its perceived validity.

Selected References

Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307– 343.

Gilovich, T., Vallone, R., & Tversky, A. (1985). The hot hand in basketball: On the misperception of random sequences.

Cognitive Psychology, 17(3), 295–314.

Miller, J. B., & Sanjurjo, A. (2018). Surprised by the hot hand fallacy? A truth in the law of small numbers.

Econometrica, 86(6), 2019–2047.

Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105–110.

Business Example: The clustering illusion often misguides financial decisions. For instance, investors may interpret a short-term rally in stock prices as evidence of a trend, leading to overconfidence and risky investments. Barberis et al. (1998) showed that

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CONJUNCTION FALLACY Conjunction fallacy is a logical fallacy that occurs when it is assumed that specific conditions are more probable than a single general one.

"Hi," Rooney called, seeking advice from Ellie.

"You're the expert on gifts. I'm going to Mark's birthday and was wondering what to give him. I was thinking of getting him a voucher for extreme racing."

"Why an extreme racing voucher?" Ellie asked, knowing Mark well.

"Well, he's into rock climbing! Plus, I saw him at the karting track once. I think he likes extreme sports."

"That's just it, you saw him once. Why do you think he's into extreme activities?

Everyone always assumes that rock climbing is about thrill-seeking, but it's actually about planning and strategy. If you work in IT and do rock climbing, everyone thinks you're an adrenaline junkie first and IT specialist second. But it's the other way around! Mark joined me in rock climbing for four years because his parents made him.

He's not an adrenaline junkie at all. I don't know what he was doing at the karting track. Probably just went along with friends. He actually loves classical music and plays the violin. You should get him a ticket to a classical concert instead."

"Alright, I'll do that. Thanks for your help!"

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(1980) demonstrated how this bias influences over-detailed business forecasts, while recent research by Tetlock (2017) in geopolitical risk analysis shows how professionals often succumb to this bias under conditions of uncertainty, leading to unrealistic expectations about outcomes.

About: The conjunction fallacy is a cognitive bias in which individuals incorrectly judge the probability of two combined events as more likely than a single general event. This error violates the laws of probability, as the probability of a conjunction (A and B) can never exceed the probability of one of its components (A or B).

Tversky and Kahneman (1983) highlighted this fallacy in their foundational research, linking it to the use of representativeness heuristics. Instead of considering statistical principles, people evaluate how much a specific scenario aligns with stereotypes or mental prototypes. This bias impacts reasoning in domains such as healthcare, legal decision-making, and risk management, where probabilistic reasoning is critical (Hertwig et al., 2008).

Reproducibility: The conjunction fallacy has been extensively replicated across diverse settings and populations. Tversky and Kahneman’s (1983) foundational study was validated in multiple cultural contexts, demonstrating its universality. Hertwig et al. (2008) further explored the role of education and framing in mitigating the bias, finding that explicit training in probability reduces its prevalence but does not eliminate it. In healthcare settings, Reyna and Brainerd (2008) showed that medical professionals are not immune to this fallacy, especially when faced with diagnostically relevant but non-statistical cues. These findings highlight the reproducibility of the conjunction fallacy and its persistence even among trained decision-makers.

Trivia Example: The “Linda problem” is the quintessential example of the conjunction fallacy. Participants are introduced to Linda, who is described as intelligent, outspoken, and deeply concerned with social justice. When asked whether Linda is more likely to be a bank teller or a bank teller and active in the feminist movement, most choose the latter. Despite its plausibility, the conjunction of two events is mathematically less probable than a single event. Later studies, such as Fiedler (1988), replicated this finding and explored how varying the problem’s phrasing can influence responses, showing the robustness and context sensitivity of the fallacy.

Selected References

Fiedler, K. (1988). The dependence of the conjunction fallacy on subtle linguistic factors. Psychological Research, 50(2), 123–129.

Hertwig, R., Benz, B., & Krauss, S. (2008). The conjunction fallacy and the many meanings of and. Cognition, 108(3), 740– 753.

Koriat, A., Lichtenstein, S., & Fischhoff, B. (1980). Reasons for confidence. Journal of Experimental Psychology: Human Learning and Memory, 6(2), 107–118.

Reyna, V. F., & Brainerd, C. J. (2008). Numeracy, ratio bias, and denominator neglect in judgments of risk and probability. Learning and Individual Differences, 18(1), 89–107.

Tetlock, P. E. (2017). Expert political judgment: How good is it?

How can we know? Princeton University Press.

Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90(4), 293–315.

Business Example: In business decision-making, the conjunction fallacy is evident when executives evaluate complex scenarios. For example, managers may judge the likelihood of a project succeeding and meeting sustainability goals as higher than the project merely succeeding. This overconfidence in specific outcomes leads to errors in strategic planning and resource allocation. Koriat et al.

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DISTINCTION BIAS Distinction bias is the tendency to view two options as more dissimilar when evaluating them simultaneously than when evaluating them separately. the hotel with larger rooms is more expensive. I think we should book the pricier one. What do you think?"

Rooney peered at the screen: "You should approach this differently. Instead of looking at two options simultaneously and comparing them, think about the impression each hotel would make individually."

"How so?" Ellie inquired.

"Like this," Rooney turned the screen towards Ellie. "I bet you won't spend much time in the hotel. You'll likely be out walking, seeing sights, and enjoying the local cuisine in restaurants and cafes."

"True," Ellie acknowledged. "And how does that relate to choosing a hotel?" "Like this," Rooney explained. "The more spacious hotel is located far from the historical center. It'll take you over an hour to get there, while the smaller hotel is just a 15minute walk from the Colosseum. Think about it: a spacious room is nice, but you're going to Rome not to sit in a room."

"I see," Ellie brightened up. "So, you're saying we should consider how we'll spend our time and choose not by comparing options, but by finding the most suitable and convenient option for our plans. Exactly!

You're a genius! Thanks. Would you like some tea or coffee?"

"Hi," Ellie greeted as she opened the door. "Great you could come. My family is planning a week-long trip to Rome, and my dad asked me to find accommodation. But I'm totally confused about it."

"I'm not sure how much I can help, but I'll try," Rooney said, walking into the kitchen.

"Look at this," Ellie said, pointing to a website.

"This hotel is nice, but the rooms are small, and this one has bigger rooms. Of course, 160

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Businesses frequently encounter this bias in marketing, where comparative advertising exaggerates trivial distinctions to influence consumer behavior.

About: Distinction bias refers to the tendency to overemphasize differences between options when evaluating them simultaneously, compared to when they are assessed individually. This cognitive bias was first introduced by Hsee and Zhang (2004), who demonstrated that side-by-side comparisons often exaggerate minor distinctions, leading to suboptimal decisions. In real-world contexts, this bias can result in regret, dissatisfaction, and inefficient resource allocation. Distinction bias occurs because simultaneous evaluation forces people to focus on measurable attributes, even when those attributes are not meaningful in isolation (Hsee and Zhang, 2010).

Reproducibility: The distinction bias has been robustly validated across experimental and applied settings. Hsee and Zhang’s (2004) foundational experiments on consumer choice have been replicated in various domains, including education and healthcare, confirming the bias’s generalizability. For example, research in healthcare settings shows that patients often overemphasize quantitative differences in treatment outcomes when presented with side-by-side comparisons (Ubel et al., 2011). Subsequent studies have refined the understanding of distinction bias, showing that it diminishes when decisions are made based on experiential rather than analytical evaluations, but persists across cultures and contexts.

Trivia Example: A practical example of distinction bias is choosing a smartphone. When comparing two models, one with a slightly larger screen and another with marginally better battery life, buyers might overemphasize these differences during side-by-side evaluation. However, when using the phone daily, these differences are often negligible. Research by Noguchi and Hills (2016) shows that such bias can lead consumers to overpay for features they rarely use or value in real-world scenarios.

Selected References

Hsee, C. K., & Zhang, J. (2004). Distinction bias: Misestimation of the impact of differences on joint versus separate evaluations. Journal of Personality and Social Psychology, 86(5), 680–695.

Hsee, C. K., Loewenstein, G., Blount, S., & Bazerman, M. H. (2009).

Preference reversals between joint and separate evaluations of options: A review and theoretical analysis.

Psychological Bulletin, 125(5), 576–590.

Noguchi, T., & Hills, T. T. (2016). Experience versus analysis in judgment under uncertainty: The role of information search. Journal of Experimental Psychology: General, 145(3), 305–320.

Ubel, P. A., Scherr, K. A., & Fagerlin, A. (2011). Redefining quality in health care: Distinguishing useful distinctions from “distinction bias.” Journal of the American Medical Association, 306(7), 771–772.

Business Example: Distinction bias is particularly problematic in hiring decisions. For instance, recruiters evaluating two candidates side-by-side may overly focus on minor, quantifiable differences, such as the number of certifications, while overlooking less tangible but impactful qualities like cultural fit or emotional intelligence. Hsee et al. (2009) demonstrated that this bias often leads to overvaluing measurable attributes at the expense of broader, holistic considerations.

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DEFAULT EFFECT The tendency for individuals to accept pre-set options or defaults when faced with a choice.

"Why do you look so tired?" Ellie asked Rooney with curiosity.

"Tired? Oh, right – I just donated blood. Why are you laughing? I'm serious! As a donor. For charity," Rooney said, noticing his answer had amused her.

"You're serious? As a donor? For charity? That doesn't sound like you at all! Are you feeling okay?" Ellie knew Rooney was reluctant to participate in charitable activities and often had to drag him along to do something socially beneficial.

"Stop teasing, I'm serious!" Rooney retorted, getting annoyed.

"I don't understand how you decided to become a donor. It's like pulling teeth to get you involved in charity."

"Firstly, that's not true. I often help various organizations. And secondly, I didn't exactly choose to become a donor."

"What do you mean you didn't choose?"

"Well, when I signed up for the robotics club, their charter mandates monthly charitable activities. It's a kind of 'default' requirement... So I thought, why not donate blood? It's a good cause!"

"Now it makes sense. Alright, go get some rest.

You're practically falling asleep standing up," Ellie said, patting Rooney on the back.

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About: The default effect refers to the tendency for individuals to stick with a pre- selected or default option rather than actively choosing an alternative. This bias arises from a combination of decision inertia, loss aversion, and the perception that defaults represent a recommended or “safe” choice. Samuelson and Zeckhauser (1988) introduced the concept through experiments showing that people disproportionately favor default options in domains such as retirement planning and insurance. Defaults are powerful tools in influencing behavior, especially in situations involving complex or uncertain decisions (Johnson and Goldstein, 2003).

can use defaults ethically to nudge individuals toward beneficial choices, such as healthier eating or increased savings.

Trivia Example: A well-documented example of the default effect is seen in organ donation policies. Countries with opt-out systems, where individuals are automatically registered as donors unless they actively decline, exhibit significantly higher participation rates compared to opt-in systems.

Research by Johnson and Goldstein (2003) demonstrates that the default setting in organ donation policies is a key determinant of participation, emphasizing the role of defaults in shaping societal outcomes.

Dinner, I., Johnson, E. J., Goldstein, D. G., & Liu, K. (2011).

Partitioning default effects: Why people choose not to choose. Journal of Experimental Psychology: Applied, 17(4), 332–341.

Johnson, E. J., & Goldstein, D. G. (2003). Do defaults save lives?

Science, 302(5649),1338–1339.

Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk and Uncertainty, 1(1), 7– 59.

Sunstein, C. R., & Reisch, L. A. (2014). Automatically green: Behavioral economics and environmental protection.

Harvard Environmental Law Review, 38(1), 127–158.

Reproducibility: The default effect has been consistently replicated in a variety of experimental and realworld contexts. Samuelson and Zeckhauser (1988) first demonstrated its robustness in laboratory settings, while Johnson and Goldstein (2003) confirmed its impact on organ donation rates across countries. More recent studies, such as those by Dinner et al. (2011), explore how default options influence choices in fields like online retail and public policy.

Selected References

Business Example: The default effect has significant implications in consumer behavior and marketing. For instance, subscription services like Netflix or Amazon Prime use automatic renewal as a default setting, capitalizing on users’ inertia to maintain subscriptions. Similarly, energy providers offer “green energy” plans as default options, increasing the adoption of sustainable practices among consumers. Sunstein and Reisch (2014) highlighted how businesses and policymakers 163

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DECOY EFFECT A phenomenon in consumer choice where consumers will tend to have a specific change in preference between two options when also presented with a third option that is asymmetrically dominated.

"What's this?" Rooney looked disapprovingly at Ellie.

"What do you mean? It's popcorn, of course," Ellie smiled.

"See, this is why I didn't want to go to the movies. What about your diet? I suggested going to a concert because I knew you'd be tempted by popcorn or sweets at the movies. We had an agreement!" Rooney said, rising from his seat in the middle of the row. Meanwhile, several small groups of people entered the theater, and it began to fill up.

"Come on, don't grumble," Ellie said, sitting next to Rooney. "I only bought popcorn."

"Okay, but why so much popcorn? I would understand if you got a small size, but this is the largest they sell!"

"Well, I wanted a medium size, but there were only three options: small for $5, large for $10, and medium for $9. So, I thought: why buy the medium for $9 when you can get the large for $10? The price difference is so small. And you'll help me eat it, right?"

"Not a chance. You're on a diet, so no popcorn!

Give it to me. I'll throw it away before the movie starts."

Ellie looked down: "Alright, you're right – I'll stick to my plan. Here, you can throw it away," she said, handing the popcorn to Rooney.

As they spoke, the lights in the theater dimmed slightly, and the first commercial began to play on the screen.

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higher cost. Research by Huber et al. (1982) and further studies by Yang and Lynn (2014) have demonstrated how carefully designed decoy options can steer consumers toward desired choices, increasing profitability and influencing consumer satisfaction.

About: The decoy effect, also known as the asymmetric dominance effect, occurs when the introduction of a third, less desirable option (the “decoy”) changes preferences between two original choices. The decoy is strategically designed to make one of the other options appear more attractive, effectively nudging decision- making.

First systematically explored by Huber, Payne, and Puto (1982), the decoy effect demonstrates how irrelevant alternatives can influence perceived value and choice. It is widely used in marketing and pricing strategies to manipulate consumer behavior, highlighting the irrational components of decision-making.

Reproducibility: Huber et al. (1982) provided foundational evidence, showing that adding an asymmetrically dominated alternative influences preferences in predictable ways.

Simonson (1989) extended these findings to realworld scenarios, confirming the effect’s robustness in more complex decision-making tasks. Yang and Lynn (2014) demonstrated the decoy effect in digital marketplaces, emphasizing its applicability in modern e-commerce. The reproducibility of the decoy effect across experimental and applied contexts highlights its relevance in consumer decision-making.

Trivia Example: A well-known example of the decoy effect can be seen in cinema pricing. Imagine a movie theater offers two options: a small popcorn for $3 and a large one for $7. Adding a medium option for $6— close in price to the large but significantly smaller—makes the large option more appealing.

Research by Frederick et al. (2014) shows how such pricing schemes exploit the decoy effect to drive consumers toward higher-margin options.

Selected References

Frederick, S., Novemsky, N., Wang, J., Dhar, R., & Nowlis, S. (2014). Opportunity cost neglect. Journal of Consumer Research, 36(4), 553–561.

Huber, J., Payne, J. W., & Puto, C. (1982). Adding asymmetrically dominated alternatives: Violations of regularity and the similarity hypothesis. Journal of Consumer Research, 9(1), 90–98.

Simonson, I. (1989). Choice based on reasons: The case of attraction and compromise effects. Journal of Consumer Research, 16(2), 158–174.

Yang, S., & Lynn, M. (2014). More evidence challenging the robustness and usefulness of the attraction effect. Journal of Marketing Research, 51(4), 508–513.

Business Example: The decoy effect is commonly employed in subscription- based businesses. For instance, a software company might offer three plans: Basic at $50, Premium at $100, and Enterprise at $120.

The Premium plan serves as the decoy, making Enterprise seem like a better deal despite its

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FRAMING EFFECT People react to a particular choice in different ways depending on how it is presented; this can involve changing the context, the wording, or the focus of the options. know I don't watch TV," Rooney replied.

"What do you think about it? Why are some people against getting vaccinated?"

Ellie continued.

"It's hard to say," Rooney shrugged. "Some might have contraindications to the vaccine, others might be against vaccinations in general, or they could be influenced by how vaccination is portrayed in the news."

"How so?"

"Well, it depends on whether the information is presented positively or negatively.

Imagine there are two vaccination programs for 3,000 people: Program A and Program B. If I tell you that Program A will save 1,000 out of 3,000 people, and Program B has a 1/3 chance of saving all 3,000 and a 2/3 chance of saving none, which would you choose?"

"Probably the first one – Program A." "Okay, now imagine I present the same information negatively. Program A results in 2,000 deaths, while Program B has a 1/3 chance of no deaths and a 2/3 chance of 3,000 deaths. What would you choose then?"

"Program B," Ellie said, surprised.

"See, depending on whether the information is framed positively or negatively, people may perceive a particular vaccination program as harmful."

"That's interesting. I've never thought about it like that."

"Did you hear about yesterday's anti-COVID vaccination protest? There were clashes with the police," Ellie said, concerned. "You 166

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tends to be more effective than “Get $10 off,” even though the monetary value is identical. Similarly, businesses frame decisions to promote desired behaviors. For example, an energy company may label a program as “opting out of green energy” rather than “opting into green energy” to increase participation rates. Research by Levin et al. (1998) shows how framing influences consumer behavior, particularly in contexts involving risk and uncertainty, such as insurance and financial products.

About: The framing effect is a cognitive bias in which people’s decisions are influenced by how information is presented, rather than the information itself. First studied extensively by Tversky and Kahneman (1981), the framing effect demonstrates that people react differently to equivalent options depending on whether they are framed in terms of potential gains or losses.

This bias highlights the irrational aspects of decision-making, as individuals are swayed by the context and wording of choices rather than their substantive content. The framing effect has far-reaching implications in fields such as marketing, public policy, and healthcare.

Reproducibility: The framing effect has been extensively replicated in laboratory and real-world settings.

Tversky and Kahneman’s (1981) foundational experiments have been validated across cultures and contexts, demonstrating the universality of the bias. Levin et al. (1998) systematically reviewed the framing effect, confirming its robustness in decision-making tasks involving risk, value, and social preferences. More recent studies, such as those by Druckman (2001), extend the findings to political and policy contexts, showing that framing significantly impacts voting behavior and public opinion.

Trivia Example: A classic example of the framing effect is the “Asian disease problem” introduced by Tversky and Kahneman (1981). Participants were asked to choose between two programs to combat a hypothetical disease expected to kill 600 people.

When the outcomes were framed positively (e.g., “200 people will be saved”), most participants chose the safer option. However, when framed negatively (e.g., “400 people will die”), participants favored the riskier option. This experiment demonstrates how framing in terms of gains versus losses can drastically alter preferences.

Selected References

Druckman, J. N. (2001). The implications of framing effects for citizen competence. Political Behavior, 23(3), 225–256.

Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76(2), 149–188.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453–458.

Business Example: The framing effect is widely used in marketing.

For instance, a discount labeled as “Save $10”

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INFORMATION BIAS The tendency to seek information when it does not affect action; more information is not always better.

"I don't understand," Rooney was puzzled.

"Nothing seems to be working..." "In what way?" Ellie asked, peering into his computer.

"Well, I'm working on a project for my internship. We have a client, a delivery company, that asked us to optimize their drivers' routes for quicker deliveries and less fuel consumption. We equipped all the drivers with a new computerized routing system, which they reported they started using. We expected to see improvements: shorter delivery times and more deliveries completed. But it's not happening. I've been analyzing the data for two hours and see no improvements."

"Could it be that the data is inaccurate? I mean, maybe the drivers aren’t actually using the new system or not using it all the time?"

Ellie suggested thoughtfully.

Rooney brightened up: "That's it! You're a genius! How didn't I think of that? Indeed, the drivers could have claimed they were using the system but weren't really. We should have that data – a special sensor records when the system is on or off. I'll check it out. Thanks, Ellie!"

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can lead to decision paralysis and wasted resources. Similarly, in hiring, managers may conduct multiple rounds of interviews or request extensive references for candidates, even when they have sufficient data to make an informed choice.

About: Information bias refers to the tendency to seek or rely on additional information that does not affect decision outcomes, often under the belief that more information inherently leads to better decisions. This bias can lead to overanalyzing or overcomplicating decisions, detracting from efficiency and clarity. First explored by Baron et al. (1988), information bias is particularly relevant in areas such as healthcare, legal decisionmaking, and organizational management. It highlights the human inclination to value information acquisition over action, even when the information has limited or no practical utility.

Reproducibility: The information bias has been robustly validated in experimental and applied contexts. Baron et al. (1988) provided foundational evidence, demonstrating that people prioritize acquiring additional information even when it is irrelevant to outcomes. Subsequent studies in healthcare, such as those by Redelmeier et al. (2001), confirm the prevalence of this bias in medical decisionmaking. Recent research by Lurie et al. (2014) has shown that information bias persists in modern contexts, such as big data and artificial intelligence, where the abundance of information can overwhelm decision-makers.

These findings emphasize the reproducibility and enduring relevance of this bias across domains.

Trivia Example: A well-known example of information bias occurs in medical diagnostics. Doctors often order unnecessary tests to confirm a diagnosis, even when the additional information is unlikely to change the treatment plan. Baron et al. (1988) illustrated this with scenarios where participants consistently chose to gather irrelevant information, believing it would improve their decisions. This behavior often results in increased costs and delays without improving patient outcomes.

Selected References

Baron, J., Beattie, J., & Hershey, J. C. (1988). Heuristics and biases in diagnostic reasoning: II. Organizational Behavior and Human Decision Processes, 42(1), 88–110.

Lurie, N., Swaminathan, J. M., & Monahan, A. (2014). Is timely information always better? The effect of feedback frequency on decision making. Journal of Operations Management, 32(4), 219–231.

Redelmeier, D. A., Ferris, L. E., Tu, J. V., Hux, J. E., & Schull, M. J. (2001). Problems for clinical judgment: Introducing cognitive psychology as one more basic science. Canadian Medical Association Journal, 164(3), 358–360.

Russo, J. E., & Schoemaker, P. J. H. (1992). Managing overconfidence. Sloan Management Review, 33(2), 7–17.

Business Example: Information bias frequently impacts business decision- making, particularly in market research. For instance, a company launching a new product may invest heavily in consumer surveys and focus groups, even when the data will not influence the launch strategy. Research

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LESS-IS-BETTER EFFECT Occurs when people prefer a smaller set to a larger set judged separately but not jointly.

Ellie was already seated in the cinema.

Commercials had been playing on the screen for about five minutes when Rooney walked in and sat next to her, saying: "Hi, sorry I'm late. Want some ice cream?" He was holding a large cup almost filled to the brim with ice cream.

"Hi, no worries, the movie hasn't started yet. I already have ice cream," Ellie showed Rooney her waffle cone overflowing with ice cream. "Wait," she suddenly said, "where did you get so much ice cream? I thought I bought the largest portion available. But now I see I was wrong."

"Don't worry," Rooney whispered, "see, your waffle cone is small but overflowing, so it looks like there’s a lot. My paper cup is larger, but not filled to the top, making it seem like there's less. But actually, you have about 200 ml of ice cream, and I have almost 300 ml. When you look at your cone alone, it's hard to tell how much ice cream there is. But when you see both together, it's clear the cup has more."

"I never would have thought!" Ellie exclaimed, surprised.

"Alright," Rooney whispered, "let's split it'; I definitely can't eat all of this. I'll be right back – I’ll grab another empty cup and a spoon from the cafe."

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portions at premium prices. Research by Hsee and Zhang (2010) shows that consumers perceive smaller portions in high-end settings as more desirable than larger portions in casual settings.

Similarly, businesses offering “exclusive” products or services use this bias to justify higher prices for smaller quantities, relying on the perception of exclusivity and quality to enhance desirability.

About: The less-is-better effect is a cognitive bias where people evaluate a smaller quantity or lowervalue item more favorably when it is presented in isolation or in a different context, compared to a larger or higher-value item. First identified by Hsee (1998), this effect highlights the role of contextual framing in decision-making. For example, individuals may choose a smaller but higher-quality option over a larger but lowerquality one, even when the latter provides objectively more value. This phenomenon demonstrates how relative evaluation, rather than objective utility, often drives human preferences, influencing decisions in consumer behavior, charitable giving, and resource allocation.

Reproducibility: The less-is-better effect has been replicated in numerous experimental settings. Hsee’s (1998) original experiments demonstrated this bias in scenarios ranging from evaluating goods to moral decision-making. Subsequent research, such as studies by Hsee and Zhang (2010), confirmed the effect across cultures and domains, including consumer behavior and charitable giving. Experimental replication in real-world contexts, such as charitable campaigns and product evaluations, further highlights the robustness and universality of the effect. These findings emphasize the importance of contextual framing in decision- making.

Trivia Example: A famous example of the less-is-better effect involves charity donations. People are more likely to donate to save a single identifiable child than a larger, abstract group of children. Slovic (2007) explored this phenomenon, showing that emotional engagement is higher when the cause appears personal and specific, even though helping more individuals objectively provides greater impact. This effect demonstrates how emotional salience can outweigh logical reasoning in decision-making.

Selected References

Hsee, C. K. (1998). Less is better: When low-value options are valued more highly than high-value options. Journal of Behavioral Decision Making, 11(2), 107–121.

Hsee, C. K., & Zhang, J. (2010). General evaluability theory.

Perspectives on Psychological Science, 5(4), 343–355.

Slovic, P. (2007). “If I look at the mass I will never act”: Psychic numbing and genocide. Judgment and Decision Making, 2(2), 79–95.

Business Example: The less-is-better effect is commonly exploited in marketing. For instance, restaurants often promote smaller but elegantly presented

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NEGLECT OF PROBABILITY The tendency to completely disregard probability when making a decision under uncertainty.

"What are you working on?" Ellie asked, noticing Rooney intensely calculating something on his computer.

"Well," he replied, "I've been asked to program a dashboard for data analysis visualizations.

I need to figure out how much time it will take so I can calculate my fee properly. I've outlined all the tasks here. I think four weeks should be enough."

"Let me see," Ellie said, peering into Rooney's computer screen. "It looks like you've covered everything, but you haven’t considered potential delays. There's always a risk of not receiving all the data, or having to redo calculations if your initial analysis doesn't pan out. You've overlooked all these possibilities."

"You're right – I didn't account for the chance that something might go wrong. Can you help me?"

"Of course," Ellie replied confidently. "Let's go through the list together and figure out more realistic timelines."

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by emphasizing the inconvenience of such occurrences without highlighting their low probability. Research by Kunreuther et al. (2001) demonstrates how emotional appeals in risk communication can lead to overinvestment in insurance for unlikely events while underinvesting in coverage for more probable risks.

About: Neglect of probability refers to a cognitive bias where individuals fail to appropriately consider the likelihood of an event occurring, focusing instead on the emotional or qualitative aspects of the outcome. This bias is especially pronounced in decisions involving rare but high-impact events, such as natural disasters or lottery wins.

Tversky and Kahneman (1983) identified this phenomenon as a key aspect of decision-making under uncertainty, showing that people often overweight rare events or underweight likely ones, depending on the framing and context.

Neglect of probability has significant implications in fields like insurance, public health, and financial planning.

Reproducibility: Neglect of probability has been consistently replicated in experimental and applied research.

Tversky and Kahneman (1983) demonstrated its robustness in studies where participants systematically misjudged probabilities in scenarios involving risk and uncertainty.

Subsequent research, such as that by Rottenstreich and Hsee (2001), highlighted how emotional salience influences probability weighting. Studies in applied contexts, including insurance markets and public health campaigns, confirm the bias’s persistence, underscoring its practical relevance and replicability across cultures and domains.

Trivia Example: A vivid example of probability neglect is seen in lottery participation. Despite the extremely low probability of winning, millions of people purchase tickets, driven by the emotional appeal of a life-changing win. Research by Haisley et al.

(2008) shows that the framing of lotteries emphasizes potential rewards while downplaying probabilities, effectively leveraging this bias to drive sales.

Selected References

Haisley, E., Mostafa, R., & Loewenstein, G. (2008). Subjective relative income and lottery ticket purchases. Journal of Behavioral Decision Making, 21(3), 283–295.

Kunreuther, H., Meyer, R., & Michel-Kerjan, E. (2001). Strategies for better protection against catastrophic risks. Journal of Risk and Uncertainty, 33(2–3), 179–195.

Rottenstreich, Y., & Hsee, C. K. (2001). Money, kisses, and electric shocks: On the affective psychology of risk. Psychological Science, 12(3), 185–190.

Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90(4), 293–315.

Business Example: Probability neglect frequently affects consumer behavior in the insurance industry. For example, people often purchase extended warranties for low-cost electronics, despite the minimal likelihood of the product failing during the warranty period. Similarly, companies market insurance for rare events, such as travel delays,

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PARKINSON’S LAW OF TRIVIALITY The law that states people within an organization commonly or typically give disproportionate weight to trivial issues.

"Why are you so upset?" Rooney greeted Ellie outside her house. "How's your internship going?"

"That's just it, it's not going at all," Ellie grumbled. "It's not an internship; it's like a punishment. It's a madhouse!" "Can you explain what's happening?"

"You wouldn't believe what the entire office was doing all day today."

"And what was that?"

"Instead of working, we spent the whole day discussing how to set up the kitchen.

Which water cooler to install, which coffee machine to buy. It's a nightmare. I'm not learning anything."

"Don't worry, you will learn. You'll see, everything will be fine tomorrow."

"I hope so, otherwise I won't last long there!"

Ellie shrugged and wearily made her way home.

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such as IT infrastructure upgrades. Research by Hinds and Bailey (2003) reveals that participants in collaborative decision-making often focus on topics where they feel confident contributing, even if those topics are trivial compared to broader organizational priorities. This dynamic leads to inefficient resource allocation and decision-making delays.

About: Parkinson’s law of triviality, also known as the “bikeshedding effect,” describes the tendency of groups to spend disproportionate amounts of time discussing trivial or minor issues while neglecting more significant and complex matters. This concept was introduced by Cyril Northcote Parkinson (1957) and exemplifies how decision-making in committees or organizations often focuses on areas that participants find familiar or easier to understand. The law highlights inefficiencies in group dynamics and decision-making, particularly in corporate, academic, and governmental settings.

Reproducibility: Parkinson’s law of triviality has been observed in both anecdotal and empirical studies. While the original formulation by Parkinson (1957) was based on qualitative insights, subsequent research in organizational behavior, such as that

by Hinds and Bailey (2003), validates the effect in collaborative group settings. Recent studies, including Lurie and Swaminathan (2009), demonstrate how decision-makers gravitate toward familiar or less cognitively demanding issues, even in high-stakes scenarios. These findings confirm the replicability of Parkinson’s law across diverse contexts and its relevance to modern organizational challenges.

Trivia Example: A classic anecdote illustrating Parkinson’s law of triviality involves a committee tasked with approving the construction of a nuclear power plant. Members spend most of their time debating the cost of the staff bike shed (a minor expense) rather than the technical and financial complexities of the plant itself. This example reflects how familiarity and perceived competence drive disproportionate attention to less important topics (Parkinson, 1957).

Selected References

Hinds, P. J., & Bailey, D. E. (2003). Out of sight, out of sync: Understanding conflict in distributed teams.

Organization Science, 14(6), 615–632.

Lurie, N. H., & Swaminathan, J. M. (2009). Is timely information always better? The effect of feedback frequency on decision making. Journal of Operations Management, 27(3), 230–240.

Parkinson, C. N. (1957). Parkinson’s law, and other studies in administration. Houghton Mifflin.

Business Example: In corporate settings, Parkinson’s law of triviality frequently manifests during budget allocation meetings. For instance, executives may spend hours debating the cost of office supplies while glossing over significant financial investments,

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REGRESSIVE BIAS A certain tendency to see past events as being more predictable than they actually were; also known as the "hindsight bias."

"Hello, Rooney, long time no see! You never come to visit me!" Ellie's voice sounded slightly offended on the phone.

"Don't be upset, it's not intentional. My little brother got sick, so I'm staying home to avoid spreading it. Besides, we just saw each other last Monday. That's not so long ago," Rooney replied. "Tell me, how are you doing?"

"Wait, I've got another call coming in," Ellie said, disappearing for a few seconds. Coming back to the conversation, she sounded irritated: "It's those spammers again. They constantly call me! Offering a better phone plan, or a chance to play in a lottery. It's like my number is coated in honey!"

"Don't exaggerate. Everyone gets those calls. I get them too. Everyone does. Come on, don't be annoyed – you promised to tell me how you're doing!"

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Similarly, in financial markets, investors may overinterpret sharp rises or declines in stock prices, assuming a predictable trend, when such movements often reflect temporary fluctuations.

Research by Fiedler et al. (2010) shows how these misinterpretations can lead to misallocated resources and poor investment decisions, with companies prioritizing short-term gains over sustainable strategies.

About: Regressive bias describes the cognitive tendency to misunderstand the natural statistical phenomenon of regression to the mean. This bias occurs when individuals fail to recognize that extreme observations (both positive and negative) are likely to move closer to the average over time due to statistical randomness. Francis Galton (1886) was the first to identify this phenomenon while studying hereditary traits, noting how children of very tall or short parents tended to exhibit heights closer to the population mean. Regressive bias can lead to flawed causal attributions, as people often interpret regression as the result of external factors, such as intervention, punishment, or reward. This bias affects judgment in fields such as education, business, healthcare, and sports performance.

Reproducibility: Regressive bias has been extensively validated through experimental and real-world studies across disciplines. Galton’s (1886) foundational research on hereditary traits remains a cornerstone of understanding statistical regression, with subsequent studies reinforcing the phenomenon’s ubiquity. Kahneman and Tversky’s (1973) experiments on probabilistic reasoning consistently demonstrated that individuals fail to account for regression to the mean in predicting outcomes, such as exam scores or athletic performance. In education, studies like those by Sherman and Chassin (2015) confirm that teachers and policymakers often misinterpret changes in student performance, attributing natural fluctuations to teaching methods or interventions. Across domains, regressive bias has proven highly replicable, emphasizing the importance of statistical literacy in mitigating its effects.

Trivia Example: The “sophomore slump” in sports offers a welldocumented example of regressive bias. Athletes who deliver exceptional rookie performances are often thought to experience a decline in their second season due to psychological or physical factors. However, Kahneman and Tversky (1973) demonstrated that this “slump” is often just regression to the mean. Extreme performance in one season is unlikely to persist because such performances often combine skill with favorable, but random, circumstances. This natural statistical correction is frequently misattributed to a decrease in effort or changes in strategy.

Selected References

Fiedler, K., Unkelbach, C., & Freytag, P. (2010). On the adaptive function of regression toward the mean and how to counteract it in prediction. Psychological Review, 117(3), 1116–1130.

Galton, F. (1886). Regression towards mediocrity in hereditary stature. The Journal of the Anthropological Institute of Great Britain and Ireland, 15, 246–263.

Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80(4), 237–251.

Sherman, J. W., & Chassin, L. (2015). The psychology of statistical reasoning: Understanding regression to the mean.

Current Directions in Psychological Science, 24(6), 450– 455.

Stigler, S. M. (1997). Regression toward the mean, historically considered. Statistical Methods in Medical Research, 6(2), 103–114.

Business Example: Regressive bias significantly impacts business decision- making, particularly in performance evaluation and financial forecasting. Managers may expect employees who deliver exceptional results in one quarter to maintain the same level of performance indefinitely. When subsequent results regress toward the mean, they may incorrectly attribute the decline to reduced effort or organizational changes, leading to unwarranted criticism or interventions.

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SURVIVORSHIP BIAS Concentrating on the people or things that "survived" some process and inadvertently overlooking those that did not because of their lack of visibility.

"What are you thinking about?" Ellie asked as she sat down next to Rooney at a café table.

"Remember Drake? My friend," Rooney said pensively. "Yeah, what about him?"

"We had a fight. He claims that getting a higher education isn't necessary. At first, I disagreed, but now I'm wondering if he might be right."

"In what way?" Ellie smiled.

"Look at people like Bill Gates and Mark Zuckerberg – they achieved success without a college degree! And Peter Thiel even established a fellowship for young entrepreneurs who want to drop out of school…"

"Think about what you're saying," Ellie continued smiling. "You're a mathematician. Sure, there are exceptions like Gates or Zuckerberg, but the majority benefit from higher education. Statistics show that people with degrees earn more and have lower unemployment rates! You know all this. And besides – would you trust a doctor or lawyer without a degree?"

"You're right, I hadn't considered that. So, how about a coffee?" Rooney asked. "Definitely!"

Ellie replied cheerfully.

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survivorship bias inflates mutual fund performance metrics, as underperforming funds are removed from datasets, giving a misleadingly optimistic view of overall market success. Brown et al. (1992) demonstrated this effect in mutual fund analyses, underscoring its impact on investment strategies and decision-making.

About: Survivorship bias is a cognitive bias where individuals focus disproportionately on successes while ignoring failures, leading to skewed conclusions. This occurs because failed entities are often excluded from datasets or narratives, creating an incomplete understanding of the factors driving success. The concept was first formally recognized during World War II by Abraham Wald, whose work demonstrated how ignoring failures could lead to flawed decision- making. Survivorship bias affects areas such as finance, entrepreneurship, healthcare, and education, distorting how success is perceived and decisions are made.

Reproducibility: Survivorship bias is a robust and consistently observed phenomenon across various domains.

Mangel and Samaniego’s (1984) analysis of World War II survivability studies remains a seminal demonstration of the bias’s real-world implications. In finance, Brown et al. (1992) replicated its presence in long-term investment performance studies. Similarly, Song et al. (2010) highlighted survivorship bias in healthcare, where successful clinical trials are more likely to be published, skewing the perceived efficacy of treatments. These findings demonstrate the widespread applicability and replicability of survivorship bias in both theoretical and applied contexts.

Trivia Example: A well-documented example of survivorship bias is found in World War II aircraft analysis.

Engineers initially suggested reinforcing areas where returning planes showed the most bullet damage. However, Wald observed that the unexamined planes—those that did not return— likely sustained hits in critical, unprotected areas. His insights redirected reinforcement efforts to these critical regions, significantly improving aircraft survival rates (Mangel and Samaniego, 1984).

Selected References

Brown, S. J., Goetzmann, W. N., Ibbotson, R. G., & Ross, S. A. (1992). Survivorship bias in performance studies. The Review of Financial Studies, 5(4), 553–580.

Mangel, M., & Samaniego, F. J. (1984). Abraham Wald’s work on aircraft survivability. Journal of the American Statistical Association, 79(386), 259–267.

Song, F., Parekh, S., Hooper, L., Loke, Y. K., Ryder, J., Sutton, A. J., & Harvey, I. (2010). Dissemination and publication of research findings: An updated review of related biases.

Health Technology Assessment, 14(8), 1–193.

Business Example: Survivorship bias is prevalent in entrepreneurial studies and investing. Media coverage often highlights successful startups, emphasizing attributes like innovation and perseverance, while ignoring the far larger number of ventures that fail despite similar traits. In finance,

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SUBADDITIVITY EFFECT The tendency to judge probability of the whole to be less than the probabilities of the parts.

"I'll never learn to do the math correctly," Ellie stated in frustration, "especially those probability problems!"

"Don't worry," Rooney encouraged her. "You're doing great! Most people don't even understand what probability is, let alone how to work with it." "What do you mean?"

"Imagine this. Suppose we go outside and ask a hundred random people three questions: What percentage of sales at the local café consists of pizza sales? What percentage is doughnuts? And then, we ask what percentage of total sales are unhealthy foods?"

"And what will happen?"

"I bet anything that most people will give a number for the third question that's less than the sum of the answers to the first two questions. You see? They might answer 20 percent for the first question, 15 percent for the second, and, say, 25 percent for the third. But pizza and doughnuts are unhealthy foods. So, the answer to the third question should be more than 35 percent in any case."

"But that's simple! I would never make that mistake!"

"See, that's why I'm saying you're doing great.

Don't underestimate yourself!"

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premiums, consumers perceive the risks as collectively higher, prompting them to purchase comprehensive coverage.

Research by Rottenstreich and Tversky (1997) highlighted how breaking down risks into vivid subcategories increases perceived probability, an effect leveraged in marketing and sales to influence consumer decisions.

About: The subadditivity effect refers to the cognitive bias where individuals overestimate the probability of an event when it is broken into detailed components, compared to when it is presented as a single, overarching probability.

This effect arises because people often assess probabilities heuristically, giving undue weight to the components, which collectively exceed the whole. First explored by Tversky and Koehler (1994), the subadditivity effect has significant implications in risk perception, decision-making, and predictive modeling.

Reproducibility: The subadditivity effect has been consistently replicated in experimental and applied contexts.

Tversky and Koehler’s (1994) original work demonstrated its robustness in probabilistic judgments, and subsequent research has extended these findings to domains such as healthcare, finance, and public policy. Studies by Sloman et al. (2004) confirmed that people tend to overestimate cumulative probabilities when events are broken down into subcomponents.

This effect has also been observed in real-world applications, such as insurance marketing and disaster risk communication, confirming its relevance and replicability.

Trivia Example: A notable example of the subadditivity effect is seen in risk estimation. When asked to estimate the likelihood of dying from natural causes, people often provide a lower probability compared to when asked to estimate specific causes (e.g., heart disease, cancer, accidents) and sum them. Research by Sloman et al. (2004) demonstrated this phenomenon, showing that individuals tend to overweight the specific causes, leading to inflated overall risk perceptions.

Selected References

Rottenstreich, Y., & Tversky, A. (1997). Unpacking, repacking, and anchoring: Advances in support theory. Psychological Review, 104(2), 406–415.

Sloman, S. A., Over, D. E., Slovak, L., & Stibel, J. M. (2004).

Frequency illusions and other fallacies. Organizational Behavior and Human Decision Processes, 91(2), 296–309.

Tversky, A., & Koehler, D. J. (1994). Support theory: A nonextensional representation of subjective probability.

Psychological Review, 101(4), 547–567.

Business Example: The subadditivity effect influences consumer behavior, particularly in risk communication and marketing. For instance, when car insurance companies present detailed risk scenarios (e.g., theft, accidents, natural disasters) alongside

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WELL TRAVELLED ROAD EFFECT Underestimation of the duration taken to traverse ofttravelled routes and overestimation of less familiar routes.

"Where are you taking me?" Ellie asked in dissatisfaction, stopping in her tracks. "Are we sure we're heading to the modern art museum? It feels like we're just wandering around the park."

"Don't worry," Rooney reassured her, taking her hand and pulling her along confidently.

"We're on the right path."

"I don't know. I don't like this. I usually go over the bridge, then through the main square near the city hall building. It's shorter that way."

"Actually, going through the city hall makes the journey 15 minutes longer. It only seems longer this way because you're not familiar with this route." "I find that hard to believe," Ellie said reluctantly as they moved forward. "Trust me, we're almost there," Rooney asserted confidently.

"We'll see!" Ellie remained skeptical.

"And here's the museum," Rooney said joyfully.

"See, normally it takes us 40 minutes, but we got here in 25!"

Looking at her watch, Ellie was surprised: "You're right. But it felt like we'd been walking for hours!"

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roads, leveraging the psychological comfort associated with familiarity to attract more customers. Studies such as those by Goodwin and Lyons (2010) demonstrate that businesses can use this effect to enhance customer satisfaction and reduce perceived delays in services.

About: The well-traveled road effect is a cognitive bias in which people perceive familiar or frequently used routes as shorter in duration than unfamiliar or rarely used ones, even when the actual travel time is the same. This bias arises because familiarity with a route reduces cognitive load and enhances predictability, creating a subjective sense of reduced travel time. Originally explored by researchers in the context of navigation and transportation psychology, this effect reflects the interplay between perception, attention, and familiarity in decision-making. It has significant implications for transportation planning, consumer behavior, and workplace productivity.

Reproducibility: The well-traveled road effect has been consistently validated in experimental and applied research. Studies by Avineri and Bovy (2008) demonstrated its robustness in both simulated and real-world navigation tasks, where participants consistently underestimated the time of familiar routes. Goodwin and Lyons (2010) extended these findings to consumer and transportation contexts, showing that subjective travel time influences decisions about route selection and service satisfaction. Subsequent research has confirmed the effect’s replicability across cultural and contextual settings, emphasizing its generalizability and relevance in practical applications.

Trivia Example: A classic example of the well-traveled road effect occurs during commutes. Drivers often perceive their daily route to work as shorter than an alternative route of equal length, even if travel time measurements show no difference.

Research by Avineri and Bovy (2008) revealed that familiarity reduces the perceived effort and duration of travel, while unfamiliar routes require greater attentional resources, amplifying the subjective experience of time.

Selected References

Avineri, E., & Bovy, P. H. L. (2008). Identification of parameters affecting drivers’ route choice decisions. Transportation, 35(6), 745–758.

Goodwin, P., & Lyons, G. (2010). Public attitudes to transport: Interpreting the evidence. Transportation Research Part A: Policy and Practice, 44(9), 891–905.

Hensher, D. A., & Rose, J. M. (2007). Behavioural responses of commuters to road user charging: Findings from a mixed logit model applied to data from three cities.

Transportation Research Part A: Policy and Practice, 41(7), 631–640.

Business Example: This bias has implications in consumer behavior and logistics. Delivery services, for instance, often prioritize familiar routes for drivers to minimize perceived workload and improve efficiency.

Moreover, retail businesses strategically locate stores along well-traveled

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ZERO-SUM BIAS A bias whereby a situation is perceived to be like a zero-sum game, where one person's gain is another's loss.

"Hi, I see you're not in a good mood. What happened?" Rooney patted Ellie on the shoulder.

"My mom has a new hobby. She's decided to take up painting."

"That's awesome! You paint and now she does too – you'll have something to talk about!"

"I don't see it as a good thing. She's hardly ever home, always at work. Now she's going to attend painting classes. We'll barely see her at home."

"You're exaggerating. When my younger brother was born, I thought Mom would give all her attention to him. I even got angry. But it turned out not to be the case. Attention isn't a pie that we have to share with my brother. I used to think if he got a bigger slice, I'd get a smaller one. But now, I'm so glad to have a brother, and Mom and I have become even closer. So, get rid of those silly thoughts. You'll spend more time with your mom, talking about art. That's cool!"

Ellie brightened up: "We'll see!" she said.

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beneficial outcomes due to zero-sum assumptions, leading to suboptimal agreements.

This bias also affects perceptions of market competition, where companies assume a competitor’s success automatically diminishes their own, discouraging innovation and collaboration.

About: Zero-sum bias is the cognitive bias where individuals mistakenly perceive situations as having fixed resources, assuming that one party’s gain must come at another’s expense.

This bias is rooted in a misunderstanding of resource dynamics and can distort judgment in social, economic, and organizational contexts.

First discussed in the context of game theory, the term “zero-sum” derives from scenarios in which the total value of gains and losses equals zero.

However, many real-world situations are nonzero-sum, where mutual benefit or shared growth is possible. Zero-sum bias impacts decision-making in interpersonal relationships, workplace collaboration, and global economics.

Reproducibility: The zero-sum bias has been robustly validated across experimental and applied studies.

Meegan’s (2010) experiments demonstrated its presence in competitive and cooperative contexts, with participants consistently perceiving gains as coming at others’ expense, even in clearly non-zero-sum situations.

Additional studies, such as those by Rubinstein (1995), confirmed the bias in decision-making scenarios involving resource allocation. Crosscultural research, including work by RóżyckaTran et al. (2015), highlighted its universality, showing that zero-sum thinking persists across diverse economic and cultural settings, underscoring its replicability and global relevance.

Trivia Example: A common manifestation of zero-sum bias occurs in workplace promotions. Employees often perceive a colleague’s promotion as a threat to their own opportunities, even in organizations with expanding roles or collaborative structures.

Research by Meegan (2010) illustrates how zerosum thinking exacerbates workplace competition and fosters conflict, even in environments conducive to collective success.

Selected References

Bazerman, M. H., & Neale, M. A. (1992). Negotiating rationally.

Free Press.

Meegan, D. V. (2010). Zero-sum bias: Perceived competition despite unlimited resources. Frontiers in Psychology, 1(191), 1–7.

Różycka-Tran, J., Boski, P., & Wojciszke, B. (2015). Belief in a zerosum game as a social axiom: A 37-nation study. Journal of Cross-Cultural Psychology, 46(4), 525–548.

Rubinstein, A. (1995). A theory of zero-sum and non-zero-sum games. Games and Economic Behavior, 10(1), 94–117.

Business Example: Zero-sum bias is particularly detrimental in business negotiations. For instance, in mergers and acquisitions, parties often overfocus on dividing resources rather than identifying opportunities for synergy and shared growth.

Bazerman and Neale (1992) demonstrated that negotiators frequently fail to explore mutually

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DUNNING-KRUGER EFFECT A cognitive bias in which people with low ability at a task overestimate their ability.

"I'm making soup," Rooney declared, despite the kitchen mess indicating his inexperience.

"Soup? Have you ever done that before?" Ellie was skeptical, noticing the haphazardly cut vegetables and the chaotic state of the kitchen.

"Okay, I've never made soup, but how hard can it be?" Rooney said confidently.

"Why are you cooking all of a sudden?" Ellie inquired, peeking into the boiling pot on the stove.

"My mom's away, and I need to make cauliflower soup for my little brother Oliver. I didn't really listen to the recipe, but I figured it's just boiling and mixing."

"Cauliflower soup? That's not even easy for me.

Are you sure about the recipe?"

Ellie was concerned, her own cooking skills notwithstanding.

"I'm almost done, actually. It's time to taste my masterpiece!" Rooney said proudly, ignoring the soup's unusual pink color and the odd addition of cheese.

"Wait, you can't just serve it without tasting!

Cauliflower soup isn't supposed to be pink, and why is there cheese?" Elli was alarmed.

"It's all about taste, not looks. Oliver loves cheese," Rooney justified.

"Fine, but taste it first," Ellie insisted, worried about serving it to his little brother.

Reluctantly, Rooney tasted the soup and immediately regretted it. His expression turned to disgust as he coughed and spat out the soup. "This is awful! I thought this would be easy!"

"Okay, Master Chef," Ellie said with a slight smirk, "you clean up, and I'll make some porridge for Oliver. There's oats and milk, and I know what I'm doing."

Elli rang the doorbell, and Rooney, clearly in a hurry, opened the door. "Hey, come in, quick," Rooney urged.

"What's going on?" Elli asked, following him into the kitchen, which was in total chaos.

Vegetables and onions were scattered everywhere, with broken eggs in the sink.

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take on responsibilities, undervaluing their skills. Research by Gino and Pisano (2008) shows that addressing this bias through structured feedback and mentorship programs can improve decision-making and organizational outcomes.

About: The Dunning-Kruger effect is a cognitive bias where individuals with low ability in a specific domain overestimate their competence, while highly skilled individuals often underestimate theirs. This phenomenon was first formally studied by David Dunning and Justin Kruger (1999), who demonstrated that people lacking expertise not only perform poorly but also fail to recognize their deficiencies due to limited selfawareness. Conversely, experts tend to underestimate their competence because they assume others possess similar knowledge. The effect has broad implications in education, workplace dynamics, and public policy, particularly in understanding decision-making and confidence.

Reproducibility: The Dunning-Kruger effect has been robustly validated in experimental and real-world settings. Dunning and Kruger’s (1999) foundational research has been replicated across various domains, including sports, academics, and financial decision-making. Studies like Ehrlinger et al. (2008) extended these findings, demonstrating that the effect persists across cultures and contexts. However, critics like Krueger and Mueller (2002) argue that statistical artifacts may explain some overestimation patterns, emphasizing the need for careful methodological designs in future studies.

Despite these debates, the core phenomenon remains widely acknowledged and empirically supported.

Trivia Example: A classic illustration of the Dunning-Kruger effect involves unskilled participants in trivia quizzes. Dunning and Kruger (1999) found that the bottom quartile of performers consistently rated their abilities as above average. Despite their low scores, these individuals demonstrated high confidence in their answers, highlighting the disconnect between perceived and actual competence. This phenomenon has since been replicated in various domains, from driving skills to financial literacy.

Selected References

Dunning, D., & Kruger, J. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134.

Ehrlinger, J., Johnson, K., Banner, M., Dunning, D., & Kruger, J. (2008). Why the unskilled are unaware: Further explorations of (absent) self-insight among the incompetent. Organizational Behavior and Human Decision Processes, 105(1), 98–121.

Gino, F., & Pisano, G. P. (2008). Toward a theory of behavioral operations. Manufacturing & Service Operations Management, 10(4), 676–691.

Krueger, J., & Mueller, R. A. (2002). Unskilled, unaware, or both?

The better- than-average heuristic and statistical regression predict errors in estimates of own performance. Journal of Personality and Social Psychology, 82(2), 180–188.

Business Example: T he Dunning-Kruger effect frequently manifests in the workplace, where employees with limited expertise may overestimate their abilities and seek leadership roles for which they are unqualified. This can lead to poor decisionmaking and team inefficiencies. Conversely, highly competent employees may hesitate to 187

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HARD-EASY EFFECT The tendency to overestimate one's ability to perform easy tasks and to underestimate one's ability to perform difficult tasks. arranged by increasing difficulty. You'll ask me the problems, I'll solve them, and you check the answers in the back of the book.

Got it?"

"Fine," Ellie agreed reluctantly. "Let's start with number 22. It seems simpler."

"No, let's do number 356. I'm sure."

"Are you sure? Maybe start with something easier?"

"No, 356. I'm sure."

Ellie read out the complex problem, struggling with the terminology and the convoluted expressions. "This is a nightmare. My brain hurts just looking at this problem. Let's really start with an easier one."

"No, I won't solve the 'simple' one. There must be a trick. Let's stick to 356." "Afraid to solve a simple problem?" Ellie teased.

"I'm not afraid," Rooney said nervously.

"Fine," Ellie sighed, taking a piece of paper and pen, and started working out the problem.

"Here's the answer: minus the square root of x." "We need to check it," Rooney said skeptically.

"Look! It's correct!" Ellie was pleased with herself.

"Let me see. Strange... Alright, let me solve 356."

Within minutes, Rooney announced, "Done. For x from four to eight, the answer is 4x divided by x minus four. And for x from eight to infinity, it's 2x divided by the square root of x minus four."

Ellie checked the answer, "Right. That's enough for me. I'm going back to bed. You're ready for the test. Close the door when you leave.

But maybe practice those 'easy' problems; it's all a bit odd."

"Hi," Rooney looked puzzled as he entered. "Are you busy? I need some help."

Ellie let him into the kitchen, yawning, "Do you know what time it is? It's 7 AM on a Saturday. I'm usually asleep."

"You'll miss all the fun. Help me prepare for a math test."

"Are you kidding? You're the math genius. How can I help? I don't get any of this." Ellie looked at Rooney, realizing he was serious.

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ineffective strategies. For instance, research by Moore and Healy (2008) shows that overconfidence in challenging predictions, like market trends, often results in costly errors, whereas underconfidence in straightforward tasks, such as budgeting, can lead to missed opportunities for efficiency.

About: The hard-easy effect is a cognitive bias where people overestimate their ability to perform well on difficult tasks and underestimate their competence on easier ones. This phenomenon arises due to varying confidence levels across different levels of task difficulty. Lichtenstein and Fischhoff (1977) formally identified the effect, observing that confidence tends to exceed accuracy on challenging tasks, while the reverse holds true for simpler ones. The bias highlights how task complexity influences self-assessment, impacting decision making in areas such as education, healthcare, and risk evaluation.

Reproducibility: The hard-easy effect has been extensively replicated in experimental and applied research.

Lichtenstein and Fischhoff’s (1977) foundational study demonstrated the bias across a range of tasks with varying difficulties. Subsequent studies, such as those by Soll and Klayman (2004), confirmed its prevalence in domains like judgment and decision-making, particularly in probabilistic reasoning. Cross-cultural research (e.g., Juslin et al., 2000) has further validated the effect, showing it persists across different populations and contexts, although the magnitude of the bias may vary.

Trivia Example: A classic example of the hard-easy effect is seen in trivia games. Participants often exhibit overconfidence when answering obscure or highly specific questions, assuming they might “guess correctly.” Conversely, they undervalue their knowledge of general or widely known facts. Studies like those by Soll and Klayman (2004) confirm that this miscalibration persists across various domains, particularly in environments where individuals are not immediately held accountable for their predictions.

Selected References

Juslin, P., Winman, A., & Olsson, H. (2000). Naive empiricism and dogmatism in confidence research: A critical examination of the hard-easy effect. Psychological Review, 107(2), 384– 396.

Lichtenstein, S., & Fischhoff, B. (1977). Do those who know more also know more about how much they know? The calibration of probabilities. Journal of Experimental Psychology: Human Learning and Memory, 6(2), 330–334.

Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502–517.

Soll, J. B., & Klayman, J. (2004). Overconfidence in interval estimates. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30(2), 299–314.

Business Example: The hard-easy effect manifests when managers overestimate their ability to solve complex strategic problems, such as entering a competitive market, while underestimating their proficiency in routine operational decisions. This bias can lead to misallocated resources and

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OVERCONFIDENCE EFFECT Excessive confidence in one's own answers to questions. For example, for some types of questions, answers that people rate as "99% certain" turn out to be wrong 40% of the time.

"Are you busy?" Ellie asked, entering the room.

She needed Rooney's help to pick up and transport the orchids she had been waiting for months. That morning, a polite girl had called her with a pleasant voice, informing her that her orchids had arrived and could be collected after lunch.

"Listen," Rooney suddenly remembered he had promised to help Ellie with the orchids. "I can't make it today. How about tomorrow?

I've decided to participate in an online chess tournament. It's easy money – the first prize is almost $20,000, and there are smaller cash prizes too."

"I didn't know you were good at chess."

"I'm not sure about 'good,' but I'm definitely above average. So, I think I have a solid shot at winning a cash prize."

"Don't you think most people in the tournament also consider themselves above average? Fine, pick me up tomorrow. Good luck."

The next day, on a gloomy Sunday morning with storm clouds gathering, Rooney rang Ellie's doorbell.

"So, how did it go, Mr. Grandmaster?" Ellie asked, opening the door.

Rooney smiled sheepishly, "Not well. Imagine, I got knocked out in the second round yesterday. Maybe I'm not as good as I thought. You were right – I underestimated the competition. But at least I'm great at helping carry orchids!" he laughed.

"Alright, let's go. Just let me grab an umbrella," Ellie said, locking the front door.

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overextending resources.

Similarly, overconfidence among executives leads to overoptimistic forecasts, resulting in missed financial targets and strategic errors (Moore and Healy, 2008).

About: The overconfidence effect refers to the cognitive bias where individuals overestimate their abilities, knowledge, or the accuracy of their judgments. It manifests in three key forms: overestimation (believing you are better than you are), overplacement (believing you are better than others), and overprecision (excessive certainty in the accuracy of your beliefs). This bias was extensively studied by Lichtenstein et al.

(1982), who found that people tend to miscalibrate their confidence, especially in contexts involving subjective or uncertain judgments. The overconfidence effect has profound implications in decision-making, risk assessment, and interpersonal dynamics, often leading to errors and inefficiencies.

Reproducibility: The overconfidence effect is one of the most robustly studied cognitive biases, replicated in various contexts and populations. Lichtenstein et al. (1982) demonstrated its prevalence in probabilistic reasoning tasks, showing a consistent overconfidence-accuracy gap.

Subsequent research by Fischhoff et al. (2005) validated these findings, revealing that the bias persists across cultures and domains. While some studies, such as those by Gigerenzer et al.

(1991), argue that overconfidence may diminish in specific contexts with expertise or feedback, the general phenomenon remains highly replicable and widely acknowledged.

Trivia Example: A striking example of the overconfidence effect is seen in driving behavior. Studies consistently show that the majority of drivers rate themselves as above average in skill, which is statistically impossible (Svenson, 1981). This overestimation can lead to risky behaviors, such as speeding or underestimating hazards, contributing to increased accident rates.

Selected References

Fischhoff, B., Slovic, P., & Lichtenstein, S. (2005). Knowing with certainty: The appropriateness of extreme confidence.

Journal of Experimental Psychology: Human Perception and Performance, 3(4), 552–564.

Gigerenzer, G., Hoffrage, U., & Kleinbölting, H. (1991).

Probabilistic mental models: A Brunswikian theory of confidence. Psychological Review, 98(4), 506–528.

Koellinger, P., Minniti, M., & Schade, C. (2007). “I think I can, I think I can”: Overconfidence and entrepreneurial behavior. Journal of Economic Psychology, 28(4), 502–527.

Lichtenstein, S., Fischhoff, B., & Phillips, L. D. (1982). Calibration of probabilities: The state of the art to 1980. Heuristics and biases: The psychology of intuitive judgment, 306– 334.

Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502–517.

Svenson, O. (1981). Are we all less risky and more skillful than our fellow drivers? Acta Psychologica, 47(2), 143–148.

Business Example: The overconfidence effect is evident in entrepreneurial ventures. Founders often overestimate the likelihood of success, ignoring statistical evidence that most startups fail.

Research by Koellinger et al. (2007) highlights that overconfidence drives entrepreneurship but also contributes to underestimating risks and

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PESSIMISM BIAS The tendency for some people, especially those suffering from depression, to overestimate the likelihood of negative things happening to them. sent me some technical test questions, which I answered. But yesterday was the third stage – an interview with the team working on robots and artificial intelligence."

"People interviewed you this time, right?"

"What? Oh, yes, people. The questions varied – some on programming, some on logic. I think I got the programming ones right, but I'm not so sure about the logic questions. I might have ruined everything."

"Don't be so dramatic. You don't know the outcome yet. I'm sure it's not that bad," Ellie tried to reassure him.

"You don't understand," Rooney ignored Ellie's words. "This was a once-in-a- lifetime chance. If I failed, they'll never take me. I'm tired of working as a tennis coach and barista. I want to use my brain."

"Why the pessimism? What did they tell you?"

"They said they'd call back. But I know they won't. They say that to everyone."

"Just wait."

"Wait for what?"

"Let's have some ice cream," Ellie suggested.

"I don't want ice cream!" Rooney grumbled and stared back at the water. Then, his phone rang. He answered mechanically without looking away from the water, "Yes, this is me." His face suddenly lit up. "Sorry, could you repeat that? Of course. Yes, yes, absolutely. Thank you! Goodbye."

"What happened?" Ellie asked.

"They asked if I could start the internship on Monday," Rooney said in disbelief, beaming with happiness, "and is that ice cream offer still on the table?”

"Rooney! Why so gloomy?" Ellie greeted Rooney in the park. He stood on the bridge, gazing at the water, clearly out of sorts. The summer sun illuminated the blue water.

"I think I messed up," he said, turning to Ellie. "I might have made mistakes during yesterday's interview." "What interview?"

"I was interviewing for an internship at a robotics company. It was such a great opportunity, and I feel like I blew it." "Can you explain what happened?"

"About a month ago, they invited me for the first interview. A robot interviewed me with basic questions. Then, two weeks ago, they 192

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to pessimism bias often underestimate growth opportunities, leading to stagnation.

Additionally, this bias can influence hiring decisions, where managers may avoid taking risks on unconventional but potentially highperforming candidates, opting for safer, less innovative hires.

About: Pessimism bias is the cognitive tendency to overestimate the likelihood of negative outcomes, particularly in uncertain or challenging situations. This bias often stems from anxiety, negative past experiences, or a general disposition toward cautious thinking.

While it can sometimes lead to prudent risk management, pessimism bias also results in excessive worry and missed opportunities.

Taylor and Brown (1988) contrasted it with optimism bias, demonstrating that individuals prone to pessimism bias often exhibit lower subjective well-being and resilience. This bias has significant implications in decision-making, public health, and organizational behavior.

Reproducibility: Pessimism bias has been consistently replicated in experimental and real-world studies. Taylor and Brown’s (1988) research demonstrated its psychological underpinnings, particularly in individuals with higher trait anxiety. Studies in behavioral economics, such as those by Barberis (2013), confirmed its prevalence in financial decision-making. Additionally, Kahneman and Lovallo’s (1993) experiments validated its impact on business decisions, showing that pessimism often leads to suboptimal outcomes. Crosscultural studies, such as those by Heine et al.

(1999), highlight its pervasiveness, though cultural contexts can moderate its magnitude.

Trivia Example: A well-known example of pessimism bias occurs in financial decision-making. Investors during economic downturns often overestimate the probability of market crashes, leading to overly cautious strategies, such as liquidating assets prematurely. Research by Barberis (2013) highlights how such bias can exacerbate market volatility, as collective pessimism drives down asset prices unnecessarily.

Selected References

Barberis, N. (2013). Thirty years of prospect theory in economics: A review and assessment. Journal of Economic Perspectives, 27(1), 173–196.

Heine, S. J., Lehman, D. R., Markus, H. R., & Kitayama, S. (1999). Is there a universal need for positive self-regard?

Psychological Review, 106(4), 766–794.

Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk taking.

Management Science, 39(1), 17–31.

Taylor, S. E., & Brown, J. D. (1988). Illusion and well-being: A social psychological perspective on mental health.

Psychological Bulletin, 103(2), 193–210.

Business Example: Pessimism bias manifests in risk-averse strategies, particularly during crises. For instance, managers may delay innovation or investment during economic uncertainty, fearing failure. Research by Kahneman and Lovallo (1993) revealed that organizations prone

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RESTRAINT BIAS The tendency to overestimate one's ability to control impulsive behavior.

"Oh, that," Ellie yawned on the phone, "I haven't started yet. I'll pull a few all- nighters next week – don't worry."

"What are you up to then?" Rooney asked. "Just watching a movie."

"Are you sure you'll get everything done? You said you have a physics exam next week."

"I'll manage. I'll work hard on Wednesday and Thursday – I'll be ready for both the exhibition and the physics test."

"You said you couldn't come to training today because you needed to prepare for the exhibition, yet here you are watching a movie."

"I know, but I just wasn't feeling inspired today.

Don't worry – I'll start working on Wednesday."

"So, you're missing training on Wednesday too?"

"Looks like it," Ellie sighed with relief.

On Thursday at 6 am, Rooney was woken up by a frantic call from Ellie: "Slow down," he said groggily, "What's up?"

"It's a disaster! What am I going to do?" Ellie's voice was frantic. "Start from the beginning," Rooney sat up in bed, trying to wake up.

"My exhibition is on Saturday, and I have to submit my work tomorrow, plus there's that silly physics test. When am I going to do all this?"

"You said you'd spend a couple of nights on it this week."

"Yeah, but I was so tired yesterday and the day before – I've got nothing ready." "Okay, I get it. Here's the plan – you work on your painting (I can't help you there), and I'll come over in the evening to help with physics."

Rooney called Ellie on a Saturday evening. She hadn't shown up for training that day, but he knew she had to prepare for her art exhibition, so he decided to call her later: "Hey," he said, "how's your painting going?"

"Which painting?" Ellie sounded surprised.

"The one for your exhibition next weekend at art school."

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Tchernev (2012) show that this overconfidence leads to decreased productivity and increased cognitive fatigue. Similarly, restraint bias impacts financial decision- making, with investors overestimating their ability to avoid impulsive trades during market volatility, often resulting in suboptimal portfolio performance.

About: Restraint bias refers to the cognitive tendency to overestimate one’s ability to control impulses, particularly in the face of temptation. This bias often leads individuals to expose themselves to unnecessary risks, underestimating the strength of their desires or overconfidence in their selfdiscipline. Hoch and Loewenstein (1991) first explored the psychological mechanisms underlying this bias, linking it to temporal inconsistencies in self-control. Restraint bias has significant implications for personal behavior, addiction recovery, and financial decisionmaking, highlighting the gap between perceived and actual self-regulation.

Reproducibility: The restraint bias has been robustly validated in various experimental contexts. Nordgren et al.

(2009) provided compelling evidence through studies where participants overestimated their ability to resist temptation, such as consuming unhealthy food or spending on unnecessary items. Subsequent research, including that by Wagner and Heatherton (2015), replicated these findings in addiction studies, showing that restraint bias plays a critical role in relapse rates.

Trivia Example: A common example of restraint bias is seen in dietary behavior. Individuals who believe they have strong self-control may keep unhealthy snacks readily available at home, assuming they can resist the temptation. Research by Nordgren et al. (2009) demonstrated that people who overestimate their self- restraint are more likely to succumb to temptations when exposed, leading to overeating or diet failures.

Selected References

Hoch, S. J., & Loewenstein, G. F. (1991). Time-inconsistent preferences and consumer self-control. Journal of Consumer Research, 17(4), 492–507.

Nordgren, L. F., van Harreveld, F., & van der Pligt, J. (2009). The restraint bias: How the illusion of self-restraint promotes impulsive behavior. Psychological Science, 20(12), 1523– 1528.

Wagner, D. D., & Heatherton, T. F. (2015). Self-regulation and its failure: The seven deadly threats to self-regulation. In M. Mikulincer, P. R. Shaver, E. Borgida, & J. A. Bargh (Eds.), APA Handbook of Personality and Social Psychology: Vol. 1. Attitudes and Social Cognition (pp.

805–842). American Psychological Association.

Wang, Z., & Tchernev, J. M. (2012). The “myth” of media multitasking: Reciprocal dynamics of media multitasking, personal needs, and gratifications. Journal of communication, 62(3), 493-513.

Business Example: Restraint bias often manifests in overconfidence regarding multitasking. Employees might assume they can resist distractions, such as checking emails or social media, during important tasks. Studies like those by Wang and

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CONGRUENCE BIAS The tendency to test hypotheses exclusively through direct testing, in contrast to tests of possible alternative hypotheses.

"Wow, that's a cool shepherd dog! What are you drawing this for?" Rooney asked.

"I'm trying to create an advertisement for dog food. What do you think, do you like it?"

Ellie replied, looking up from her sketch.

"The shepherd dog looks great, but it's not immediately clear that it's for dog food, to be honest. Maybe you could add an owner feeding it?" suggested Rooney.

"I read a marketing survey which found that in advertisements, people respond better to animals than to humans. That's why I decided to draw a dog," Ellie explained.

"I get that, but the survey didn't test which specific breeds people respond best to.

Maybe many like poodles or dachshunds, not just shepherds. And not everyone has a shepherd at home..." Rooney pointed out.

Ellie pondered for a moment, "You're right. I hadn't thought of that. Indeed, it would be better to draw many happy dogs of different breeds... That would be much more effective! Thank you!"

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ignoring alternative explanations such as product design issues or changing consumer preferences. Research by Bazerman and Moore (2013) highlights how this bias can lead to suboptimal strategies, as leaders fail to fully explore and address the root causes of business challenges.

About: Congruence bias is a cognitive bias in which individuals tend to test hypotheses by confirming their assumptions rather than seeking evidence that could disprove them. This bias often leads to flawed decision-making because it overlooks alternative explanations or possibilities. Congruence bias is closely related to confirmation bias but is distinct in its emphasis on testing methods rather than merely seeking confirmatory evidence. Wason (1960) first identified this phenomenon in his studies on hypothesis testing, showing how people’s natural inclination to confirm rather than challenge their ideas limits critical thinking.

Reproducibility: Congruence bias has been consistently demonstrated in experimental settings. Wason’s (1960) original experiments have been replicated across various contexts, confirming the robustness of the phenomenon. Subsequent research, such as that by Klayman and Ha (1987), expanded on these findings by exploring the cognitive mechanisms underlying hypothesis testing. More recent studies, including those by Nickerson (1998), validated the bias in applied settings like medical diagnostics and legal decision-making, emphasizing its broad applicability and persistence.

Trivia Example: A classic example of congruence bias is seen in Wason’s (1960) number sequence task.

Participants were given a sequence (e.g., 2-4-6) and asked to identify the rule governing it by testing additional sequences. Most participants proposed sequences that confirmed their assumptions (e.g., increasing by two) instead of testing alternatives (e.g., any ascending numbers). This approach limited their ability to accurately identify the rule.

Selected References

Bazerman, M. H., & Moore, D. A. (2013). Judgment in managerial decision making (8th ed.). Wiley.

Klayman, J., & Ha, Y. W. (1987). Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review, 94(2), 211–228.

Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.

Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual task. Quarterly Journal of Experimental Psychology, 12(3), 129–140.

Business Example: Congruence bias is common in managerial decision-making. For instance, when evaluating the cause of declining sales, managers might focus exclusively on confirming their assumption that poor marketing is to blame,

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INSENSITIVITY TO SAMPLE SIZE The tendency to under-expect variation in small samples. planning to go to a summer art school and can't decide which one to choose."

"What's the dilemma?"

"One school is in San Francisco, offering lectures from 40 artists each month, while the other is in Paris, with 10 artists teaching monthly. About half of the graduates from both schools get to exhibit individually in prestigious galleries. I checked last year's statistics, and it turns out 70% of graduates from both schools got to exhibit somewhere. Naturally, I aim for an individual exhibition. So, which school should I pick?"

"I'm not sure if you should approach the choice of an art school mathematically, but if you want to calculate, the school with fewer students is better."

"Why? I thought the exhibition chances are the same at both schools. I was expecting you to suggest flipping a coin."

"That's true, the probability is the same, but in the smaller school, 7 out of 10 students get to exhibit, while in the larger one, it's 28 out of 40. So, in the first school, almost everyone gets to exhibit (7 do, 3 don't), while in the second school, 12 out of 40 miss out."

"I see, so it's not just about probability, but also the number of people!" "Exactly!" Rooney pondered. "And overall, I think you'll prefer the smaller school. There should be a more personalized approach, but you'll have to work harder.

Just how you like it!"

"Hi, I wanted to get your advice," Ellie said as she placed her backpack on the table and pulled out some printouts. "I have a question that's right up your alley!"

Rooney smiled: "Shoot!"

"Look at this," Ellie spread out the papers with printed numbers in front of Rooney. "I'm 198

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sample data often misrepresent population-level patterns, leading to overconfidence in initial findings and costly errors in strategy implementation.

About: Insensitivity to sample size is a cognitive bias in which individuals fail to recognize the importance of sample size in determining the reliability and variability of statistical outcomes.

People often assume that results from small samples are just as representative as those from larger ones, leading to erroneous conclusions.

This bias was first systematically studied by Kahneman and Tversky (1972), who demonstrated that individuals frequently neglect the increased variability inherent in smaller samples. This phenomenon has significant implications in decision-making, particularly in fields like healthcare, education, and business analytics.

Reproducibility: Insensitivity to sample size has been extensively replicated in experimental and real-world contexts. Kahneman and Tversky’s (1972) foundational experiments demonstrated this bias in probabilistic reasoning tasks. Subsequent studies, such as those by Sedlmeier and Gigerenzer (2001), confirmed its persistence across diverse decision-making scenarios, including medical diagnostics and financial forecasting. Cross-cultural research, like that by Juslin et al. (2000), highlights the universality of this bias, though education and statistical training can mitigate its effects. These findings affirm the robustness and replicability of insensitivity to sample size as a pervasive human error.

Trivia Example: A famous example involves hospital birth data.

Kahneman and Tversky (1972) asked participants to evaluate whether a small hospital or a large hospital would be more likely to record a day where 60% of the newborns were male. Most participants incorrectly assumed that both hospitals had an equal likelihood, ignoring the fact that smaller samples are more prone to extreme deviations.

Selected References

Fiedler, K., & Juslin, P. (2006). Information sampling and adaptive cognition. Cambridge University Press.

Juslin, P., Winman, A., & Olsson, H. (2000). Naive empiricism and dogmatism in confidence research: A critical examination of the hard-easy effect. Psychological Review, 107(2), 384– 396.

Kahneman, D., & Tversky, A. (1972). Subjective probability: A judgment of representativeness. Cognitive Psychology, 3(3), 430–454.

Sedlmeier, P., & Gigerenzer, G. (2001). Teaching Bayesian reasoning in less than two hours. Journal of Experimental Psychology: General, 130(3), 380–400.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Business Example: In market research, insensitivity to sample size often leads to poor decision-making. For instance, a company may rely on the feedback of a small focus group to make critical product development decisions, assuming it reflects broader consumer sentiment. Research by Fiedler and Juslin (2006) illustrates how small-

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ILLICIT TRANSFERENCE Assuming that properties of the parts will transfer to the whole.

"You seem pleased," Ellie noted, "good news?"

"Yes, I got a call from John, remember him? He's working on a new startup. It's very intriguing. He offered me a chance to work with him," Rooney said, smiling.

"What do you think about it?"

"I'm considering giving it a try. I trust John; he wouldn't propose something he doesn't believe in. The company must be promising."

Ellie shook her head, "That's odd logic. Just because John is a good friend doesn't automatically make the company solid. It's like saying only worthless people work at a worthless firm... If I were you, I'd take a closer look and learn more about their operations. It's not that I have anything against John, but still…"

"You're right," Rooney agreed, "I'll think it over."

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misinterpretations of the slogan as “Pepsi brings your ancestors back from the dead.” Research by Henseler et al. (2015) illustrates how contextspecific adaptations are crucial to avoid such pitfalls.

About: Illicit transference refers to a cognitive bias where individuals improperly transfer or generalize evidence or reasoning from one context to another, often leading to flawed conclusions. This bias occurs when people assume that the attributes or principles of one domain directly apply to another without considering contextual differences. Illicit transference often results from oversimplification and a lack of critical evaluation, playing a significant role in errors across fields such as education, law, and business decision-making.

Reproducibility: Illicit transference has been consistently validated in experimental studies. Kahneman and Lovallo (1993) demonstrated this bias in risk assessments, where participants overgeneralized decision-making strategies across distinct contexts. Additional research by Gilovich et al. (2002) confirmed the bias in causal reasoning, showing that people often assume correlations in one domain apply universally.

More recent studies, such as those by Henseler et al. (2015), extend these findings to applied settings, emphasizing the importance of context in marketing and organizational strategy. These replications highlight the bias’s robustness and universality across domains.

Trivia Example: An example of illicit transference is the belief that a successful entrepreneur in one industry will automatically succeed in another, unrelated field. This assumption neglects contextual differences, such as market dynamics and industry-specific expertise. Research by Kahneman and Lovallo (1993) highlighted this bias in decision-making, noting how overconfidence in transferable skills leads to risky business expansions or investments.

Selected References

Gilovich, T., Griffin, D., & Kahneman, D. (2002). Heuristics and biases: The psychology of intuitive judgment. Cambridge University Press.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.

Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk taking.

Management Science, 39(1), 17–31.

Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Business Example: Illicit transference is commonly seen when companies assume that a successful campaign in one demographic will yield the same results in another without adapting the message to cultural or social nuances. For instance, Pepsi’s “Come Alive” campaign was successful in English-speaking markets but failed in China due to translation issues, leading to

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LAW OF THE INSTRUMENT An over-reliance on a familiar tool or methods, ignoring or under-valuing alternative approaches.

"If all you have is a hammer, everything looks like a nail."

"So, were my ideas helpful for rewriting your physics project?" Rooney asked. "Really helpful, I'm grateful," Ellie responded, "but I'm up against a deadline, and you sent me all the revisions in LaTeX instead of just adding comments to my Word document.

Now it's going to take me ages to sort through it!"

"You know I don't use the Word."

"I know, but you can work in the Word. You could've made an exception for me."

"No way, I love my LaTeX and I'm not changing my habits, not even for you!" Rooney declared.

"Alright, fine. Anyway, thanks! I've printed the document and I'll start making corrections now. Thanks again!"

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Research by Nickerson and Zenger (2004) shows that such bias can stifle innovation and lead to suboptimal performance. Similarly, companies overly reliant on cost-cutting strategies may fail to recognize opportunities for growth and investment.

About: The law of the instrument, also known as Maslow’s hammer, describes a cognitive bias where individuals rely too heavily on a familiar tool or approach, even when it is not the most appropriate solution. This phenomenon was first articulated by Abraham Maslow (1966), who noted, “If the only tool you have is a hammer, it is tempting to treat everything as if it were a nail.”

This bias highlights the tendency to apply familiar methods to diverse problems, often leading to oversimplified or ineffective solutions.

The law of the instrument is particularly prevalent in professional settings, where specialized expertise can limit openness to alternative approaches.

Reproducibility: The law of the instrument has been consistently observed across various contexts. Maslow’s (1966) original conceptualization has been validated by subsequent research, such as Kahneman’s (2011) work on cognitive biases and heuristics. Studies by Nickerson and Zenger (2004) demonstrated how this bias affects organizational strategy, while Gigerenzer and Gaissmaier (2011) explored its implications for decision-making under uncertainty. Crossdisciplinary research confirms its prevalence, highlighting the need for awareness of this bias in professional and personal decision-making.

Trivia Example: An example of the law of the instrument is seen in academic research. A scholar proficient in statistical modeling may attempt to apply quantitative methods to problems better suited to qualitative analysis, such as interpreting cultural narratives. Kahneman (2011) describes how reliance on habitual cognitive frameworks often constrains creative problem-solving.

Selected References

Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making.

Annual Review of Psychology, 62(1), 451–482.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux. Maslow, A. H. (1966). The psychology of science: A reconnaissance. Harper & Row. Nickerson, J. A., & Zenger, T. R. (2004). A knowledge-based theory of the firm: The problem-solving perspective.

Organization Science, 15(6), 617– 632.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Business Example: The law of the instrument often manifests in technology adoption. For instance, an IT department accustomed to using a specific software might apply it across all projects, even when alternative tools would be more effective.

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LOOK-ELSEWHERE EFFECT The error in data analysis that occurs when the significance of an observation is checked repeatedly until a statistically rare event appears to be significant.

At the entrance to Ellie's greenhouse, Rooney stumbled over a garden gnome, yet again.

"Listen," he said to Ellie, "can't we move this gnome somewhere else? I'm going to crack my head open on it someday."

"No way. He protects my plants from negative energy," Ellie declared.

"Are you serious?" Rooney's eyes widened.

"That's new to me. And does it work?"

"You know, I was skeptical at first too. For the first 3-4 months after I got him, nothing changed. But then my Pleione orchids blossomed. Ever since, my orchids have been thriving."

"Have you considered that it's not because of the gnome, but because you've gotten better at growing orchids? The connection between the gnome's arrival and the orchids blooming isn't exactly clear!"

"It might not be clear to you, but it is to me! It's been proven experimentally! So, the gnome stays right where he is!" Ellie insisted

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purchasing behavior purely by chance. Without statistical adjustments, such as Bonferroni corrections, these findings may lead to misguided strategies. Research by Ioannidis (2005) demonstrates the prevalence of false positives in large-scale data analyses, cautioning against overreliance on unadjusted exploratory findings.

About: The look-elsewhere effect refers to a statistical phenomenon in which the likelihood of observing a seemingly significant result increases as more hypotheses are tested. This effect often arises when researchers conduct multiple analyses or explore large datasets without adjusting for the increased probability of false positives. The look-elsewhere effect highlights the importance of statistical rigor in research design, particularly in disciplines such as physics, medicine, and psychology. First widely discussed in the context of particle physics, the effect emphasizes the dangers of overinterpreting results that appear significant only by chance due to multiple comparisons.

Reproducibility: The look-elsewhere effect is well-documented and reproducible across various disciplines.

Gross and Vitells (2010) rigorously demonstrated its impact in high-energy physics, highlighting how multiple testing inflates false- positive rates.

Ioannidis (2005) extended these findings to medical research, where exploratory studies often produce spurious associations due to inadequate statistical controls. The replicability of this effect in diverse domains reinforces the need for robust statistical methodologies to minimize false discovery rates and ensure the reliability of research conclusions.

Trivia Example: A notable example is the discovery of the Higgs boson particle at CERN. Physicists accounted for the look-elsewhere effect by setting stringent statistical thresholds to ensure the observed signal was not a false positive resulting from numerous analyses conducted across the dataset (Gross and Vitells, 2010). This rigorous approach helped confirm the particle’s existence with high confidence.

Selected References

Gross, E., & Vitells, O. (2010). Trial factors for the look elsewhere effect in high energy physics. The European Physical Journal C, 70(1), 525–530.

Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2(8), e124.

Miller, J. (1981). Significance tests in exploratory multiway contingency tables: Bonferroni adjustments and the number of tables. Psychometrika, 46(4), 531–536.

Business Example: The look-elsewhere effect frequently manifests in marketing analytics. For instance, businesses analyzing extensive customer data may identify correlations between certain demographics and

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OBSERVER-EXPECTANCY EFFECT When a researcher's cognitive bias causes them to unconsciously influence the participants of an experiment.

"Thanks for joining me today to teach a math lesson at my nephew's kindergarten," Ellie said, pleased. She had agreed long ago to visit the kindergarten to share something interesting with the children but had been putting off the lesson.

"It was my pleasure. The girls did great. They quickly grasped how to add numbers and easily outdid the boys. I've always said girls are more adept at math than boys."

"Actually, I wanted to talk to you about that.

Isn't that a bit sexist? First, it was wrong to split the children into groups of girls and boys. Second, you helped the girls more, so your 'experiment' was skewed. You influenced the outcome."

"I thought all the kids were happy… I didn't see it from that perspective and honestly didn't notice if I was helping the girls more.

Maybe it was subconscious. I wasn't analyzing myself at that moment," Rooney pondered. "You know, we promised to come back. Next time, let's split them into random, mixed groups, and I solemnly promise not to help anyone. Deal?"

"Deal!"

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About: The observer-expectancy effect, also known as experimenter bias, occurs when a researcher’s expectations unconsciously influence the outcomes of a study. This bias can manifest through subtle cues, such as tone of voice or body language, inadvertently guiding participants toward expected results. First highlighted by Rosenthal (1966) in his pioneering work on interpersonal expectations, this phenomenon shows the importance of maintaining objectivity in research. The observer-expectancy effect poses a significant threat to scientific validity, particularly in social and medical sciences where human interaction is inherent.

Reproducibility: The observer-expectancy effect has been consistently validated in controlled experiments. Rosenthal and Fode’s (1963) studies demonstrated that experimenter expectations could influence the behavior of animal and human subjects alike. This effect has since been replicated across domains, including education, where teacher expectations significantly impact student performance (Rosenthal and Jacobson, 1968). More recent research, such as that by Gilder and Heerey (2018), highlights the ongoing relevance of this bias in modern research and organizational contexts, emphasizing the need for rigorous methodological safeguards like double-blind designs to mitigate its influence.

Trivia Example: A classic example is the “Clever Hans” effect. A horse named Clever Hans was believed to perform arithmetic by tapping its hoof. However, subsequent investigations revealed that Hans was responding to subtle, unintentional cues from his handler rather than solving the problems independently (Pfungst, 1911). This incident exemplifies how observer expectations can influence behavior, even in non-human subjects.

Selected References

Baltes, B. B., Bauer, C. C., & Frensch, P. A. (2007). Does the observer- expectancy effect influence performance ratings? Journal of Applied Psychology, 92(1), 125–136.

Gilder, T. S. E., & Heerey, E. A. (2018). The role of experimenter belief in social priming. Psychological Science, 29(3), 403– 417.

Pfungst, O. (1911). Clever Hans (the horse of Mr. von Osten): A contribution to experimental animal and human psychology. Henry Holt.

Rosenthal, R. (1966). Experimenter effects in behavioral research.

Appleton- Century-Crofts.

Rosenthal, R., & Fode, K. (1963). The effect of experimenter bias on the performance of the albino rat. Behavioral Science, 8(3), 183–189.

Rosenthal, R., & Jacobson, L. (1968). Pygmalion in the classroom.

Urban Review, 3(1), 16–20.

Business Example: The observer-expectancy effect is evident during employee performance reviews. Managers who hold preconceived expectations about an employee’s capabilities may unconsciously communicate these biases, influencing how the employee performs during evaluations or feedback sessions. Research by Baltes et al. (2007) shows that such biases can skew performance assessments, leading to inequitable workplace outcomes.

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OUTCOME BIAS Judging a decision based on its eventual outcome instead of based on the quality of the decision at the time it was made.

With those words, Rooney darted onto the highway, pedaling furiously against the traffic. Ellie's heart raced with fear; any moment, a car could appear. The road climbed uphill, and soon Rooney vanished from sight. Minutes later, to everyone's shock, Rooney reappeared, still in the middle of the road. Suddenly, a huge truck loomed behind him.

Rooney surged forward, increasing his speed downhill. The truck, without slowing down, blared its horn – the distance between Rooney and the truck closing by the second.

The crowd, including the dark-haired guy, fell silent. A girl even closed her eyes.

Rooney pedaled with all his might, and just as the truck nearly caught up, he swerved off the road right by the crowd, to loud cheers and applause. The truck thundered past. The boys and girls surrounded Rooney, congratulating him and patting him on the back. The dark-haired guy extended his hand to Rooney, saying, "Bro, that was insane, didn't expect that!"

"What was that?" Ellie sternly asked as they headed home. "Just a bet, that's all!"

"Some bet? Do you realize you were lucky to survive?"

"I did survive, didn't I?" Rooney smirked.

"You think winners aren't judged?" Ellie snapped.

"That was incredibly stupid. And until you understand that, don't call me," she said, striding towards her house.

From a distance, Ellie spotted Rooney sitting on his bicycle, arguing loudly with a darkhaired guy at the roadside. The guy, surrounded by about fifteen friends, both boys and girls, was shouting something at Rooney. Ellie moved closer to hear better.

"You think I can't do it?" she heard Rooney say.

"Watch this!"

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organizations to reward luck over skill, perpetuating ineffective practices and poor decision-making cultures. Additionally, outcome bias can undermine learning, as failures that stem from rational decisions are often dismissed without proper analysis.

About: Outcome bias refers to the tendency to judge the quality of a decision based on its outcome rather than the reasoning or process used to arrive at that decision. This bias disregards the role of chance and external factors in determining results, often leading to an unfair evaluation of decision-makers. Baron and Hershey (1988) formally explored this phenomenon, showing how individuals retroactively attribute success or failure to the quality of decisions, even when outcomes were influenced by randomness or unforeseen events. Outcome bias is particularly problematic in fields like healthcare, law, and management, where decisions often involve significant uncertainty.

Reproducibility: Outcome bias has been extensively validated in experimental studies. Baron and Hershey’s (1988) experiments demonstrated the bias in healthcare scenarios, where participants evaluated a physician’s decisions more harshly when the outcome was negative, irrespective of the soundness of the decision. These findings have been replicated across various domains, including finance and legal judgments (Sezer et al., 2016). Research also highlights cultural consistency in this bias, though its magnitude may vary depending on societal attitudes toward risk and accountability.

Trivia Example: A famous example of outcome bias is evident in sports. A coach who takes a high-risk strategy that fails is often criticized, regardless of whether the decision was rational given the available information. Conversely, successful risky plays are celebrated, even if they were statistically unwise (Kolar et al., 2025). This tendency to overvalue outcomes shapes public perceptions of competence in sports and beyond.

Selected References

Baron, J., & Hershey, J. C. (1988). Outcome bias in decision evaluation. Journal of Personality and Social Psychology, 54(4), 569–579.

Denrell, J., & March, J. G. (2001). Adaptation as information restriction: The hot stove effect. Organization Science, 12(5), 523–538.

Kolar, E., Biloslavo, R., Pišot, R., Veličković, S., & Tušak, M. (2025). Conceptual framework of coaches’ decisionmaking in conventional sports. Frontiers in Psychology, 15, Article 1498186.

Sezer, O., Zhang, T., Gino, F., & Bazerman, M. H. (2016). Overcoming the outcome bias: Making intentions matter. Organizational Behavior and Human Decision Processes, 137, 13–26.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Business Example: Outcome bias can distort performance reviews.

For instance, a manager who takes a calculated risk that fails may be viewed less favorably than a manager whose uncalculated gamble succeeds.

Research by Denrell and March (2001) demonstrates that this bias can lead

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PLANNING FALLACY The tendency to underestimate the time, costs, and risks of future actions and overestimate the benefits.

In the evening, as was his routine, Rooney stopped by to pick up Ellie, so they could head to the gym together.

"Listen, I've been meaning to ask you," he said as they stepped outside, "have you completed your physics project? Or at least made a start?"

Ellie's expression turned gloomy, and she replied in a dull voice, "That project's due next Monday. There’s still time! I planned to work on it over the weekend."

Rooney responded, "Well, today's already Tuesday – you should get started on it right away. How exactly do you plan to finish the entire project in just a weekend?"

"Can’t you help me with it?"

"I can, but remember last time? I worked nonstop for three days to help you with your previous project. I'm not prepared to lose 72 hours of sleep again. So, we'll start working on your project after our training session today."

"But..."

"No 'buts'. If you argue, I won't help."

"Alright," Ellie said irritably, "we'll start today."

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estimates. This bias not only increases costs but also harms stakeholder confidence.

About: The planning fallacy refers to the tendency of individuals and organizations to underestimate the time, costs, or resources required to complete a task, even when they have previous experience with similar projects. First identified by Kahneman and Tversky (1979), the bias is driven by an overemphasis on optimistic scenarios and a failure to account for potential setbacks or complexities. This cognitive bias affects personal decision-making, project management, and public policy, often leading to delays, budget overruns, and unmet expectations.

Reproducibility: The planning fallacy has been extensively replicated across diverse contexts. Kahneman and Tversky’s (1979) initial experiments demonstrated its prevalence in individual decision-making, while Buehler et al. (1994) confirmed its persistence in collaborative and group settings. Cross-cultural studies, such as those by Roy et al. (2005), further validate the bias, indicating its universality. Research also highlights that interventions, such as “reference class forecasting,” which involves comparing projects to historical data, can reduce the bias’s impact (Flyvbjerg, 2009).

Trivia Example: One of the most cited examples of the planning fallacy is the construction of the Sydney Opera House. Initially projected to take four years at a cost of AUD 7 million, the project ultimately required 14 years and cost AUD 102 million (Flyvbjerg, 2009). This case illustrates how underestimating unforeseen challenges and risks can result in significant overruns.

Selected References

Buehler, R., Griffin, D., & Ross, M. (1994). Exploring the “planning fallacy”: Why people underestimate their task completion times. Journal of Personality and Social Psychology, 67(3), 366–381.

Buehler, R., Peetz, J., & Griffin, D. (2010). Planning for the near and distant future: How does temporal distance affect task completion predictions? Journal of Experimental Social Psychology, 46(5), 709–720.

Flyvbjerg, B. (2009). Survival of the unfittest: Why the worst infrastructure gets built—and what we can do about it.

Oxford Review of Economic Policy, 25(3), 344–367.

Kahneman, D., & Tversky, A. (1979). Intuitive prediction: Biases and corrective procedures. TIMS Studies in Management Science, 12, 313–327.

Roy, M. M., Christenfeld, N. J., & McKenzie, C. R. (2005).

Underestimating the duration of future events: Memory incorrectly used or memory bias? Psychological Bulletin, 131(5), 738–756.

Business Example: The planning fallacy is pervasive in corporate environments, particularly in IT and software development. For example, ambitious deadlines for large-scale digital transformation projects often fail due to unexpected technical challenges or underestimated resource needs. Research by Buehler et al. (2010) demonstrates that teams consistently underestimate project durations, even when given incentives to provide accurate

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SURROGATION Losing sight of the strategic construct that a measure is intended to represent, and subsequently acting as though the measure is the construct of interest.

"I looked at the statistics from our last robotics exhibition," Rooney said, "Can you believe that only 100 people visited our booth over two days? That seems low. Maybe we shouldn't participate in these exhibitions."

Ellie encouraged him, "I think we should focus not on the number of visitors but on how many people applied to join our club. I understand the importance of statistics, but I feel like you're replacing the exhibition's actual purpose with visitor numbers. Your goal isn't just to showcase our booth to as many people as possible, right? At least, it shouldn't be the main objective."

"You're right. As a result of the exhibition, we gained 8 new sponsors and 60 people joined the club."

"That's fantastic! It means the exhibition was a success. You interacted with a hundred visitors, and more than half of them wanted to join the club, plus we even found sponsors!"

"You're right, I should focus on the quality of the interactions, not just the quantity."

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firms that excessively focus on surrogate metrics often undermine their broader strategic goals, such as customer satisfaction and brand equity, due to misplaced priorities.

About: Surrogation refers to the cognitive tendency to substitute a performance metric for the broader goals it is intended to measure. Over time, individuals and organizations may conflate the metric with the underlying objective, focusing excessively on optimizing the metric rather than achieving the true goal. First explored by Kerr (1975) in his analysis of organizational behavior, surrogation often results in distorted priorities and unintended consequences, particularly in high- stakes environments such as business management, education, and healthcare.

Reproducibility: Surrogation has been consistently validated across various domains. Kerr’s (1975) foundational research on the folly of rewarding A while hoping for B demonstrated its prevalence in organizational contexts. Choi et al. (2013) extended these findings, showing how surrogate metrics distort strategic decision-making in firms. More recently, research by Likierman (2020) highlighted the persistence of surrogation in leadership evaluations, emphasizing the challenge of aligning metrics with true organizational objectives.

Trivia Example: A classic example of surrogation is the widespread use of standardized test scores in education. Originally intended as proxies for assessing student learning, these scores have become the primary focus of many schools. This shift often leads to “teaching to the test,” where broader educational goals, such as critical thinking and creativity, are neglected in favor of optimizing test performance (Koretz, 2005).

Selected References

Choi, S., Hecht, G., & Tayler, W. B. (2013). Lost in translation: The effects of incentive compensation on strategy surrogation. The Accounting Review, 88(1), 327–357.

Kerr, S. (1975). On the folly of rewarding A, while hoping for B. Academy of Management Journal, 18(4), 769–783.

Koretz, D. M. (2005). Alignment, high stakes, and the inflation of test scores. Yearbook of the National Society for the Study of Education, 104(2), 99–118.

Likierman, A. (2020). The metrics trap: Why executives get it wrong. Harvard Business Review, 98(3), 82–91.

Marr, B. (2012). Key performance indicators: The 75 measures every manager needs to know. Financial Times/Prentice Hall.

Business Example: Surrogation is frequently observed in the use of financial metrics like quarterly earnings. For instance, managers may prioritize short-term cost-cutting to meet earnings targets, even at the expense of long-term innovation and growth.

Research by Choi et al. (2013) highlights how

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WEBER-FECHNER LAW The principle describing the relationship between stimulus and perception, such as the logarithmic relation between stimulus intensity and sensation.

"Hi, Rooney," Ellie greeted, seeing him on the street. "How was Samantha’s party last night?"

"It was a bit of a letdown. You’re lucky you didn’t go. Can you believe her neighbor came over twice to complain about the noise? After his first visit, we turned the music way down, but it didn’t help. He came back again. We practically had to turn the music off... So, the whole vibe was ruined," Rooney sighed.

"I see, but the music probably did seem loud to him." "What do you mean?"

"Well, think about it. If you initially played the music loudly and then only turned it down a little, you’d feel the difference between what it was and what it became. But Samantha's neighbors probably didn't feel much change."

"Why’s that?"

"Because compared to silence, the music still sounded loud to them. So, the neighbor probably didn’t mean to ruin your evening on purpose."

"You're probably right. But still, the party was a flop."

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discounts that emphasize the relative size of savings. Research by Chandon et al. (2009) highlights how consumer perceptions of value are shaped by such sensory and cognitive biases.

About: The Weber-Fechner law describes the relationship between the physical magnitude of a stimulus and its perceived intensity. Specifically, it posits that the perceived change in a stimulus is proportional to the logarithm of its actual magnitude. First articulated by Ernst Weber and later refined by Gustav Fechner in the mid-19th century, this principle provides a foundational understanding of human sensory perception. It explains why incremental changes are more noticeable at lower intensities but harder to detect as the baseline intensity increases, and it is applicable across various sensory modalities such as vision, hearing, and touch.

Reproducibility: The Weber-Fechner law has been robustly validated across numerous experiments and sensory domains. Weber’s (1834) initial studies on weight perception demonstrated the proportional relationship between stimulus change and detectability, findings later generalized by Fechner (1860) to other sensory modalities. Subsequent research, such as that by Teghtsoonian (1971), replicated these effects across cultural and environmental contexts, confirming their universality. While the exact parameters vary between individuals and settings, the core principles of the law remain highly reproducible and widely applicable.

Trivia Example: An everyday example of the Weber-Fechner law occurs in sound perception. A person can easily detect the addition of a single decibel to a quiet room but may struggle to notice the same increment in a noisy environment. This phenomenon is why sound engineers carefully manage audio levels to achieve perceptible differences without distortion (Zeng, 2020).

Selected References

Chandon, P., Morwitz, V. G., & Reinartz, W. J. (2009). Do intentions really predict behavior? Self-generated validity effects in survey research. Journal of Marketing, 73(1), 1–14.

Fechner, G. T. (1860). Elemente der Psychophysik [Elements of psychophysics]. Breitkopf und Härtel.

Teghtsoonian, R. (1971). On the exponents in Stevens’ law and the constant in Ekman’s law. Psychological Review, 78(1), 71–80.

Weber, E. H. (1834). De pulsu, resorptione, auditu et tactu: Annotationes anatomicae et physiologicae. C. F. Koehler.

Zeng, F.-G. (2020). A unified theory of psychophysical laws in auditory intensity perception. Frontiers in Psychology, 11, Article 1459.

Business Example: The Weber-Fechner law is particularly relevant in pricing strategies. For instance, a $10 discount on a $20 product feels more substantial than the same discount on a $200 product, even though the absolute value is identical. This principle guides marketing tactics, such as offering tiered

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DENOMINATION EFFECT The tendency to spend more money when it is denominated in small amounts (e.g., coins) as opposed to large amounts (e.g., bills).

I’m really thirsty. I'm going to buy some water."

A few minutes later, Rooney returned with two bottles of water in hand, only to find that Ellie was no longer on the bench. He looked around, but Ellie was nowhere to be seen among the bustling shoppers. Sitting down on the bench and opening a bottle, he took a sip of water. That’s when he spotted Ellie. She was coming out of a nearby store.

"Ah, there you are!" she exclaimed. "Listen, I found such a cool T-shirt in there!Can you lend me some money?"

Rooney was about to protest that they had agreed to meet at the bench, that it was time to end this endless shopping, and that Ellie had just left that very store without buying anything; but experience told him it would be a waste of time.

Instead, he reached into his pocket. He had broken the fifty when he bought the water, but after rummaging in his pockets, he found forty dollars in tens and another ten in change. He handed it all to Ellie and grumbled, "Here. But I’m not going into the store. I’ll wait here."

It was over an hour before Ellie emerged from the store. Her face was radiant, and she was carrying a large paper bag.

"Thanks!" she said, smiling. "I bought so much – there was a sale on T-shirts!

But I don’t have any change left. I spent it all."

"I figured," Rooney sighed, "why am I not surprised?"

"Thanks," Ellie said, handing Rooney a fiftydollar bill, "I didn't end up needing it. I changed my mind about buying that Tshirt. But thanks for lending it to me anyway."

"I get it," Rooney replied grimly. He hated shopping and was annoyed that Ellie had dragged him to the mall after their workout. "Just sit here, near this vending machine," he instructed. "I’ll be right back.

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particularly in impulse purchases and smallticket items. Similarly, credit card companies capitalize on the denomination effect by offering small monthly payment options, making large purchases seem more manageable and encouraging higher spending.

About: The denomination effect is a cognitive bias where people are more likely to spend large sums of money when the amount is presented in smaller denominations (e.g., $100 bills) rather than in a single large amount (e.g., a $1000 bill). This bias occurs because smaller denominations feel less “real” and psychologically less painful to part with, making individuals more willing to spend.

The effect was first studied by Thaler (1985), who found that people tend to focus more on the number of units in a denomination rather than the overall value. This bias has implications for consumer behavior, financial planning, and retail strategies.

Reproducibility: The denomination effect has been consistently replicated in both laboratory and field settings.

Thaler’s (1985) foundational work on mental accounting provided the basis for later studies, including those by Prelec and Loewenstein (1998) and Thomas and Morwitz (2005), which showed the effect’s robustness in consumer spending and decision-making. These studies have been extended in contemporary research, such as those by Kim and colleagues (2009), who confirmed the phenomenon in online shopping environments. Despite some variations in the magnitude of the effect depending on context and individual differences, the core principle remains reproducible across various domains.

Trivia Example: An example of the denomination effect can be observed when individuals use coins instead of a $20 bill for smaller purchases. Despite the total amount being the same, people feel more comfortable spending the coins on multiple small items. Research by Prelec and Loewenstein (1998) demonstrates how individuals treat small amounts of money, such as coins, as “disposable,” even if they are equal to larger amounts in paper currency.

Selected References

Kim, K., Lee, H., & Park, J. (2009). The denomination effect in online shopping: A field study. Journal of Consumer Research, 36(4), 561–573.

Prelec, D., & Loewenstein, G. (1998). The red and the black: Mental accounting of savings and debt. Marketing Science, 17(1), 4–28.

Thomas, M., & Morwitz, V. G. (2005). Penny wise and pound foolish: The effects of price format on price perceptions and purchase intentions. Journal of Consumer Research, 32(1), 1–13.

Thaler, R. H. (1985). Mental accounting and consumer choice.

Marketing Science, 4(3), 199–214.

Thomas, M., & Morwitz, V. G. (2005). Penny wise and pound foolish: The effects of price format on price perceptions and purchase intentions. Journal of Consumer Research, 32(1), 54-64.

Business Example: The denomination effect influences purchasing behavior, particularly in the context of sales and pricing strategies. For example, stores may price items at $9.99 instead of rounding up to $10, as consumers perceive the smaller denomination as a better deal. Research by Thomas and Morwitz (2005) highlights how businesses strategically use this effect to increase consumer spending,

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DISPOSITION EFFECT The tendency to sell an asset that has accumulated in value and resist selling an asset that has declined in value.

"Is everything okay?" Rooney noticed that Ellie seemed upset. "Did something happen?"

"No, it's nothing," she replied, "just had an argument with my dad." "About what?"

"He recently invested in some stocks, and naturally, some have gone up in value while others have dropped."

"So far, so logical," Rooney listened very attentively.

"Well, get this – he's planning to sell the assets that have increased in value and keep the ones that have dropped. But that's absurd!

Why get rid of assets that are appreciating?"

Rooney smiled, "I think I understand what's happening here," he said. "Investors are often taught to 'buy low, sell high.' In many cases, this makes sense. For example, when you believe a stock has reached its peak and won’t rise further. Then, of course, you should sell. But blindly following this rule is indeed foolish. If the assets are promising and likely to grow in the future, it’s better to hold onto them, not discard them."

"You're right, but my dad is so stubborn, you can’t change his mind."

"Do you want me to try talking to him?" Rooney offered.

"I don’t think it'll help, but you can try. Maybe you'll have better luck," Ellie said, thoughtful.

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(2006) found that when firms were faced with losing investments, managers often resisted selling or cutting back on those investments due to an emotional attachment to the original decision, leading to inefficiencies and financial loss.

About: The disposition effect refers to the cognitive bias where investors are more likely to sell assets that have increased in value while holding onto assets that have decreased in value, despite the rational strategy being to sell losing investments and hold onto winning ones. This bias, first identified

by Shefrin and Statman (1985), can be explained by the emotional pain of realizing a loss and the tendency to want to “break even.” The disposition effect can lead to suboptimal investment decisions, such as failing to cut losses or missing out on further gains by holding onto losing positions too long. The effect has been widely studied in financial markets, demonstrating its persistent influence on investor behavior.

Reproducibility: The disposition effect has been widely replicated across a range of markets and investors. Shefrin and Statman’s (1985) original work demonstrated the bias in a study of individual investors’ behavior in the stock market. Subsequent studies, such as those by Odean (1998), replicated the effect in real-world trading data, confirming that investors are more likely to sell assets that have appreciated in value while holding onto those that have declined. Further research by Barberis et al. (2001) and Frazzini (2006) has extended these findings across different contexts, including mutual fund investors and institutional investors. While the magnitude of the effect can vary depending on factors such as experience and risk tolerance, the general tendency to sell winners and hold losers remains a robust and replicable phenomenon in financial markets.

Trivia Example: An example of the disposition effect can be seen in individual stock traders. A retail investor may hold onto a stock that has performed poorly, hoping for a rebound, while quickly selling off stocks that have appreciated in value to lock in the gains. Research by Odean (1998) found that individual investors were more likely to sell stocks that had gained value, while holding onto stocks that had lost value, thus preventing their portfolios from maximizing long-term returns.

Selected References

Barberis, N., Shleifer, A., & Vishny, R. W. (2001). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343.

Frazzini, A. (2006). The disposition effect and underreaction to news. Journal of Finance, 61(4), 2017–2046.

Hossain, T., & Morgan, J. (2006). …and the winner takes it all: Strategic behavior in winner-take-all markets.

Management Science, 52(12), 1818–1832.

Odean, T. (1998). Are investors reluctant to realize their losses?

The Journal of Finance, 53(5), 1775–1798.

Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence.

Journal of Finance, 40(3), 777–790.

Business Example: The disposition effect often manifests in the context of corporate decision-making. For instance, firms may be reluctant to abandon poorly performing projects due to the sunk cost fallacy, which is closely related to the disposition effect. Instead of cutting their losses and reallocating resources, companies may persist in underperforming initiatives, wasting valuable resources. Research by Hossain and Morgan 219

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ENDOWMENT EFFECT The theory that people value a good or service more highly when they own it than when they do not.

"How’s your robotics project coming along?

Finished?" Ellie asked. Rooney had been working on a robot for several weeks, disappearing into his attic for days on end immersed in this project.

"Not yet," he sighed. "You see, it needs parts, but they're expensive. I need to save up some money first."

"How much do you need?" Ellie wondered if she could help Rooney.

"About 400 to 500 dollars more."

"I see. Wait, what about selling something you don't need?" Ellie suggested. "Like what?"

Rooney asked.

"For instance... your Polaroid. You know, the vintage camera. You don't use it at all!"

"You mean my SX-70?" Rooney looked at Ellie in surprise. "Yeah."

"But I still need that. It's important to me."

"Hold on, you got it for free. You won it in a contest last year. Besides, you yourself said, 'What do I need this junk for?' 'What am I going to do with it?' 'Even for free, it's useless.' And those cameras now sell for 400-500 dollars, maybe even more. I saw it online recently," Ellie stated matter-offactly.

"500 dollars for an SX-70? That’s too little. It's a valuable item! No, I won't sell it.

I’ll find another way to earn the money for the robot parts."

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product as less valuable. This effect also influences organizational decision-making, where leaders might cling to outdated strategies or products simply because they are part of the company’s legacy, hindering innovation and progress.

About: The endowment effect is a cognitive bias where individuals assign higher value to objects they own than to identical objects they do not own.

This phenomenon occurs because ownership leads to a sense of attachment, and people are reluctant to part with things they possess, even when they may not be of intrinsic value.

Originally identified by Kahneman, Knetsch, and Thaler (1990), the endowment effect challenges the rational decision-making model, where value should theoretically be determined by market forces or utility. The bias has significant implications for consumer behavior, negotiation, and economics, often leading individuals to overvalue their possessions and make decisions based on emotional attachment rather than objective worth.

Reproducibility: The endowment effect has been robustly replicated across various settings and populations. Kahneman et al. (1990) first demonstrated the bias in a study involving coffee mugs, where participants who were given a mug valued it significantly higher than those who did not own it. This finding has been replicated in countless contexts, such as real estate (Gerardi and Shapiro, 2009), where homeowners often overestimate the value of their properties. More recent studies, like those by van Boven et al.

(2003), have extended the research, showing that the effect is not limited to physical objects but can also extend to abstract items, such as digital goods. These findings demonstrate the replicability of the endowment effect across different domains and highlight its broad applicability in both consumer behavior and economic theory.

Trivia Example: One example of the endowment effect occurs in the context of garage sales. Sellers often overprice items they no longer need, simply because they have owned them. A study by Kahneman et al. (1990) demonstrated that people are willing to sell goods for less when they do not own them, highlighting how ownership inflates perceived value. This bias also extends to less tangible assets, such as investments in time or effort, where individuals may overestimate the return on their personal investments.

Selected References

Gerardi, K. S., & Shapiro, A. H. (2009). Does the endowment effect occur in the housing market? Brookings Papers on Economic Activity, 2009(1), 195–230.

Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1990). Experimental tests of the endowment effect and the comparison of willingness to sell and willingness to buy. Journal of Political Economy, 98(6), 1325–1348.

Morewedge, C. K., Shu, L. L., Gilbert, D. T., & Wilson, T. D. (2009).

Bad riddance or good riddance? The effect of transitioning to a new product on the value consumers place on their old products. Journal of Consumer Research, 36(4), 664– 675. van Boven, L., Dunning, D., & Loewenstein, G. (2003). The illusion of invulnerability: The overconfidence bias and its implications for negotiation. Journal of Personality and Social Psychology, 85(2), 268–280.

Business Example: The endowment effect can impact pricing strategies and negotiations. A company may overvalue its products simply because it has invested significant resources into developing them, leading to inflated prices. Research by Morewedge et al. (2009) found that when consumers are given a product to hold, they tend to demand a higher price for it when it comes time to sell, even if they initially viewed the 221

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IKEA EFFECT The tendency for people to place a disproportionately high value on objects that they partially assembled themselves, regardless of the quality of the end result. practical, right? They must get dirty instantly. Maybe it's time to let them go."

"They're not horrible, Rooney!" Ellie retorted, clearly offended. "It's my personal creative design. I spent two days on them!"

"Sure, the 'paintwork of the century,'" Rooney said sarcastically. "But remember, there's a big purple stain on one of them."

"You don't get fashion," Ellie snapped. "That's what makes them unique." "Maybe fashion's not my forte, but I know business.

If you insist on selling them, you might need to drop the price."

"Just criticism, no help," Ellie sighed. "I won't sell my work short."

"Fine, I'll help you market them tomorrow. New photos, a new description.

Maybe then they'll sell."

The next day, Rooney helped Ellie revamp her eBay listing. They took artistic photos and crafted a compelling description: "Exclusive custom sneakers by upcoming designer Ellie W. Handcrafted, unique design. Oneof-a-kind city casual chic. Satisfaction guaranteed."

A week later, Rooney called Ellie on Friday night: "I noticed your sneakers are off eBay. Did you sell them?"

"No," Ellie's voice brimmed with happiness. "I didn't." "What happened? No interest?"

"On the contrary, I had 18 bidders. But then I thought, they're cool, they're mine.

I spent two days making them. So, I decided to keep and wear them myself."

"Hey, Ellie, what's up?" Rooney's voice was light and cheerful, typical for a Friday night with the weekend ahead.

"Just pondering the world's woes," Ellie replied, her mood not nearly as bright.

"What do you mean?" Rooney asked, puzzled.

"I've had my designer sneakers on eBay for four weeks now, and nobody's interested. I thought they'd be a hit..."

"Ah, those sneakers you painted with acrylic?

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merchandise or “build-your-own” kits for items like shoes or jewelry can increase consumer engagement and perceived value. Research by Morewedge et al. (2010) showed that companies leveraging the IKEA effect can foster a sense of ownership, which leads to greater customer satisfaction and loyalty, even if the custom products are not objectively superior.

About: The IKEA effect is a cognitive bias in which people place disproportionately high value on products they have partially created themselves, even if the final product is of lower quality compared to a professionally assembled version. Named after the Swedish furniture giant IKEA, which popularized the concept of flat-pack furniture, this bias is driven by the sense of achievement and personal involvement in the creation process. The IKEA effect highlights the powerful influence of effort and labor on perceived value, which can lead individuals to overestimate the quality of self-assembled products. This bias has significant implications in consumer behavior, marketing strategies, and decision-making processes.

Reproducibility: The IKEA effect has been widely replicated in experimental and applied research. Norton et al.

(2007) demonstrated the bias in a controlled setting, showing that participants who put together their own furniture valued it significantly higher than those who did not participate in the assembly. Similar studies by Morewedge et al. (2010) confirmed the effect in other contexts, including crafting and cooking.

The replicability of the IKEA effect is evident across different domains, with researchers finding it consistently applicable in various consumer behaviors, from simple DIY tasks to more complex product customization scenarios.

While the magnitude of the effect can vary depending on factors such as the complexity of the task and individual preferences, the general tendency to overvalue self-made products remains robust.

Trivia Example: The IKEA effect is seen in IKEA’s furniture products. Research by Norton et al. (2007) demonstrated that individuals who assembled their own IKEA bookshelf valued it significantly higher than those who purchased a preassembled version, even though both were of identical quality. This effect is not limited to physical products, as similar effects have been observed with DIY projects, where individuals often overestimate the quality of the work they perform, such as home improvements or homemade crafts.

Selected References

Morewedge, C. K., Huh, Y. E., & Vosgerau, J. (2010). Thought for food: Inappropriately perceived food as more desirable when it is self- prepared. Psychological Science, 21(8), 1277–1282.

Norton, M. I., Mochon, D., & Ariely, D. (2007). The IKEA effect: When labor leads to love. Journal of Consumer Psychology, 22(3), 453–460. van der Meer, E. (2020). The IKEA effect and product evaluation: The role of product involvement. International Journal of Consumer Studies, 44(5), 444–453.

Business Example: The IKEA effect can influence customer satisfaction and loyalty. Companies that allow customers to customize or build their own products may create a stronger emotional connection with the product. For example, online retailers offering personalized 223

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IRRATIONAL ESCALATION/ESCALATION OF COMMITMENT The phenomenon where people justify increased investment in a decision, based on the cumulative prior investment, despite new evidence suggesting that the decision was probably wrong.

"What's wrong this time?" Rooney asked, looking at Ellie, who was absorbed in her computer.

"Just drafting a schedule for my boss at work."

"Isn’t that a secretary’s job?" Rooney was surprised. "You were hired as a web designer intern!"

"I know, but I don’t really have a choice," Ellie sighed.

"What do you mean 'no choice'? There's always a choice," Rooney asserted confidently.

"And what would that be?"

"I think you just need to leave. Look, you’ve been interning at this company for a month, but you haven't worked on a single web design project. All I hear about is you making coffee, copying documents, writing meeting minutes, and now, scheduling for your boss... It's time to move on. You're not a secretary; you're a web designer."

"You're right, but I put so much effort into getting this internship... It was so competitive! I worked day and night. It feels like a waste to give it up now."

"But what are you really giving up? Think about it – if you're not growing as a web designer, then there's no point in staying there."

"You're right. I'll hand in my resignation tomorrow," Ellie said, closing her computer.

"That's the spirit! Let me help you find another internship."

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Kodak’s film-based products even as digital photography emerged. Research by Staw (1976) shows that companies often justify continued investment based on the rationale that discontinuing a project would waste the resources already spent, even if doing so would be the most rational decision.

About: Irrational escalation, also known as the sunk cost fallacy, refers to the tendency for individuals or organizations to continue investing in a failing project or endeavor due to the cumulative investments already made, rather than considering the future costs and benefits. People become emotionally attached to their investments, leading them to escalate their commitment despite mounting evidence that the decision is no longer rational. This bias often occurs in business, government, and personal contexts, where continued investment in poor decisions can lead to significant financial and resource losses. The concept was first explored by Staw (1976) and has since been widely examined in both behavioral economics and psychology.

Reproducibility: The phenomenon of irrational escalation has been widely studied and replicated in various experimental and real-world settings. Staw’s (1976) pioneering work on the sunk cost effect demonstrated how individuals tend to escalate their commitment to losing ventures. Further research, such as that by Arkes and Blumer (1985), confirmed the effect in both business and personal decision-making. More recent studies, such as those by Garland and Newport (1991), extended the findings to organizational behavior, showing how group dynamics can amplify the escalation of commitment. Despite differences in experimental settings and contexts, the core principle of irrational escalation has been robustly replicated across domains.

Trivia Example: One example of irrational escalation is the Concorde project, which involved a supersonic passenger aircraft developed by both the UK and France. Despite the project being over-budget and underperforming, the governments continued funding it due to the large investments already made. This decision led to further losses, as the aircraft ultimately failed to achieve commercial success. Research by Arkes and Blumer (1985) demonstrated how such biases can cloud judgment and lead to the continuation of unproductive endeavors.

Selected References

Arkes, H. R., & Blumer, C. (1985). The psychology of sunk cost.

Organizational Behavior and Human Decision Processes, 35(1), 124–140.

Garland, H., & Newport, S. (1991). Effects of absolute and relative sunk costs on the decision to persist with a course of action. Organizational Behavior and Human Decision Processes, 48(1), 55–69.

Staw, B. M. (1976). Knee-deep in the big muddy: A study of escalating commitment to a chosen course of action. Organizational Behavior and Human Performance, 16, 27–44 Tversky, A., & Kahneman, D. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Business Example: Irrational escalation often manifests in the form of “throwing good money after bad.” For example, companies may continue to fund failing marketing campaigns or product developments because of the sunk costs involved. A notable instance is the continued development of 225

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LOSS AVERSION The tendency to prefer avoiding losses to acquiring equivalent gains.

"What's happened this time?" Rooney noticed that Ellie was visibly upset. "I somehow managed to lose my wallet," she said sadly.

"Don't worry about it! How much money was in it?"

"About fifty bucks."

"And you're this upset over that?"

"I'm not devastated, but it's still a loss," Ellie replied, slightly offended.

"Here’s what we'll do – take this and don't fret over it!" Rooney handed her a fifty-dollar bill.

"Thank you!" Ellie sighed, taking the money. "But why the long face now?"

"It's still a shame about the wallet. Even though I only lost fifty bucks, it feels like I lost a hundred or more."

"Forget about it! Let’s go to the gym instead," Rooney suggested.

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likely to stick with the service due to the fear of losing money. Research by Prelec and Loewenstein (1998) confirmed that consumers perceive the potential loss of money from automatic charges as significantly more impactful than the benefit of gaining free service.

About: Loss aversion is a cognitive bias described by Kahneman and Tversky (1979) as the tendency for individuals to prefer avoiding losses rather than acquiring equivalent gains. This phenomenon is central to their prospect theory, which posits that losses are psychologically about twice as powerful as gains of the same size. Loss aversion explains many behaviors, including risk aversion, status quo bias, and reluctance to change. The concept suggests that people’s emotional reaction to losses far outweighs the joy of comparable gains, which can drive irrational decision-making and suboptimal choices, particularly in financial and consumer contexts.

Reproducibility: Loss aversion has been widely replicated in experimental and applied settings. Kahneman and Tversky’s (1979) initial experiments laid the foundation for understanding the psychological asymmetry between gains and losses.

Subsequent research, such as that by Tversky and Kahneman (1991), confirmed the robustness of this bias in various decision-making contexts, from investment behavior to consumer purchasing decisions. More recent studies, like those by Ert and Erev (2017), extended the findings to behavioral economics and marketing, demonstrating how loss aversion influences consumer choices and competitive strategies.

Despite some variation across cultures and individual differences, the basic principle of loss aversion remains highly replicable in different domains.

Trivia Example: One example of loss aversion is the reluctance to sell an underperforming stock. Investors often hold onto losing assets, hoping they will rebound, rather than realizing the loss and reinvesting in more promising opportunities.

Studies by Thaler (1980) show that people are often unwilling to realize losses on investments due to the psychological discomfort associated with acknowledging a loss, even when it is the rational decision to cut losses.

Selected References

Ert, E., & Erev, I. (2017). Loss aversion in decisions over time.

Journal of Economic Behavior & Organization, 133, 190– 207.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Prelec, D., & Loewenstein, G. (1998). The red and the black: Mental accounting of savings and debt. Marketing Science, 17(1), 4–28.

Thaler, R. H. (1980). Toward a positive theory of consumer choice.

Journal of Economic Behavior & Organization, 1(1), 39–60.

Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference-dependent model. Quarterly Journal of Economics, 106(4), 1039–1061.

Business Example: Loss aversion can be seen in the behavior of consumers, particularly in pricing strategies. For instance, companies often use “loss-framing” to encourage consumer action. A classic example is the subscription model, where consumers are given a “free trial” and then automatically charged if they do not cancel, making them more

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MONEY ILLUSION The tendency to concentrate on the nominal (face value) of money rather than its value in terms of purchasing power.

"What are you thinking about?" Rooney asked, sitting down next to Ellie, who was seated by a fountain in the park, absently touching the water.

"Just thinking about how odd today has been," she responded, still lost in thought. "I received my first month’s internship salary today. At first, I thought they paid me 2 percent less than promised, which naturally upset me. But then a colleague explained that I actually got a 2 percent raise due to a salary indexation in my department. Now, I guess I should be relieved, but it still feels strange. I feel like I should be happy, but I'm not really.”

Rooney smiled and said, "And rightly so. The inflation rate is at 4 percent, and you only got a 2 percent raise. But it's silly to worry about it. Let's go for a walk instead!"

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smaller nominal increase rather than the real value, may not perceive the higher cost in terms of their actual purchasing power. Research by Jäkel et al. (2017) demonstrates that money illusion influences both consumer spending and saving decisions, as well as businesses’ pricing strategies, particularly in the retail sector.

About: The money illusion refers to the tendency of individuals to think of currency in nominal rather than real terms. This bias leads people to focus on the face value of money rather than adjusting for inflation or changes in purchasing power. For instance, when individuals receive a salary increase, they may feel richer, even if inflation has eroded the real value of their income. Money illusion can significantly influence personal finance, consumer behavior, and economic policy, as it distorts decision-making and leads to suboptimal financial choices. The concept was first introduced by Fisher (1928), and subsequent research has shown that individuals often fail to account for changes in the real value of money, even when they are aware of inflation.

Reproducibility: The phenomenon of money illusion has been consistently replicated across various contexts and economic conditions. Fisher’s (1928) foundational research demonstrated how individuals neglect the impact of inflation in their financial decision-making. Subsequent studies, such as those by Shafir et al. (1997) and Jäkel et al. (2017), confirmed the persistence of money illusion in both personal and consumer behavior. More recent studies, including those by Thaler (1985) and Angner (2010), show that money illusion continues to play a role in how individuals assess value and make economic decisions, even in modern economies with complex financial systems.

Trivia Example: An example of money illusion can be seen during periods of inflation. For instance, if a person receives a nominal pay raise of 5% in a year when inflation is 6%, they may still feel a sense of improvement in their financial situation, even though their real purchasing power has actually decreased. Studies by Shafir et al. (1997) have shown that people are more likely to focus on the nominal increase and neglect the inflationary context.

Selected References

Angner, E. (2010). A course in behavioral economics. Palgrave Macmillan.

Fisher, I. (1928). The theory of interest: As determined by impatience to spend income and opportunity to invest it.

Macmillan.

Jäkel, F., Kühberger, A., & Jelicic, M. (2017). Money illusion: How the nominal value of money influences consumer behavior. Journal of Economic Psychology, 62, 88–98.

Shafir, E., Diamond, P., & Tversky, A. (1997). Money illusion. Quarterly Journal of Economics, 112(2), 341–374.

Thaler, R. H. (1985). Mental accounting and consumer choice.

Marketing Science, 4(3), 199–214.

Business Example: The money illusion can affect how consumers perceive prices and value. For example, during periods of high inflation, businesses may adjust the prices of products by increasing them nominally, but consumers, focused on the

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NOT INVENTED HERE A stance adopted by social, corporate, or institutional cultures that avoids using or buying already existing products, research, standards, or knowledge because of their external origins.

"No, I'm not buying this portable phone charger," Rooney said, putting the package back on the hook.

"Why not?" asked Ellie, curious. "What's wrong with it?"

"See, it says 'Made in China.' I don’t trust Chinese products."

Ellie looked at Rooney disapprovingly. "You're surprising me – that's such a silly thing to say. First of all, most branded products are made in China. Second, you just said a minute ago that you liked its price and how lightweight it is - it's convenient. And third, it's quite strange to distrust the quality just because it's made in China. It sounds like discrimination. I bet most of the clothes you're wearing right now were made in China."

"Alright, alright," Rooney conceded, waving his hands. "You've convinced me. Let's buy it! I really need a charger. My phone is always running out of battery."

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market, companies like Nokia and BlackBerry were slow to adopt touch-screen technology, which had been popularized by Apple. Research

by Madsen and Desai (2010) found that the NIH bias played a significant role in these companies’ reluctance to embrace innovations that were seen as coming from outside their established product development frameworks. As a result, both companies lost their market leadership positions.

About: The “Not Invented Here” (NIH) bias refers to the tendency for individuals or organizations to undervalue or reject ideas, products, or solutions that were developed externally, even if they are objectively superior. This bias is rooted in a sense of ownership and pride in one’s own creations, leading to a reluctance to adopt or trust outside innovations. NIH can manifest in various settings, such as in business, academia, and product development, where teams or leaders may dismiss external contributions in favor of their own solutions. The NIH bias can limit creativity, hinder collaboration, and lead to inefficiency, as it discourages the adoption of potentially beneficial innovations from outside sources. This phenomenon has been extensively studied in organizational behavior and management, with researchers exploring its impact on innovation and competitive advantage.

Reproducibility: The NIH bias has been widely studied and replicated in various organizational and decisionmaking contexts. Studies by Madsen and Desai (2010) and more recent research by Mahdad, and Roshani (2024) demonstrated that organizations are often hesitant to adopt external ideas, even when they are in clear need of innovation. This bias has been observed in both for-profit and nonprofit sectors, where teams or departments exhibit resistance to external ideas due to cultural and organizational factors. Furthermore, research by Krueger and Dickson (2009) highlighted the psychological underpinnings of NIH, showing how group dynamics and organizational identity can contribute to the phenomenon. Despite occasional cases of successful external innovation adoption, NIH remains a pervasive force in organizational culture, which often hinders progress and innovation.

Trivia Example: One example of the NIH bias can be found in the history of the medical field, particularly the initial resistance to hand-washing as a hygiene practice. Ignaz Semmelweis, a Hungarian physician in the 19th century, introduced handwashing in hospitals to prevent the spread of infections. Despite the overwhelming evidence supporting its effectiveness, his ideas were rejected by the medical community at the time, largely because they were perceived as coming from an outsider and contradicted established norms (Semmelweis, 1861). This resistance highlights the powerful influence of the NIH bias in even critical areas like healthcare.

Selected References

Krueger, J. I., & Dickson, D. M. (2009). The role of social identity in the ‘Not Invented Here’ effect. Journal of Applied Social Psychology, 39(8), 1961–1978.

Madsen, P. M., & Desai, V. (2010). The ‘Not Invented Here’ syndrome: An empirical test of the intergroup perspective. Journal of Product Innovation Management, 27(4), 537–551.

Mahdad, M., & Roshani, S. (2024). The open innovation kaleidoscope: Navigating pathways and overcoming failures. Review of Managerial Science, 19, 1637–1668.

Semmelweis, I. (1861). The etiology, concept, and prophylaxis of childbed fever. P. C. & G. Verlag.

Business Example: The NIH bias can prevent companies from adopting successful technologies or practices developed by competitors or external partners.

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PSEUDOCERTAINTY EFFECT The tendency to make risk-averse choices if the expected outcome is positive, but make risk-seeking choices to avoid negative outcomes.

"Ellie, what have you gotten yourself into now?"

Rooney complained, exasperated. "We agreed, no slot machines. You've already dragged me to this shopping mall. Stop playing. Let's go home before you lose all your money again."

"Just one more game, please. If I stop now, I'll lose 50 bucks." "How is that even possible?"

"What do you mean?"

"You just turned down a 1-dollar lottery ticket at the store for a chance to win a 10,000-dollar voucher, but here you are, ready to play away 50 dollars? So, when there's something to win, you don’t want to play, but when there's a chance of losing, you're all in? How much have you lost already?"

"I don't know, about 70 dollars…"

"It's time to stop!"

"But…" "I don't want to hear it! We're going home," Rooney said firmly.

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discount voucher that guarantees a small immediate reward, rather than an uncertain but larger potential reward, like a lottery. Research

by Köszegi and Rabin (2006) shows that consumers are often more likely to accept smaller, guaranteed rewards instead of taking a risk for a higher potential outcome. This bias can also explain why some investors prefer certain but lower returns over riskier assets that could potentially yield higher returns, leading to suboptimal portfolio management.

About: The pseudocertainty effect occurs when people overvalue outcomes that seem certain, even when the actual certainty is illusory or incomplete. Essentially, individuals act as though they are in a more certain situation than they are, focusing on certain gains or losses rather than considering the full range of possible outcomes. This bias arises when individuals are faced with risky choices and are presented with a “guaranteed” option in a scenario that ultimately involves uncertainty. First identified by Tversky and Kahneman (1981) in the context of decisionmaking under risk, the pseudocertainty effect plays a key role in shaping consumer behavior, financial decision-making, and insurance choices. It highlights how people tend to overestimate the security of seemingly guaranteed outcomes, leading to skewed decision-making.

Reproducibility: The pseudocertainty effect has been widely replicated in both laboratory and real-world settings. Tversky and Kahneman’s (1981) original study demonstrated how people consistently prefer certain gains, even when probabilistic options would result in a higher expected return.

Subsequent studies have reinforced these findings. For example, studies by Loomes and Sugden (1982) showed that participants in various economic decision-making tasks consistently overestimated certainty. More recent research by Gonzalez and Wu (1999) confirmed that the pseudocertainty effect is robust, even when participants are familiar with the underlying probabilities. This bias appears across cultures and is relevant in diverse domains, from financial decisions to healthcare choices, proving its replicability and widespread impact44o6n human behavior.

Trivia Example: An example of the pseudocertainty effect is the “Asian disease problem,” a thought experiment developed by Tversky and Kahneman (1981). In this experiment, participants were presented with two options for dealing with a hypothetical disease outbreak. In one condition, they were offered a certain outcome (saving 200 lives) and in another, a probabilistic option (a 1/3 chance of saving 600 lives). Despite both options being mathematically equivalent, participants preferred the certain gain, even though the probabilistic option offered a higher expected value. This illustrates how the illusion of certainty can lead people to make choices that do not maximize expected utility.

Selected References

Gonzalez, R., & Wu, G. (1999). On the shape of the probability weighting function. Cognitive Psychology, 38(1), 129-166.

Köszegi, B., & Rabin, M. (2006). A model of reference-dependent preferences. Quarterly Journal of Economics, 121(4), 1133– 1165.

Loomes, G., & Sugden, R. (1982). Regret theory: An alternative theory of rational choice under uncertainty. Economic Journal, 92(368), 805–824.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453–458.

Business Example: The pseudocertainty effect can influence investment and consumer decisions. For instance, in marketing, a company might offer a 233

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UNIT BIAS The standard suggested amount of consumption (e.g., food serving size) or unit of measure (e.g., a pair of shoes in a box) is perceived as the appropriate amount to use or consume. said Ellie, looking around. "Do you want to come with me? What's with the mess here?" The kitchen was in chaos. Oatmeal remnants were scattered on the floor, the kitchen table was smeared with something red, and children's toys were strewn everywhere.

"You see, my mom left me in charge of my little brother today. I turned away for just a minute, and he smeared everything with oatmeal, drew on the table with mom's lipstick, and scattered toys all over the place. Lucky he didn’t break anything. Mom took him out for a walk now, and I've got to clean up this mess. See how much work I have?" Rooney spread his arms to emphasize the scale of the disaster. "He even pulled out flour from the cupboard and spilled it, and then splashed juice all over the walls. I can't go anywhere until I clean it all up."

"I see," said Ellie. "Listen, that looks like a lot of work. Can't you just clean up half now and finish the rest after the park?"

"What do you mean 'half'?" Rooney was puzzled.

"Like, clean up the floor and wipe the table now, and leave the walls and furniture for later?"

Ellie suggested.

"No, that won't do. I need to clean the whole kitchen. I don’t like leaving things halfdone. Plus, mom would be upset if I only cleaned half of it. Sorry, but I have to stay and clean."

"Alright," Ellie replied, rolling up her sleeves. "Let me help you then. Otherwise, you’ll be scrubbing here till the evening!"

"Come in!" Rooney opened the door and let Ellie in. As usual, they headed to the kitchen.

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competitive. A study by Chandon et al. (2000) showed that consumers tend to buy larger units, such as jumbo sizes, because they believe it represents a better deal, even when it leads to wasteful over-purchasing. This behavior also affects product pricing strategies in retail, where smaller units might appear less valuable even when they are a better fit for consumers’ needs.

About: The unit bias refers to the cognitive tendency to view a single unit of something as the appropriate or optimal amount, regardless of its actual size or quantity. People tend to think that consuming or using one unit of a product is the ideal amount, whether the unit is a serving of food, a portion of a product, or even an abstract measure like a task or project. This bias can lead to overconsumption or inefficiency, as individuals overlook the total amount or benefits involved and focus instead on the simplicity of “one unit.” The concept was initially explored in the context of portion sizes in food consumption, but it has since been found to apply to a wide range of behaviors, from product purchases to organizational tasks (Vohs and Faber, 2007). Unit bias contributes to consumer behaviors and organizational inefficiencies by distorting perceptions of what is appropriate or needed.

Reproducibility: The unit bias has been consistently demonstrated in a variety of experimental settings. Vohs and Faber (2007) first identified the bias in food consumption contexts, showing that participants tend to eat a single portion, regardless of the portion size. Wansink et al.

(2006) replicated these findings in controlled dining settings, confirming that unit bias plays a significant role in food- related decisions.

Subsequent research has extended these findings into other domains, including consumer product purchases (Chandon et al., 2000) and organizational task management (Zhang and Fishbach, 2010), further reinforcing the robustness of the effect. Though its impact can vary based on context—such as the size of the unit or cultural differences in consumption—the fundamental tendency to overvalue a single unit remains highly replicable.

Trivia Example: The unit bias is seen in food consumption, where individuals are likely to consume an entire serving or portion, even if it is larger than necessary. For example, when given a large portion of food at a restaurant, individuals tend to finish the entire meal, even if they are no longer hungry. Research by Wansink et al. (2006) demonstrated that diners who were served larger portions ate more, showing that the mere presence of a unit can encourage consumption, regardless of satiety or need.

Selected References

Chandon, P., Wansink, B., & Laurent, G. (2000). A benefit congruency framework of sales promotion effectiveness.

Journal of Marketing, 64(4), 65–81.

Vohs, K. D., & Faber, R. J. (2007). Spent resources: Self-regulatory resource availability affects impulse buying. Journal of Consumer Research, 33(4), 537–547.

Wansink, B., Painter, J. E., & Lee, Y. K. (2006). The office candy dish: Proximity’s influence on estimated and actual consumption. International Journal of Obesity, 30(5), 871–875.

Zhang, Y., & Fishbach, A. (2010). The “unit bias” effect: People’s decisions are influenced by a simple unit. Psychological Science, 21(1), 27–32.

Business Example: The unit bias can influence purchasing decisions, particularly in retail and consumer products. For example, consumers may perceive bulk purchases or “family-size” products as a better value, simply because the packaging offers a single unit of a product in a larger quantity, even though the price per unit may not be as 235

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PART 4 DECISION MAKING

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BELIEF IS REALITY

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BACKFIRE EFFECT When people react to disconfirming evidence by strengthening their beliefs.

"Hi, I'm going to the store today for canvases and drawing boards. Can you help me? Come with me? I'm afraid I won't be able to carry it all by myself."

"Okay, but on one condition: we're not going into any other stores. You know how I am with shopping – like a bull seeing red."

"Deal! Thanks! But about the bulls, you're wrong," Ellie said with a smile.

"What do you mean 'wrong'?" Rooney, still groggy and not in the best mood, asked.

"Literally wrong. Bulls don't react to the color red. They can't even distinguish red-green shades!"

"Nonsense! Of course, they can," Rooney interrupted. "Matadors always wave red capes at them. I saw it myself when I visited my father’s relatives in Spain."

"You're so clueless," Ellie continued, amused that Rooney took her comment so seriously. "Bulls react to the movement, not the color. They get angry because the cape is moving, not because of its color."

"They react to the color. I've seen it with my own eyes," Rooney insisted.

"If you don't believe me, look it up in any encyclopedia," Ellie didn't give up.

"I won’t bother. I trust my eyes. Anyway, I’ll pick you up in an hour." Rooney hung up, rubbed his eyes, and stretched, ready to finally wake up.

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brand were more likely to interpret negative information as biased or inaccurate, further entrenching their allegiance to the brand. This phenomenon can hinder companies’ efforts to address issues or repair damaged reputations (e.g., Swire-Thompson et al., 2020).

About: The backfire effect refers to a cognitive bias in which people strengthen their existing beliefs when presented with information that contradicts them, rather than changing their views in response to the new information. This phenomenon is particularly pronounced in politically charged or emotionally significant topics, where individuals may react defensively to facts or arguments that challenge their opinions. The backfire effect was first studied by Lord, Ross, and Lepper (1979), who showed that participants became more entrenched in their beliefs after being exposed to persuasive arguments that countered their positions. This effect highlights the difficulty of changing deeply held beliefs and suggests that individuals often seek out information that aligns with their preconceptions, leading to polarization and entrenchment in various social and political domains.

Reproducibility: The backfire effect has been repeatedly demonstrated in experimental settings and across different topics. Lord et al. (1979) pioneering study established the backfire effect in the context of social issues and moral judgments. Later studies by Nyhan and Reifler (2010) and Lewandowsky et al. (2012) replicated and extended these findings, confirming that the effect is prevalent across political, health, and other domains. Despite some recent debate over the strength and magnitude of the backfire effect, its general tendency to reinforce existing beliefs in response to contradicting information has been well documented. The backfire effect is particularly pronounced when the information is perceived as threatening to one’s identity or worldview. Research by Lewandowsky et al.

(2017) found that correcting misinformation about climate change often backfires because people perceive the corrections as a challenge to their worldview, rather than an opportunity to change their minds.

Trivia Example: A notable example of the backfire effect is found in the political domain. When people who hold strong political beliefs are presented with data that contradict their views, such as misinformation about climate change, they often become even more convinced of their original stance. A study by Nyhan and Reifler (2010) demonstrated that correcting misperceptions about political facts, like the Obama birth certificate controversy, actually strengthened individuals’ false beliefs rather than changing them, illustrating the power of the backfire effect in reinforcing misinformation.

Selected References

Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest, 13(3), 106–131.

Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37(11), 2098– 2109.

Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017). Beyond Misinformation: Understanding and Coping with the “Post-Truth” Era. Journal of Applied Research in Memory and Cognition, 6(4), 353-369.

Nyhan, B., & Reifler, J. (2010). When corrections fail: The persistence of political misperceptions. Political Behavior, 32(2), 303–330.

Swire-Thompson, B., DeGutis, J., & Lazer, D. (2020). Searching for the backfire effect: Measurement and design considerations. Journal of Applied Research in Memory and Cognition, 9(3), 286–299.

Business Example: The backfire effect can influence consumer behavior and brand loyalty. For example, if a company’s customers are confronted with a negative review or scandal involving the brand, rather than reconsidering their loyalty, they may double down on their support. This effect is often seen with “brand tribes,” where consumers who identify strongly with a brand resist any contradictory information. Research found that individuals who had positive attitudes toward a 241

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BELIEF BIAS The tendency to judge the strength of arguments based on the plausibility of their conclusion rather than how strongly they support that conclusion. were lucky to find a bench right by the fountain. The bright sun lit up the park, making the water jets sparkle brilliantly.

"I love Saturdays," Rooney said as he sat down.

"You can be lazy, sleep in, and just give your brain a rest."

"What do you mean, 'rest'? Just because you're not solving equations non-stop doesn't mean your brain isn't working," Ellie countered.

"For your information, people only use 10 percent of their brains," Rooney said, showing off his knowledge.

"That's nonsense and a myth," Ellie retorted. "It's been proven that people can and do use their entire brains."

"That doesn't sound very convincing. Sometimes I think about nothing at all – which proves that in such moments I'm not using my brain, or only partially using it."

"That proves nothing!" Ellie was confident in her argument. "I'm telling you, it's all a myth.

Many people believe it and look for silly evidence. The brain makes up 3% of the body's weight but uses 20% of its energy.

But that doesn't mean if you're not proving a theorem with one hand and drawing with the other, your brain isn't working."

"Okay, okay, I give up! Just drink your lemonade," Rooney said, and thought to himself that perhaps his brain did a lot more work than he had previously believed.

"Finally, the weekend! Time to relax from all the studying," Rooney, who loved weekends and often planned what he would do on Saturday and Sunday, said. This Saturday was no different, and he met Ellie at a café.

"I don't want to sit here. Let's go outside and sit by the fountain in the square," said Ellie, also in great spirits, eager to enjoy the beautiful summer day.

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that has historically been successful with a particular product line may ignore evidence that market conditions have changed, continuing to invest in that product despite declining sales.

Similarly, investors may continue to support a company with a long history of high returns, disregarding new information about potential risks or shifts in market trends. Research by Kunda (1990) and Stanovich (2009) suggests that such biases lead to suboptimal decision-making in various business contexts, including corporate strategy and investment choices. The tendency to stick with familiar beliefs and past successes can inhibit innovation and responsiveness to market changes.

About: Belief bias is a cognitive bias where an individual’s preexisting beliefs and knowledge influence their ability to evaluate logical arguments. Specifically, people tend to accept conclusions that align with their beliefs, even if the arguments leading to those conclusions are logically invalid. Conversely, they may reject conclusions that contradict their beliefs, regardless of the strength or validity of the argument. This bias can lead to faulty reasoning and decision-making, particularly in complex or emotionally charged situations. First identified

by Evans (1989), belief bias has been widely studied in the context of reasoning, decisionmaking, and education. It plays a significant role in areas such as political judgments, scientific reasoning, and even consumer behavior, where individuals may dismiss evidence that challenges their preconceptions and instead seek out information that confirms what they already believe.

Reproducibility: The effect has been extensively replicated across a wide range of experimental settings. Evans (1989) demonstrated that people are more likely to accept conclusions that fit their existing beliefs even when the premises are logically flawed. Subsequent studies, such as those by Kunda (1990) and Stanovich (2009), confirmed the robustness of belief bias in reasoning tasks, highlighting its persistence across domains, including moral reasoning, political ideology, and consumer behavior. More recent research by Ball and Thompson (2018) further validated the effect, showing that belief bias is especially pronounced when people are presented with emotionally charged or personally relevant topics.

Trivia Example: One example of belief bias can be found in the interpretation of news articles or scientific research. For instance, a person who strongly believes in climate change may more readily accept data supporting the existence of climate change while dismissing studies that contradict it, even if the conflicting studies are scientifically rigorous. Similarly, individuals may be more likely to believe sensationalist headlines that align with their beliefs, even if the underlying content is weak or misleading. Research by Kunda (1990) demonstrated that people are more likely to accept logically valid arguments that align with their preexisting attitudes, while they scrutinize and reject arguments that challenge them.

Selected References

Ball, L. J., & Thompson, V. A. (2018). Belief bias and reasoning. In L. J. Ball & V. A. Thompson (Eds.), The Routledge international handbook of thinking and reasoning (pp. 16–36).

Routledge/Taylor & Francis Group.

Evans, J. S. B. T. (1989). Bias in human reasoning: Causes and consequences. Lawrence Erlbaum Associates.

Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480–498.

Stanovich, K. E. (2009). What intelligence tests miss: The psychology of rational thought. Yale University Press.

Tversky, A., & Kahneman, D. (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press.

Business Example: The belief bias can influence decision-making and risk assessment. For example, a company

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CONFIRMATION BIAS The tendency to search for, interpret, focus on and remember information in a way that confirms one's preconceptions.

"Hey, Ellie – great to bump into you. We've got a sports ball at the tennis club. Want to come with me?" Rooney asked.

"How do I fit into your tennis scene? I'm not a member of the club, I'm not even remotely involved," Ellie replied, surprised. "You should ask Yanzhen. You like her, right?

Plus, she's a club member."

"Who said I like her?" Rooney blushed. "Besides, I've already sent her two messages and she hasn't replied. She doesn't want to go with me."

"Why do you think she doesn't like you? First off, not replying to messages doesn't mean anything. And secondly, be persistent!"

"If she wanted to go with me, she would have responded."

Rooney was pondering this when suddenly his phone rang.

"Yes," he said, answering the call. "Yes, it's me.

Who's this? Hi, Yanzhen.

Yeah, sure. I'll pick you up."

After hanging up, Rooney shouted with joy, nearly knocking Ellie off her feet, "Yes! Yes! Yes! Can you believe it? That was Yanzhen!

She's going to the ball with me! I can’t believe it!"

"See," Ellie said with a smile, "what did I tell you?"

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supports their current approach. A notable example is Kodak’s reluctance to fully embrace digital photography, despite the technology’s growing potential. Research by Russo and Schoemaker (2002) showed that businesses tend to favor information that validates their existing strategies, leading to missed opportunities and slow adaptation to market changes. This bias can also affect hiring practices, where managers may favor candidates who reflect their own values or preferences, rather than considering a broader pool of talent.

About: Confirmation bias refers to the tendency to search for, interpret, favor, and recall information in a way that confirms one’s preexisting beliefs or hypotheses, while giving disproportionately less consideration to alternative possibilities. First described by Wason (1960), confirmation bias has been recognized as a central feature of human reasoning, affecting everything from personal relationships to political decision-making.

People with strong beliefs may selectively gather evidence that supports their views, and even interpret ambiguous information in a manner that reinforces their existing opinions. This bias is not only prevalent in everyday reasoning but also contributes to the entrenchment of misinformation and the polarization of social and political debates. It plays a significant role in fields such as medicine, law, and business, where decision-making often relies on the interpretation of complex and sometimes contradictory information.

Reproducibility: The confirmation bias has been widely documented and replicated across various contexts. Wason’s (1960) initial study showed that individuals tend to look for evidence that supports their hypotheses, even when doing so leads to errors in reasoning. Subsequent studies, such as those by Nickerson (1998), have further confirmed the robustness of this bias in decisionmaking, judgment, and social interactions. More recent research by Lord, Ross, and Lepper (1979) demonstrated how confirmation bias can influence individuals’ attitudes toward controversial topics, such as capital punishment, by reinforcing existing beliefs. Studies in business and management, like those by Russo and Schoemaker (2002), have also confirmed that confirmation bias can lead to suboptimal strategic decisions in organizations. These findings highlight the ubiquity and replicability of confirmation bias across different domains and its profound impact on human reasoning.

Trivia Example: An example of confirmation bias can be seen in the realm of sports fandom. Fans of a particular sports team are likely to highlight the team’s victories and dismiss any defeats, attributing them to unfair refereeing or bad luck rather than considering the performance of the opposing team. Similarly, if a fan’s team is performing poorly, they may focus on a few good plays or minor achievements to confirm their belief that the team is still competitive. Research by Plous (1993) demonstrated that people tend to pay more attention to and remember information that supports their favorable views, while ignoring or discounting information that contradicts those views.

Selected References

Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37(11), 2098– 2109.

Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.

Plous, S. (1993). The psychology of judgment and decision making. McGraw-Hill.

Russo, J. E., & Schoemaker, P. J. H. (2002). Winning decisions: Getting it right the first time. Doubleday.

Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual task. Quarterly Journal of Experimental Psychology, 12(3), 129–140.

Business Example: The confirmation bias can hinder innovation and strategic decision-making. For instance, companies that have had previous success with a particular business model may ignore emerging market trends or fail to adapt to technological disruptions, instead focusing on data that 245

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CONTINUED INFLUENCE EFFECT The persistence of a disproven belief that continues to influence reasoning and beliefs even after being corrected.

"Hi, Ellie," Ellie recognized Rooney's voice on the phone. "Sorry, but I can’t come over tomorrow. I have to look after my brother."

"Why?" "Some kids at his day care got rubella, so we decided to keep him home." "Rubella? But there's a vaccine for that."

"There is, but many parents believe that the MMR vaccine, for measles, mumps, and rubella, causes autism."

"But hasn’t it been proven that it doesn’t?"

"It has been, but many parents still believe in that myth. Anyway, why don’t you come over to my place instead?"

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product recall, the misinformation surrounding the event can persist in consumers’ minds, even after the company addresses the issue. Research

by Swire et al. (2017) demonstrates that consumers continue to believe false claims or rumors about products or companies even after corrective advertising or official statements. This bias can undermine corporate reputation, delay recovery from scandals, and hinder customer loyalty. Companies may invest significant resources into corrective measures, but these efforts can have limited effectiveness due to the continued influence of prior misinformation.

About: The continued influence effect refers to the tendency for misinformation to persist in people’s beliefs and influence their decisions, even after the information has been corrected.

This bias occurs when people continue to rely on and use incorrect or outdated information, even when they are explicitly told it was false or misleading. The effect is particularly prevalent in situations involving rumors, fake news, or unverified information, and it poses a significant challenge for both personal decision-making and public discourse. Research by Lewandowsky et al.

(2017) shows that once misinformation is introduced, it can be difficult to fully correct, as the original, erroneous beliefs continue to shape perceptions. This bias has important implications for fields such as health communication, political opinion formation, and legal decision-making, where the impact of misinformation can be long-lasting and detrimental.

Reproducibility: The has been consistently replicated in various contexts. Lewandowsky et al. (2017) showed that misinformation persists even after individuals are explicitly warned or corrected, confirming the difficulty of eradicating false beliefs. Additional studies by Ecker et al. (2010) and Swire et al. (2017) have replicated these findings, showing that people often retain the original, erroneous information and continue to use it in decisionmaking, even after being presented with corrected facts. Research also indicates that the effect can be stronger when the misinformation aligns with personal beliefs or preexisting knowledge. Despite variations in the magnitude of the effect, the phenomenon remains highly replicable across various settings (e.g., van der Linden, 2015), from political opinions to consumer behavior.

Trivia Example: An example of the continued influence effect occurs in the context of public health misinformation. For instance, the belief that vaccines cause autism persists among certain segments of the population, despite widespread scientific evidence to the contrary. Studies by Ecker et al. (2010) and others have demonstrated that even when people are exposed to corrective information, they continue to hold the original, inaccurate belief. The misinformation regarding vaccines, first popularized by Andrew Wakefield’s fraudulent study in 1998, continues to influence public opinion and decision-making, even though the study has been discredited and retracted. This example highlights how the continued influence effect can perpetuate harmful beliefs, even in the face of clear refutation.

Selected References

Ecker, U. K. H., Lewandowsky, S., & Cook, J. (2010). Correcting misperceptions of climate change: Using cognitive science to improve the effectiveness of communications.

Psychological Science in the Public Interest, 11(3), 1-23.

Lewandowsky, S., Ecker, U. K. H., & Cook, J. (2017).

Beyond misinformation: Understanding and coping with the “post-truth” era. Journal of Applied Research in Memory and Cognition, 6(4), 353–369.

Swire, B., Ecker, U. K. H., & Lewandowsky, S. (2017). The role of familiarity in correcting inaccurate information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(12), 1948–1961. van der Linden, S. (2015). The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model. Journal of Environmental Psychology, 41, 112–124.

Business Example: The continued influence effect can shape consumer behavior and brand perceptions. For example, if a company experiences a negative incident, such as a 247

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CONSERVATISM (BELIEF REVISION) The tendency to insufficiently revise one's belief when presented with new evidence.

"Hi, Ellie, great you could make it," Rooney said as he opened the door. "It's my little brother Oliver's birthday. Can you help me out?"

"Of course, I can help."

"See those two bags of balloons and the helium tank? Could you inflate the balloons?

Meanwhile, I'll head to the store." "No problem."

"Oh, I forgot to mention," Rooney paused at the door, "each bag has 50 balloons, but one has been lying around for a while. We bought it before we moved here. So, there might be a lot of defective balloons in it. I just don't know which bag is the old one and which is new."

When Rooney returned from the store, Ellie showed him her work.

"Look, out of 12 balloons, 8 were defective, so I could only inflate 4." "Then that must be the old bag. Try the other one – it should have new balloons."

"Are you sure? Maybe it's just a bad batch on top?"

"I'm certain. 8 out of 12 being defective means you definitely have the wrong bag. We should throw it out."

"Should we really discard it? What if it's not the case?" "Trust me, it is – just toss it, no doubt about it."

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emphasizes how companies often fail to adapt to new business models because they remain too committed to their traditional ways of thinking, leading to missed opportunities and eventual decline. Conservatism bias can also impact strategic decision-making, where leaders may ignore or downplay external threats due to a preference for familiar strategies.

Reproducibility: The conservatism bias has been widely replicated across various domains. Edwards (1968) first identified the bias in decision-making experiments, where individuals failed to adjust their beliefs when presented with new evidence.

Subsequent studies have confirmed the robustness of the effect. For example, Gilovich et al. (2002) found that people tend to be conservative in updating their beliefs about the probability of uncertain events, even when provided with strong, conflicting evidence. More recent research by Buehler et al. (1994) and Johnson and Russo (1984) demonstrated that conservatism bias is particularly prominent when individuals are under cognitive load or emotionally invested in their prior beliefs.

Despite minor variations in specific contexts, the overall tendency to underweight new information in favor of prior beliefs remains a widely replicable phenomenon.

Selected References

About: Conservatism bias refers to the tendency to favor prior beliefs or information over new evidence when forming judgments or making decisions.

Individuals with this bias underweight new information, giving disproportionate importance to their existing views or prior knowledge. In decision-making contexts, this can lead to slow adjustment to new realities, as individuals are reluctant to revise their beliefs, even in the face of compelling new evidence. Conservatism bias is closely related to the concept of belief perseverance, where individuals cling to their original beliefs despite contradictory evidence.

First identified by Edwards (1968), this bias has profound implications across various domains, from personal decisions to professional settings, including finance, politics, and health.

Understanding conservatism bias is important for improving decision-making processes, as it helps explain why people tend to resist change and hold onto outdated beliefs or strategies.

Trivia Example: Investors may hold onto underperforming stocks because they have previously been successful, disregarding new data suggesting the company’s future performance may be poor. Research by Barberis et al. (1998) highlights how investors often underreact to new information, continuing to base decisions on outdated beliefs about stock values. This effect can result in losses, as investors fail to adjust their portfolios based on the latest market data, instead relying on prior expectations about a company’s performance.

Barberis, N., Shleifer, A., & Vishny, R. W. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343.

Buehler, R., Griffin, D., & Ross, M. (1994). Exploring the “planning fallacy”: Why people underestimate their task completion times. Journal of Personality and Social Psychology, 67(3), 366–381.

Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard Business School Press.

Edwards, W. (1968). Conservatism in human information processing. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 359–369). Cambridge University Press.

Gilovich, T., Griffin, D., & Kahneman, D. (2002). Heuristics and biases: The psychology of intuitive judgment. Cambridge University Press.

Johnson, E. J., & Russo, J. E. (1984). Product familiarity and learning new information. Journal of Consumer Research, 11(1), 542–550.

Business Example: The conservatism bias can prevent companies from adapting to changing market conditions or emerging technologies. For example, companies that were once leaders in traditional media, like Blockbuster, resisted adopting digital streaming technologies, instead sticking to their established business model. This resistance to change was driven by the company’s prior success with physical rentals and a reluctance to embrace new, disruptive technologies. Research

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EXPERIMENTER’S OR EXPECTATION BIAS A bias caused by the experimenter whose expectations about the outcome of the experiment can be subtly communicated to the participants in the experiment.

"See," Ellie said, pointing to the orchids, "I told you flowers from an online store are always worse than from the shop on our street.

Look, these orchids are barely alive – they're from the internet, but these ones are thriving."

"Listen," Rooney observed the flowers carefully, "I know you prefer going to the store and picking flowers yourself instead of ordering online, but that doesn’t mean the internet ones are inferior."

"Why not?"

"Because they're growing under different conditions."

"What do you mean? The conditions seem the same to me. They get the same light and I water them equally."

"But look: the orchids from the regular store are in special orchid soil, while the ones from the internet aren’t. I think these internet orchids deserve a chance."

"I hadn't thought of that. Alright, I'll repot them in special soil today."

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unknowingly influence survey respondents to view the product more favorably, either through the way questions are framed or through body language cues. Studies found that managers may unintentionally lead focus groups in a way that aligns with their expectations of the product, potentially skewing market research results.

This bias can result in poor decision-making based on inaccurate data and lead to the development or promotion of suboptimal products (e.g., Babad, 2009).

About: Experimenter’s bias, also known as expectation bias, refers to the unintentional influence that an experimenter’s expectations or beliefs can have on the outcome of an experiment. This bias occurs when researchers’ preconceptions affect how they collect, interpret, or present data, potentially leading to skewed or biased results.

For example, experimenters may subconsciously interpret ambiguous data in ways that support their hypotheses or may unknowingly cue participants toward certain responses.

Expectation bias can occur at all stages of research, from the design of the study to the analysis of the results. This phenomenon is particularly prevalent in psychological, medical, and social science studies, where subjective interpretation plays a role in data collection.

Research by Rosenthal (1966) on “The Pygmalion Effect” demonstrated how experimenter expectations can influence participant performance, showing that the belief in participants’ potential can lead to improvements in their performance.

Reproducibility: The experimenter bias has been widely studied and replicated across numerous disciplines.

Rosenthal (1966) conducted a classic study demonstrating how experimenters’ expectations influence participants’ behavior in both classroom and laboratory settings. Further research by Dror and Kukucka (2013) and Kassin et al. (2003) has replicated these findings in various contexts, confirming that expectations can influence the data collection process. The phenomenon has been observed across fields as diverse as medical research, where clinicians’ expectations about treatment efficacy affect the assessment of outcomes, and in social science studies, where experimenters’ beliefs can influence the interpretation of responses (e.g., Lawson, 1964). While experimental controls such as double-blind protocols are effective in minimizing expectation bias, it remains a significant challenge in subjective data analysis.

Trivia Example: One example of experimenter’s bias occurred in psychology experiments with animals, such as those conducted by Clever Hans in the early 20th century. Hans, a horse, appeared to be able to perform complex arithmetic, but in reality, the horse was responding to subtle cues from its trainer, who unknowingly provided these cues based on his expectations of the horse’s behavior.

This bias was later identified as the experimenter’s influence on the horse’s actions, demonstrating how the expectations of the experimenter can shape the results in unintentional ways. This example illustrates the importance of controlling for experimenter bias in scientific research to ensure reliable results.

Selected References

Babad, E. (2009). A generalized expectancy effect in experimental research in the social sciences. In D. M. McInerney, G. A. D. Liem, & A. D. Liem (Eds.), Research on sociocultural influences on motivation and learning (Vol. 9, pp. 225– 247). Springer.

Lawson, R. (1964). A longitudinal study of the effects of experimenter bias on the operant learning of laboratory rats. Journal of Psychiatric Research, 2(2), 61–72.

Kassin, S. M., Appleby, S. C., & Perkins, D. (2003). The influence of bias on police officers’ judgments in interrogations. Law and Human Behavior, 27(2), 141-159.

Dror, I. E., & Kukucka, J. (2013). The forensic confirmation bias: Problems, perspectives, and proposed solutions. Journal of Applied Research in Memory and Cognition, 2(1), 42–52.

Rosenthal, R. (1966). Experimenter effects in behavioral research.

New York: Appleton-Century-Crofts.

Business Example: The experimenter bias can occur during consumer product testing or market research surveys. For instance, if a product development team strongly believes in the superior quality of a product, they may 251

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END-OF-HISTORY ILLUSION Individuals believe that they have experienced significant personal growth and changes up to the present moment, but will not substantially grow or mature in the future. up for me?"

He smiled, "Both, watching a movie and decided to wait for you. You're back late, or rather, early," he said, glancing at the clock. "How was the party? Was it good?"

"Well, not really special," Ellie mumbled, feeling oddly upset.

"What happened? Did that boy you like not show up? What's his name… Jake?"

Ellie grew more upset, "No, he was there."

"But…" "But he spent the whole evening dancing with Tessa. Thankfully, Rooney was there. At least I had someone to talk to."

"Don't worry so much, you'll see, everything will turn out fine."

Ellie sat down next to her dad on the couch and suddenly blurted out, "As if I'll ever like someone else again! Never in my life! I won't let this happen to me again!"

"Come on," he laughed, "I remember when I was about 30, I fell madly in love with a girl who didn't even notice me. I thought I'd never feel affection for anyone else! But as you can see, I eventually met your mum and fell in love... You're still young!"

"You think?"

"Sure! I've got an idea: how about we go to the kitchen for some cocoa? I brought back some amazing cocoa from my business trip. You’ll love it!"

"Sounds great, Dad!"

Ellie returned home late. Quietly entering, she carefully took off her sneakers and tiptoed to her room. Suddenly, she noticed a sliver of light coming from the living room.

Peeking in, she saw her dad, still awake: "Hi, Dad. Are you watching a movie or waiting 252

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many consumers in their twenties may purchase a smartphone or gadget that they believe will suit their needs for the foreseeable future, only to find that their needs or preferences have shifted as they grow older. Research by Van Boven and Gilovich (2003) showed that people often underestimate how much their preferences will evolve over time, which can affect their satisfaction with long- term purchases. This bias can also impact marketing strategies, where companies might fail to adapt to shifting consumer values or preferences, relying too heavily on assumptions about stability.

About: The end-of-history illusion refers to the cognitive bias where people believe that their preferences, values, and identity have reached a stable point and will not change in the future, even though they have likely evolved significantly in the past.

This bias causes individuals to overestimate the degree of permanence in their current state and underestimate future changes. The phenomenon was first identified by Quoidbach et al. (2013), who demonstrated that people tend to perceive their current selves as the final version of who they are, forgetting the dynamic nature of personal growth and adaptation. The end-ofhistory illusion has implications for personal decision-making, as it influences how individuals make predictions about their future preferences, from their taste in music and fashion to their career goals and life aspirations.

Reproducibility: The end-of-history illusion has been replicated across several studies, confirming its robustness and applicability in various contexts. Quoidbach et al. (2013) demonstrated this bias in a series of studies where participants predicted their preferences and identities for future years, only to be shown that their actual preferences had changed significantly. Further research by van Boven and Gilovich (2003) demonstrated that people are not only overconfident about their future preferences but also about their future happiness, suggesting that individuals consistently underestimate the potential for growth and change. This effect has been observed in both personal and professional settings, including consumer product choices (as discussed above) and in how people evaluate their career and life trajectories. Despite minor variations in individual contexts, the end-ofhistory illusion remains a well-replicated phenomenon that shapes both personal and business decision-making.

Trivia Example: The end-of-history illusion can be seen in the way people evaluate their future tastes. In a 2013 study, Quoidbach et al. found that individuals who were asked to predict their preferences in five or ten years from the present tended to make predictions that overestimated the stability of their current tastes. For example, a young adult might believe they will always enjoy the same music genre they prefer at the time, despite the fact that their tastes have likely changed in the past. This bias highlights how people are often blind to their own evolving preferences and are overly confident in the constancy of their present selves.

Business Example: The end-of-history illusion can influence consumer behavior and purchasing decisions.

For instance, companies might assume that customers’ preferences for a particular product or service will remain unchanged, leading to stagnant innovation and missed opportunities.

The technology industry offers a clear example:

Selected References

Quoidbach, J., Gilbert, D. T., & Wilson, T. D. (2013). The end of history illusion. Science, 339(6115), 96–98.

Van Boven, L., & Gilovich, T. (2003). To do or to have? That is the question. Journal of Personality and Social Psychology, 85(6), 1193–1202.

Wilson, T. D., & Gilbert, D. T. (2005). Affective forecasting.

Advances in Experimental Social Psychology, 37, 345–411.

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EXAGGERATED EXPECTATION Overestimating the likelihood that expected developments will occur.

“Hey," Rooney entered the living room on a beautiful Saturday. Ellie was nervously flipping through music sheets at the piano.

"What's wrong? Why are you so anxious?"

"It's terrible," Ellie gestured frustratedly, sending a flurry of music sheets flying to the floor around the piano. "I haven't played in ages, can't remember a single piece, and now Dad wants me to play at a charity event. I just know I'm going to embarrass myself."

"Why do you think that?"

"Can't you see? Nothing's coming to me, I can’t remember anything... It's all going to end badly."

"Let's do this: I'll help you pick up the sheets, and we can look through them together. We’ll find something."

"And you're going to play for me, too? I told you, I can't remember a single note."

"First, you can play beautifully on your own.

Second, you don’t have to know every note by heart. You can play from the sheets."

"It doesn’t matter, with or without the sheets – I’m going to make a fool of myself. You'll see! The concert is already tomorrow!"

"Just calm down now, and I'll help you prepare," Rooney said soothingly.

"Everything will be fine."

On Sunday evening, Ellie called Rooney. "So, how did it go?" he asked. ”Great! I didn’t make a single mistake and even played 2 of the 5 pieces by heart. Can you believe it?"

"See, and you were saying, ‘I’ll embarrass myself…’"

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promote it with grand claims of groundbreaking features and capabilities. Consumers, in turn, develop exaggerated expectations about the device’s performance. Once the product is released, the actual experience might not live up to the highly anticipated claims, leading to disappointment and dissatisfaction. A study by Kahn and Szymanski (2002) revealed that companies that overpromise during product launches often see higher early sales but face greater consumer backlash when the product does not meet inflated expectations. This bias can harm customer loyalty and brand reputation, especially in a market where word-of-mouth and reviews play a significant role in purchasing decisions.

About: Exaggerated expectation bias occurs when individuals overestimate the likelihood or magnitude of an outcome, based on unrealistic expectations. This bias is driven by a combination of optimism and selective attention to positive information, often leading to disappointment when outcomes fall short of expectations. It can manifest in various contexts, including product development, investment decisions, and personal goals. For instance, people might overestimate the success of a new product launch, assuming it will outperform all competitors, without adequately accounting for market conditions or consumer behavior. The effect has significant implications for decisionmaking, as it distorts how individuals or organizations plan and prepare for future events.

Over time, exaggerated expectations can contribute to stress, frustration, and poor outcomes, especially when individuals are unable to meet their inflated expectations.

Reproducibility: The exaggerated expectation bias has been extensively replicated across a variety of settings, from consumer behavior to investment and political decision-making. Mellers et al.

(1997) demonstrated the bias in a series of experiments where participants overestimated the outcomes of uncertain events. Further studies, such as those by Kahneman and Tversky (1979) on prospect theory, have shown that individuals tend to overestimate the likelihood of positive outcomes and underestimate potential risks. More recent work by Loewenstein et al.

(2001) explored how individuals’ expectations can become inflated through selective exposure to optimistic information, particularly in financial and consumer contexts. The consistency of the bias across domains such as business, entertainment, and investing further affirms its replicability and pervasive influence on decision-making.

Trivia Example: An example of exaggerated expectation bias is seen in the entertainment industry, particularly with movie releases. In 2018, the film Solo: A Star Wars Story was expected to be a major box-office success due to its connection to the popular Star Wars franchise. However, despite the hype, the movie grossed significantly less than expected, leading to a publicized disappointment among producers and fans alike. Research by Mellers et al. (1999) showed that when individuals form highly optimistic expectations based on prior experiences or external cues, they are often shocked by the reality of outcomes, contributing to the exaggerated expectation bias. This is especially prominent in industries where marketing and media hype can create inflated expectations.

Selected References

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Kahn, B. E., & Szymanski, D. M. (2002). The effects of inflated expectations on consumer satisfaction. Journal of Marketing Research, 39(2), 261–271.

Loewenstein, G., Weber, R. A., Hsee, C. K., & Welch, E. (2001). Risk as feelings. Psychological Bulletin, 127(2), 267–286.

Mellers, B. A., Schwartz, A., Ho, K., & Ritov, I. (1997). Decision affect theory: Emotional reactions to the outcomes of risky options. Psychological Science, 8(6), 423–429.

Business Example: The exaggerated expectation bias is often seen in the tech industry, particularly with the launch of new gadgets or software. For instance, when a new smartphone is announced, companies often 255

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FORER EFFECT OR BARNUM EFFECT The tendency to give high accuracy ratings to descriptions of their personality that supposedly are tailored specifically for them but are, in fact, vague and general enough to apply to a wide range of people.

"Can I take a look at the magazine?" asked Ellie.

"Sure, go ahead. Mom loves reading it," Rooney replied without looking up.

"Let's see, what does the horoscope say?"

"Please don’t tell me you believe in horoscopes."

Rooney stopped making coffee and looked at Ellie.

"It's not that I believe in them, but often they're spot on about me."

"But that’s the trick – they write vague statements like 'Aries, beware of big expenses.' And that's relevant for many people... In the sense that everyone should spend wisely. It's a psychological tactic: you think it applies personally to you, but in reality, it's general enough to apply to everyone on the planet."

"Maybe so, but I still like to read it. It’s fun," Ellie replied, flipping through the magazine's pages.

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While these tests provide generalized descriptions, many employees may interpret them as highly accurate, leading to misplaced confidence in their self-awareness or the compatibility of their team. Research by McCrae and Costa (1989) has shown that people tend to accept personality assessments more favorably when they are presented as personalized, even if the content is general and lacks empirical validity. This can lead to organizations making decisions based on these assessments, despite their limited predictive power regarding actual job performance.

About: The Forer effect, also known as the Barnum effect, describes the tendency for people to perceive vague, general statements as highly accurate when applied to themselves—even though these statements could apply to many others. Named after psychologist Bertram Forer, the term originates from a 1948 study in which students received identical personality analyses but rated them as uniquely accurate. This bias reflects how individuals interpret ambiguous feedback in ways that affirm their self-image. It is frequently exploited in pseudoscientific fields like astrology, fortune-telling, and some personality tests. The alternate name, “Barnum effect,” references P.T. Barnum, the 19th-century showman known for using broad, universally appealing statements in his acts. Psychologist Paul Meehl coined the term in 1956, drawing parallels between Barnum’s methods and the tendency to accept flattering but vague descriptions as personally meaningful. The effect illustrates how easily people can be misled by the illusion of uniqueness when presented with statements designed to feel specific but apply broadly (e.g, Snyder et al., 1977).

Reproducibility: Forer’s original experiment (1949) demonstrated that participants were prone to giving high accuracy ratings to personality descriptions that were, in fact, vague and generalized. Subsequent studies have replicated these findings across various contexts, from astrology readings (Furnham and Schofield, 1987) to evaluations of personality tests. In a more recent meta-analysis, Jones and Harris (2016) found that people continue to show susceptibility to the Forer effect when provided with personal assessments, even in more controlled environments like organizational settings. Despite some variations based on individual differences or the context of the feedback, the phenomenon is highly replicable across studies.

Trivia Example: People who read horoscopes frequently feel that the predictions apply specifically to their lives, despite the fact that the same predictions are written for a wide audience. For instance, a horoscope might say, “You will experience both challenges and rewards in the near future,” a statement so vague and general that it could apply to anyone, yet many individuals will feel that it is personally tailored to their current situation. Studies such as those by Furnham and Schofield (1987) demonstrate that individuals tend to attribute personal relevance to such broad statements, reinforcing the Forer effect in everyday life.

Selected References

Forer, B. R. (1949). The fallacy of personal validation: A classroom demonstration of gullibility. Journal of Abnormal and Social Psychology, 44(1), 118–123.

Furnham, A., & Schofield, S. (1987). Accepting personality test feedback: A review of the Barnum effect. Current Psychological Research & Reviews, 6(2), 162–178.

Jones, L. L., & Harris, L. T. (2016). Personality assessments and susceptibility to the Forer effect: A meta-analysis.

Personality and Social Psychology Bulletin, 42(10), 1412– 1424.

McCrae, R. R., & Costa, P. T. (1989). Reinterpreting the MyersBriggs Type Indicator from the perspective of the FiveFactor Model of Personality. Journal of Personality, 57(1), 17-40.

Snyder, C. R., Shenkel, R. J., & Lowery, C. R. (1977). Acceptance of personality interpretations: the" Barnum Effect" and beyond. Journal of consulting and clinical psychology, 45(1), 104.

Business Example: Companies often use broad personality assessments, such as the Myers-Briggs Type Indicator (MBTI) or other popular frameworks, to gauge candidates’ suitability for a position.

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FORM FUNCTION ATTRIBUTION BIAS The tendency to view form and function as a single construct while ignoring the possibility that a form can serve multiple functions.

"How was the exhibition yesterday?" Ellie asked.

"It was really interesting. Many people liked the robots from our club, but there were some odd things too." "Oh? Like what?"

"Remember our 'Deceptive Robot'? Turns out, many people got genuinely upset when they found out the robot “lied” to them.

One person even yelled at it. We tried explaining that it was an experiment where we 'teach' the robot to deceive, but it didn’t help. Luckily, this incident happened in the early hours of the exhibition, so we just removed that robot from our display and replaced it with another one. Still, the fact remains. After the exhibition, I learned that, according to studies, people don't react much to lies from other humans, but they react strongly to lies from robots. Overall, though, everything went well."

"That's great. Sorry I couldn’t make it yesterday.

I had a lot of work."

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these visual features with better performance.

For example, when car manufacturers design vehicles with sleek, futuristic exteriors, they often expect customers to perceive these cars as more advanced in terms of safety, performance, or technology, even if the underlying features do not support these assumptions. Research by Chitturi et al. (2007) showed that customers tend to associate aesthetically pleasing product designs with higher perceived functionality and value, which can lead businesses to prioritize form over function in their design processes. This bias can also influence consumer satisfaction, as expectations based on appearance may not align with the actual product experience, leading to disappointment when the product underperforms.

About: The form-function attribution bias refers to the cognitive tendency to attribute the function or purpose of an object or system based on its form or appearance. People often assume that the way something looks directly correlates with what it is supposed to do. This bias arises from an intuitive desire to quickly categorize and understand the world based on superficial cues.

For example, in the realm of design, people might assume that a sleek, high-tech-looking device is more efficient or advanced than one with a more utilitarian appearance, even if the latter performs better. This bias can lead to misjudgments in evaluating products, services, or even social roles, as individuals may focus on appearance rather than deeper functional qualities. The form-function attribution bias is prevalent in many areas, such as marketing, product design, and interpersonal interactions, influencing how people perceive effectiveness or capability based on visual features rather than underlying performance.

Reproducibility: Many studies replicated the bias in consumer product evaluations, demonstrating that people tend to favor products with visually appealing designs, assuming better functionality without evaluating the technical aspects (e.g., Jussim and Honeycutt, 2024). Research by Chitturi et al.

(2007) further confirmed the bias in the automotive and technology industries, showing that consumers’ perception of product quality is often driven by visual attributes. More recent studies, such as those by Raghunathan et al.

(2006), have explored how this bias influences consumer preferences in other industries, such as fashion and food products. The effect remains stable across different product categories and cultural contexts, suggesting that it is a pervasive cognitive bias that plays a crucial role in consumer decision-making.

Trivia Example: An example of form-function attribution bias can be found in the consumer electronics industry, particularly in the marketing of smartphones and gadgets. For example, sleek, minimalistic designs often influence consumers to perceive a product as more advanced or functional, even when the product’s technical specifications might not be superior. In one study by Kim and Jang (2013), consumers were more likely to rate a product with a modern, stylish appearance as higher in quality and performance, even if the actual specifications were identical to a less stylish competitor. This bias leads consumers to base their purchasing decisions on form over function, often valuing aesthetics over practicality.

Selected References

Chitturi, R., Raghunathan, R., & Mahajan, V. (2007). Form versus function: How the intensities of specific emotions evoked in functional versus hedonic trade-offs mediate product preferences. Journal of Marketing Research, 44(4), 702– 714 Jussim, L., & Honeycutt, N. (2024). Bias in Psychology: A Critical, Historical and Empirical Review. Swiss Psychology Open, 4(1), Article 5.

Raghunathan, R., Naylor, R. W., & Hoyer, W. D. (2006). The importance of a general affective tone in understanding the effects of product displays on consumers’ intentions.

Journal of Marketing Research, 43(4), 463–472.

Business Example: The form-function attribution bias can significantly impact product design and marketing strategies. Companies often focus on creating products that look attractive and modern, assuming that consumers will equate 259

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HINDSIGHT BIAS The inclination to see events that have already occurred as being more predictable than they were before they took place. eat the nuts. I’ll pick them out of the chocolate."

"Fine, but only a little bit, and only if the nuts are removed beforehand. And don't eat too much! I need to go feed my brother dinner."

Rooney hung up the phone.

The next day, Rooney stopped by Ellie's house to head to training. He rang the doorbell.

"Who is it?" a familiar voice asked from behind the door.

"What do you mean 'who'? It's me," Rooney said, "aren't you getting ready for training?"

"I'm not going," the voice behind the door replied.

"Why not? Can you at least open the door?" "No, I won't."

"What happened?"

"I ate too much chocolate yesterday. Now I’ve got a rash all over my face."

"How much chocolate did you eat?"

"A kilogram..." The voice behind the door trembled, as if scared by its own answer.

"A whole kilogram? I knew it. I told you not to eat it! You're allergic to nuts!" "But I picked them all out."

"So what? I told you that wouldn’t help, that the nuts or their traces would still be there! I warned you."

"I think you said something else," the voice from behind the door retorted, offended.

"Not at all," Rooney hissed angrily, "I warned you, but you never listen. Anyway, I'm leaving now. Do you have any medication?"

"Yes!" Ellie's voice responded from behind the door.

"Come over tomorrow," Ellie's cheerful voice came through the phone. "Dad brought back a kilogram of Swiss chocolate with nuts! Can you imagine?" "What chocolate?"

Rooney responded irritably. "First, you shouldn’t be eating sweets; second, you have training tomorrow; and third, what about the nuts? You're allergic to them."

"Oh, come on – let's say Dad brought it for Mum, but a little bit won’t hurt. I’ll burn off the calories at training tomorrow, and I won't 260

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the 2008 financial crisis, many analysts retrospectively claimed that the collapse of certain financial institutions could have been predicted, even though it was impossible to foresee the event with certainty before it happened.

Research by Plous (1993) demonstrated that individuals involved in financial decisions often overestimate their ability to foresee outcomes, which can lead to biased post-event analyses. This bias can also affect corporate strategies, where business leaders may take unwarranted credit for successes or unfairly blame themselves for failures, believing that they should have predicted the outcomes more accurately.

About: Hindsight bias, often referred to as the “knew-itall-along effect,” is the tendency for individuals to believe, after the fact, that an event was predictable, even though there was little or no basis for predicting it. This bias occurs because people perceive events as having been more predictable than they were before they happened, which can distort their recollection of past decisions or judgments. Hindsight bias is commonly observed in fields such as law, finance, and sports, where people tend to believe that outcomes were foreseeable based on the information available at the time, even though they were not. For example, when an unexpected business failure occurs, observers might later argue that the signs of failure were obvious, even though the company’s leaders had made decisions based on incomplete or conflicting information. This bias can affect how people learn from past experiences, as they may falsely believe that they could have predicted the outcome, which may lead to overconfidence in future decision- making.

Reproducibility: Fischhoff (1975) demonstrated this effect by asking participants to predict the outcome of an event and then to evaluate how predictable it was after they knew the outcome. Subsequent studies, such as those by Roese and Vohs (2012), have confirmed that people consistently exhibit hindsight bias in a wide range of contexts, from business decisions to legal judgments. This bias is particularly strong when people are emotionally invested in the outcome, as shown in research by Schkade and Kahneman (1998), who found that hindsight bias is more pronounced in situations involving high-stakes decisions. More recent studies, like those by Tversky and Kahneman (1982), continue to reinforce the robustness of hindsight bias, suggesting that it is a pervasive cognitive bias that distorts how people evaluate past events.

Trivia Example: After a football team wins a championship, fans and analysts often claim that the victory was inevitable, pointing to key plays or strategic moves that led to the win. However, if the same team had lost, those same plays might have been criticized. A study by Fischoff (1975) demonstrated that individuals who knew the outcome of an event were more likely to rate the event as being more predictable than those who did not know the outcome. This effect is evident in many sports events, where the outcome appears clearer once it has occurred, but people often fail to acknowledge how uncertain the prediction was before the event.

Selected References

Fischhoff, B. (1975). Hindsight ≠ foresight: The effect of outcome knowledge on judgment under uncertainty. Journal of Experimental Psychology: Human Perception and Performance, 1(3), 288–299.

Plous, S. (1993). The psychology of judgment and decision making. McGraw-Hill. Roese, N. J., & Vohs, K. D. (2012).

Hindsight bias. Perspectives on Psychological Science, 7(5), 411–426.

Schkade, D. A., & Kahneman, D. (1998). Does living in California make people happy? Psychological Science, 9(5), 399–403.

Tversky, A., & Kahneman, D. (1982). Judgment under uncertainty: Heuristics and biases. Cambridge University Press.

Business Example: After a major market crash or financial crisis, investors, analysts, and corporate leaders often look back and claim that the signs of the crash were clear, even though the circumstances were highly uncertain at the time. For example, during 261

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HOT-HAND FALLACY The belief that a person who has experienced success with a random event has a greater chance of further success in additional attempts. of spending no more than a hundred," she said. The salesman, unfazed, offered a lottery ticket for 5 dollars that could win a discount on any pair of glasses in the store. "What's the maximum discount?" Ellie asked. "75 percent!" the salesman replied with a bright smile. "Anything but this!" Rooney exclaimed. But Ellie, intrigued, bought a ticket and asked Rooney to draw.

"This is a scam! You'll regret it," Rooney warned, but Ellie insisted. Rooney reluctantly reached into the lottery container and pulled out a ticket, handing it to Ellie. She excitedly scratched it off, revealing a 25 percent discount.

"Awesome!" she exclaimed. Another ticket, please!" She looked at Rooney, "Draw again!

You’re lucky today.” "Maybe we should stop?" Rooney suggested skeptically.

"Nonsense! You're drawing winning tickets!"

Ellie encouraged. Rooney drew another ticket. Ellie quickly scratched it off to reveal a 50 percent discount. Elated, she jumped for joy and turned to the salesman, "One more!"

The salesman, eyes wide with astonishment, obliged. A crowd had started to gather around them. "Draw again!" Ellie urged Rooney. Rooney pulled yet another ticket.

Ellie, in one swift motion, scratched it off to find, "Thank you for trying. Better luck next time!"

"I don't get it!" she said, perplexed. "Everything was going so well! Why?" The salesman’s face returned to its default polite indifference as the gathered spectators dispersed. "Ellie," Rooney said, "when will you understand that lotteries are just a trick?

There's no lucky hand. It's all just probability."

"Even if it's just probability," Ellie mused, then suddenly added, "but a 50 percent discount isn't something you stumble upon every day!" Smiling, she winked at Rooney.

" Welcome!" a cheerful salesman greeted Rooney and Ellie at the entrance. Rooney regretted agreeing to go shopping with Ellie. They were on a quest to find the perfect pair of sunglasses, which had led them through various shops without success. " I know what I want," Ellie said, pointing to a pair of large sunglasses. The helpful salesman quickly fetched them. "There, I made a quick choice," she said to Rooney, heading to the cashier. "Unbelievable!" Rooney joked.

"That will be 110 dollars," the salesman said.

"What?" Ellie realized she forgot to ask the price amidst her spree.

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consecutive days is likely to continue rising. For example, during periods of stock market growth, investors may assume that a stock will continue to rise after a few days of positive returns, even if the increase is due to random fluctuations rather than any fundamental change in the company.

Research by Barberis, Shleifer, and Vishny (1998) demonstrated that investors often fall into this fallacy, making decisions based on the perceived continuation of trends rather than analyzing underlying data. This can lead to overconfidence and potentially risky investment strategies, as investors may ignore the role of chance and market randomness in price movements.

About: The hot-hand fallacy is a cognitive bias in which individuals believe that a person who has experienced success in a random event or activity is likely to continue experiencing success, even when the outcomes are statistically independent. This bias is most commonly observed in sports, where athletes who make a series of successful shots are perceived to be “on a roll” and expected to continue succeeding. The fallacy arises from the erroneous belief that streaks of success indicate skill or inherent ability, rather than the result of chance. While people may intuitively feel that someone who has succeeded multiple times in a row is more likely to continue succeeding, statistical evidence does not support this belief in contexts where outcomes are random or largely influenced by luck. The hot-hand fallacy has been studied extensively in sports psychology and decision- making, demonstrating how people misinterpret random events as predictive of future success.

Reproducibility: The hot-hand fallacy has been extensively studied and replicated in both laboratory and real-world settings. The study by Gilovich et al.

(1985) found that basketball players’ shooting success did not increase during streaks, contrary to what players and observers believed.

Subsequent research, such as that by Bar-Eli et al.

(2006), has replicated these findings, showing that the belief in the hot hand persists across different sports and even among professional players. Other studies, such as those by Roney and Trick (2009), have found that the hot-hand fallacy is not only prevalent in sports but also in financial markets, where people misjudge the continuation of successful trends. These consistent findings suggest that the hot-hand fallacy is a robust cognitive bias, one that affects decision-making in diverse contexts, including gambling, investment, and sports analysis.

Trivia Example: A well-known example of the hot-hand fallacy occurs in basketball. When a player makes several consecutive successful shots, fans, commentators, and even coaches may believe that the player is “on fire” and likely to continue making shots, despite the fact that the likelihood of future shots being successful is independent of past performance. A famous study by Gilovich, Vallone, and Tversky (1985) showed that both players and observers tended to overestimate the likelihood of a player continuing a streak, even though the success rate was no higher during streaks than during other periods. This misperception has led to overconfidence in players and teams, influencing strategic decisions and player evaluation, despite the randomness of the outcomes.

Selected References

Barberis, N., Shleifer, A., & Vishny, R. W. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343.

Bar-Eli, M., Plessner, H., & Raab, M. (2006). The hot-hand phenomenon: A review of the literature. Psychology of Sport and Exercise, 7(1), 3–21.

Gilovich, T., Vallone, R., & Tversky, A. (1985). The hot hand in basketball: On the misperception of random sequences.

Cognitive Psychology, 17(3), 295–314.

Roney, C. J. R., & Trick, L. M. (2009). Sympathetic magic and perceptions of randomness: The hot hand versus the gambler’s fallacy. Thinking & Reasoning, 15(2), 197–210.

Business Example: In business, the hot-hand fallacy can influence stock market trading, where investors believe that a stock that has performed well for several 263

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ILLUSION OF CONTROL The tendency to overestimate one's degree of influence over external events.

"Hi," Ellie said, looking Rooney up and down.

They had planned to attend a classical music concert today. Ellie's friend, Debika Rains, was singing in the choir and had given Ellie two tickets. As usual, Ellie was a bit late. She had spent a long time choosing the right dress, and the rain since lunch had made her journey longer than expected. Approaching the doors of the philharmonic, she noticed Rooney waiting for her at the entrance, completely soaked.

"Sorry I'm late," she said guiltily. "What happened to you? Why are you all drenched?" She just realized that Rooney's hair and suit were totally wet, with droplets running down his face.

"It just happened," he replied. "I forgot my umbrella today and got soaked. It always happens this way. If I had brought my umbrella, it surely wouldn’t have rained."

"Sure, of course!" Ellie laughed. "I don't think even 'great Rooney' can control the weather."

"I'm telling you," Rooney insisted, "I've noticed it. Every time I forget my umbrella, it rains, as if on cue."

"Don’t be ridiculous! Let's quickly go inside. You need to get sorted out! And the concert is about to start."

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selecting specific stocks, often engaging in frequent trading and taking higher risks, despite the random nature of stock price fluctuations.

Studies showed that investor sentiment often leads individuals to believe they can predict or influence market trends, which can result in overconfidence and poor investment strategies.

Similarly, in project management, managers may believe they can exert more control over project timelines and outcomes than is realistically possible, leading to overcommitment, unrealistic goal-setting, and the neglect of unforeseen risks.

This belief in control can result in frustration and failure when outcomes do not align with expectations (e.g., Obolensky, 2024).

Reproducibility: Langer’s (1975) early research demonstrated that individuals perceive greater control in situations of chance, and subsequent studies have reinforced these findings. For instance, studies in gambling behavior have replicated the illusion of control in casino environments, showing that individuals believe their actions influence random outcomes like dice rolls or card draws (e.g., Van de Calseyde et al., 2014; Wallsten et al., 1997). In the context of investing, research by Odean (1999) further confirmed that investors overestimate their ability to control or predict market movements, often resulting in excessive risk-taking and trading. These studies suggest that the illusion of control is a robust and replicable cognitive bias, affecting decisionmaking in a wide variety of domains.

Selected References

About: The illusion of control is a cognitive bias in which people believe they have control over outcomes that are actually determined by chance. This phenomenon occurs when individuals overestimate their ability to influence random or uncontrollable events, leading to overconfidence in their own skills or judgment. It is most commonly observed in gambling, sports, investing, and other high-stakes situations. For example, gamblers may believe that their superstitions or rituals, such as shaking dice in a specific way, can influence the outcome of a roll.

This bias can lead people to take unnecessary risks, miscalculate probabilities, and make suboptimal decisions. The illusion of control can be driven by personal experiences, where individuals recall instances when they succeeded in a random situation and mistakenly attribute it to their own actions. Langer’s (1975) seminal research on the illusion of control demonstrated how people perceive greater control in situations of randomness, particularly when they have prior success or feel more involved in the process.

Trivia Example: A common example of the illusion of control can be seen in the behavior of lottery players. While the odds of winning the lottery are the same for every ticket, individuals often believe that certain actions, such as choosing their own numbers or buying multiple tickets, increase their chances of winning. This is because they perceive that their involvement in the process gives them more control over the outcome, despite the fact that the lottery is a purely random event. In a study by Langer (1975), participants who chose their own lottery numbers were more likely to rate their chances of winning as higher than participants who received random numbers. This illusion of control can lead to continued gambling behavior, even in the face of overwhelming odds against winning.

Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328.

Obolensky, N. (2024). The illusion of control: The need for a new paradigm. Global Perspectives, 5(1), Article 117323.

Odean, T. (1999). Do investors trade too much? American Economic Review, 89(5), 1279-1298.

Van de Calseyde, P. P., Keren, G., & Zeelenberg, M. (2014).

Decision time as information in judgment and choice. Organizational behavior and human decision processes, 125(2), 113-122.

Wallsten, T. S., Budescu, D. V., Erev, I., & Diederich, A. (1997). Evaluating and combining subjective probability estimates. Journal of Behavioral Decision Making, 10(3), 243–268.

Business Example: Investors may feel they can “beat the market” by 265

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ILLUSORY CORRELATION The perception of a relationship between two variables when only a minor or no relationship actually exists.

"I think I bombed my physics exam," Ellie said sadly, sitting down next to Rooney at a café table, tossing her backpack carelessly on the floor.

"Why do you think that? You prepared well, and I even helped you," Rooney reassured her, confident that Ellie, as usual, was making a mountain out of a molehill.

"It's all because of this blue sweater," Ellie gestured to her sweater. "I'm always unlucky in it."

"That's nonsense," Rooney replied. "What does the sweater have to do with anything?"

"I'm telling you, this sweater is cursed. First, I twisted my ankle in it, then a neighbor's dog almost bit me, and I got soaked while carrying my advertising sketches in it. I should throw it away. If I'd worn my white sweater, the one from Oxford University, I would've been lucky. I always am in that one. But this stupid sweater just brings trouble. Probably why I failed the exam."

"Look," Rooney said confidently, "first, it's not certain you failed, and second, the sweater has nothing to do with it. Let's just have our coffee. I've already ordered."

"Here's your cappuccino," a pleasant voice said nearby. The waitress leaned over to place the tray of coffee and milk on the table but stumbled over the discarded backpack. The tray tilted towards Ellie, spilling everything. "I'm so sorry," she stammered, trying to wipe the coffee off Ellie's stunned face.

"There, I told you," Ellie exclaimed. "I need to get rid of this unlucky sweater. It's nothing but trouble."

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actual quality. This bias can also influence investor behavior. A study by Barberis et al. (1998) demonstrated that investors tend to overestimate the relationship between past performance and future outcomes. For example, an investor might believe that a company’s stock performance is strongly linked to its leadership style, even when other factors, such as market conditions or random fluctuations, have a more significant impact. This illusory correlation may lead investors to make suboptimal investment decisions, overvaluing stocks based on perceived patterns that don’t hold up in the long term.

Reproducibility: Hamilton and Gifford’s (1976) pioneering study on stereotypes has been reproduced numerous times, showing that people tend to form illusory correlations based on minimal or biased information. In the domain of social psychology, studies have consistently shown that people are more likely to remember and attach significance to instances that confirm their preexisting beliefs, particularly when those events are rare or emotionally charged. In the realm of finance, Barberis et al. (1998) found that investors tend to attribute performance trends to the management of a company, even when the correlation is weak or non-existent. More recent studies by Fiedler et al. (2006) have confirmed the persistence of illusory correlations, showing that people continue to form false associations even when provided with corrective feedback. These findings highlight the enduring and replicable nature of the bias in a wide variety of contexts.

Selected References

About: Illusory correlation refers to the cognitive bias where individuals perceive a relationship between two variables or events, even when no such relationship exists or when the correlation is much weaker than assumed. This phenomenon occurs because people are naturally inclined to seek patterns in the world around them, often resulting in the overestimation of the strength or presence of a connection. The bias is especially prevalent in situations where two events co- occur frequently but for random reasons, such as stereotypes or superstitions. The concept was first identified by Chapman’s (1967) research on the way people associate certain traits with specific groups, leading to the formation of false associations.

Illusory correlation has wide implications, from the formation of social stereotypes to the way people perceive causality in everyday life. For example, people may believe that a particular brand of soda leads to better performance at work simply because they’ve experienced success while drinking it on a few occasions, ignoring other factors that contributed to their success.

Trivia Example: The stereotype that people of a particular ethnicity are more likely to engage in criminal behavior is based on the illusory correlation between crime rates and that group, despite statistical evidence showing that crime rates are often more closely linked to socio- economic factors rather than ethnicity. In a study by Hamilton and Gifford (1976), participants were more likely to associate negative behaviors with minority groups, even though the actual rate of negative behaviors was not higher than that of majority groups. This misperception is driven by the fact that rare events (such as criminal behavior) are more likely to be remembered and associated with certain groups, leading to the false belief that the two are correlated.

Business Example: Consumers might perceive that a brand is linked to high quality simply because they have experienced a few positive interactions with it, even if those experiences were coincidental or influenced by factors unrelated to the product’s

Barberis, N., Shleifer, A., & Vishny, R. W. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343.

Chapman, L. J. (1967). Illusory correlations in observational report. Journal of Verbal Learning and Verbal Behavior, 6(2), 151-155.

Fiedler, K., Messner, C., & Bluemke, M. (2006). Unresolved problems with the “I”, the “A”, and the “T”: A logical and psychometric critique of the Implicit Association Test (IAT). European Review of Social Psychology, 17, 74–147.

Hamilton, D. L., & Gifford, R. K. (1976). Illusory correlation in interpersonal perception: A cognitive basis of stereotyping. Journal of Experimental Social Psychology, 12(5), 392-407.

Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328.

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ILLUSION OF VALIDITY Believing that one's judgments are accurate, especially when available information is consistent or inter-correlated.

"What are you doing?" Rooney called Ellie to arrange a time to pick her up for the Halloween party on Saturday. "When should I come by?"

"You know, I think I might not go," Ellie suddenly said. "Why not? What happened?"

"I don't know, I feel like my costume isn't quite right."

"What do you mean 'not right'? You designed and sewed it yourself. Your costume is awesome. I'm sure you'll win the best costume contest this year."

"I doubt it. Claire always wins, every year. It'll be the same this time, just watch.

She has such creative ideas. I’ve never beaten her."

"Just because Claire has won several years in a row doesn't mean she'll win tonight.

Everything will be fine. Don't worry, your costume is fantastic, and you know you're a design genius."

"I'm not so sure about that today," Ellie pondered.

"Listen, in the end, what does it matter what costume you wear or who wins?

I'm sure we'll have a great time. I'll pick you up at 10. Be ready!"

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stocks they believe will outperform based on apparent trends. Similarly, in business strategy, managers may rely on coherent but untested theories to make decisions, overlooking more rigorous analytical models. For example, a manager may prioritize employee engagement strategies based on anecdotal success stories without testing their effectiveness across different organizational contexts.

Such misplaced confidence in judgment can lead to poor resource allocation and decision-making (e.g., Amgain, 2024).

About: The illusion of validity refers to the cognitive bias where individuals overestimate the accuracy of their judgments or decisions, particularly when they rely on coherent but limited information.

This bias arises from the human tendency to favor consistency and patterns in data, leading to an overconfident belief in the correctness of a prediction, even when the evidence does not support such confidence. Kahneman and Tversky (1973) highlighted this bias in their studies on human judgment, showing how people often mistake coherence in data for validity, ignoring base rates or statistical reliability. For example, in hiring decisions, recruiters may feel confident in their ability to predict a candidate’s success based on interview performance, despite evidence showing that structured methods like work sample tests are more predictive. This misplaced confidence in the coherence of information can result in suboptimal decisions.

Reproducibility: Kahneman and Tversky’s (1973) foundational work demonstrated the bias in statistical prediction tasks, where participants often ignored base rates in favor of coherent but misleading patterns. Subsequent research, such as that by Klayman et al. (1999), showed that this bias persists even when individuals are trained to identify statistical errors. In applied settings, studies confirm the bias’s presence in sports scouting, investment behavior, and managerial decision-making (e.g., Arkes, 1981; Oskamp, 1965). These consistent findings showcase the illusion of validity as a robust and replicable phenomenon, emphasizing the need for decision-making frameworks that prioritize evidence over intuition.

Trivia Example: The illusion of validity can be seen in sports scouting. Scouts often believe they can predict an athlete’s future success based on a small set of performance metrics, such as speed or strength during trials, coupled with subjective impressions. However, research by Massey et al.

(2011) found that these evaluations often fail to account for broader factors like adaptability or consistency. The illusion of validity leads scouts to overestimate their ability to identify talent based on limited, coherent data while undervaluing broader statistical models that consistently outperform subjective evaluations.

Selected References

Arkes, H. R. (1981). Implications of judgmental heuristics for managerial decision making. Academy of Management Review, 6(2), 221–230.

Amgain, P. N. (2024). Behavioral Biases and Investment Decision: A Systematic Literature Review. Kanya Journal, 5(1), 1239.

Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80(4), 237–251.

Klayman, J., Soll, J. B., González-Vallejo, C., & Barlas, S. (1999). Overconfidence: It depends on how, what, and whom you ask. Organizational Behavior and Human Decision Processes, 79(3), 216–247.

Oskamp, S. (1965). Overconfidence in case-study judgments. Journal of Consulting Psychology, 29(3), 261– 265.

Business Example: The illusion of validity is particularly pervasive.

Investors often feel confident in their ability to predict market trends based on patterns in historical data, even when these patterns lack statistical significance. Studies demonstrated how investor sentiment drives the illusion of validity, leading individuals to overinvest in 269

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ILLUSORY TRUTH EFFECT The tendency to believe false information to be correct after repeated exposure.

"Where are you off to?" Ellie bumped into Rooney on the street. He seemed to be in a hurry.

"We have a small celebration at the tennis club today. The coronavirus restrictions have been eased a bit, so we decided to have a little party," Rooney replied cheerfully, clearly having missed social events during the quarantine.

"Understood. But be careful. Despite the lifted restrictions, the virus is still a big risk.

Having a party at this time might not be the best idea."

"Don’t worry, I'm always taking vitamin C. I’ll be fine."

"What does vitamin C have to do with it? Where did you even get that idea?"

"From everywhere. They say taking vitamin C significantly reduces the chance of getting infected."

"I don't know where you heard that, but it's nonsense. Social distancing, masks, and vaccination are what help against the coronavirus. Even if you were vaccinated, it doesn’t completely protect you. Where did you find this information about vitamin C?" "I don’t know, everyone says so," Rooney shrugged. "Well, they're wrong. Social distancing is important." "Okay, I get it. I promise I won’t get too close to anyone."

"Good. See you tomorrow!"

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ethical sourcing, even when such practices are not rigorously followed. Research by Pennycook, Cannon, and Rand (2018) demonstrated that repetition of information increases consumer trust in brands, even when the claims are vague or unverifiable. This effect can also influence workplace culture; repeated narratives about a company’s innovation, for example, can lead employees to perceive the organization as innovative, even if evidence of groundbreaking developments is lacking. This highlights the importance of transparency and factual accuracy in corporate communications to maintain ethical practices.

About: The illusory truth effect describes the cognitive bias where repeated exposure to a statement increases the likelihood that people perceive it as true, regardless of its actual validity. This effect occurs because familiarity with information is often mistaken for accuracy, driven by the brain’s tendency to favor ease of processing (fluency).

First identified by Hasher, Goldstein, and Toppino (1977), the phenomenon highlights how repetition can shape beliefs, even in the absence of supporting evidence. The illusory truth effect is particularly concerning in the context of misinformation and fake news, where repeated exposure to false claims can lead people to accept them as factual. This effect demonstrates the importance of critical thinking and source verification in an age where information is easily disseminated but not always accurate.

Reproducibility: The original study by Hasher et al. (1977) showed that repeated statements were more likely to be judged as true compared to novel ones. More recent work by Fazio et al. (2015) replicated these findings, confirming that repetition increases perceived truth even for statements explicitly labeled as false. Furthermore, a study by Pennycook et al. (2018) demonstrated the effect in the context of fake news, showing that repeated exposure to false headlines increased their perceived accuracy among social media users.

These consistent results across domains such as marketing, social media, and political communication highlight the robustness and real-world relevance of the illusory truth effect, particularly in an era of digital misinformation.

Trivia Example: One example of the illusory truth effect can be seen in advertising. Slogans like “XYZ toothpaste is the most recommended by dentists” often rely on repetition to create a perception of credibility.

Even if the claim lacks substantiation, repeated exposure can make consumers believe it to be true. A study by Fazio et al. (2015) demonstrated that even when participants were told a statement was false, repeated exposure increased their belief in its truth. This illustrates how the brain’s reliance on familiarity over critical evaluation can lead to the acceptance of falsehoods, especially when critical thinking is not actively engaged.

Selected References

Fazio, L. K., Brashier, N. M., Payne, B. K., & Marsh, E. J. (2015).

Knowledge does not protect against illusory truth. Journal of Experimental Psychology: General, 144(5), 993–1002.

Hasher, L., Goldstein, D., & Toppino, T. (1977). Frequency and the conference of referential validity. Journal of Verbal Learning and Verbal Behavior, 16(1), 107–112.

Pennycook, G., Cannon, T. D., & Rand, D. G. (2018). Prior exposure increases perceived accuracy of fake news. Journal of Experimental Psychology: General, 147(12), 1865–1880.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Business Example: The illusory truth effect plays a significant role in marketing and public relations. Repeated advertisements or branding messages can shape consumer perceptions, even when the claims lack evidence. For instance, companies often repeat slogans emphasizing sustainability or 271

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MERE EXPOSURE EFFECT The tendency to develop a preference for things merely because they are familiar with them.

"Hey, what music is this playing?" Ellie asked irritably. "It's just awful! I hate this song.

Can I find something else on your phone?"

Rooney listened for a moment.

"Ah, yeah, you know, I didn't like this song at first either. But it's often on social media, and it gets a lot of radio play too. I've kind of gotten used to it. It doesn’t bother me.

But if you don't like it, go ahead and change it to something else."

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colors, and slogans appear ubiquitously across media platforms, creating a sense of familiarity that translates into consumer trust and loyalty.

For instance, research by Fang et al. (2007) demonstrated that repeated exposure to a product significantly increased consumer preference, even when participants were unaware of the frequency of exposure. The effect is particularly potent in crowded markets where distinguishing features among competing brands are subtle, yet familiar branding tips the scale.

About: The mere exposure effect describes the psychological phenomenon where repeated exposure to a stimulus increases an individual’s preference for it, even in the absence of conscious awareness. This bias, first systematically studied

by Robert Zajonc in 1968, highlights the human tendency to associate familiarity with positivity.

Evolutionary explanations suggest that the mere exposure effect developed as a survival mechanism, encouraging individuals to favor known, safe stimuli over unknown and potentially threatening ones. It extends across sensory modalities—visual, auditory, and tactile stimuli all elicit this effect. However, it operates within a delicate balance; while moderate repetition enhances liking, excessive exposure can lead to habituation or even aversion. This effect has profound implications for fields ranging from advertising to interpersonal relationships, shaping how preferences are formed and maintained.

Reproducibility: Zajonc’s (1968) pioneering experiments have been confirmed across diverse contexts, with consistent findings indicating that repeated exposure leads to enhanced affective responses toward stimuli. Meta-analysis by Bornstein (1989) has substantiated the robustness of the effect across cultures, ages, and modalities.

However, research also reveals boundary conditions: for example, overexposure can reverse the effect, leading to aversion, known as the “wear-out effect.” This nuanced dynamic makes the mere exposure effect a practical tool in fields like marketing, where strategic repetition is critical (e.g., Bornstein and Craver-Lemley, 2022).

Trivia Example: A compelling example of the mere exposure effect is evident in film and music. Audiences often grow to enjoy songs or movie franchises they initially found unremarkable after encountering them repeatedly. For instance, repetitive airplay of pop songs on radio stations often transforms unfamiliar tracks into favorites.

This effect is also prevalent in cinema, where sequels of successful franchises leverage familiarity to maintain audience engagement and boost revenues.

Selected References

Bornstein, R. F. (1989). Exposure and affect: Overview and metaanalysis of research, 1968–1987. Psychological Bulletin, 106(2), 265–289.

Bornstein, R. F., & Craver-Lemley, C. (2022). Mere exposure effect. Cognitive illusions, 241-258.

Fang, X., Singh, S., & Ahluwalia, R. (2007). An examination of different explanations for the mere exposure effect.

Journal of Consumer Research, 34(1), 97-103.

Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of Personality and Social Psychology, 9(2), 1-27.

Business Example: The mere exposure effect forms the backbone of advertising and branding strategies. Companies like McDonald’s or Apple ensure their logos, 273

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NORMALCY BIAS The refusal to plan for, or react to, a disaster which has never happened before..

"Hi, we got quite scared by the earthquake last night. Spent half the night outside after the tremors. How about you? Is everything okay? How's your little brother? And your mom?"

Rooney's sleepy voice came through the phone, clearly just woken up. "Ellie, do you realize it's 5 AM? Normal people are still asleep."

"How can anyone sleep after an earthquake?"

Ellie persisted.

"Earthquake? What earthquake?" Rooney's voice still sounded groggy.

"Didn’t you hear about the earthquake? The whole city is talking about it. There were strong tremors last night!" "Really?"

Rooney scratched his head.

"How could you not notice? We all woke up and ran out of the house, stayed out for a long time before going back in."

"I don’t know, we didn't feel anything. Mom and my brother are still asleep. Probably because we lived in Japan for a long time.

Earthquakes are common there. When I was little, my mom worked there. I'm used to it."

"That's unbelievable! You should at least watch the news. Next time something like this happens, I'll call you right away."

"Alright, alright, I'll check everything now.

Thanks for calling!" Rooney stretched and hung up the phone.

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to outdated paradigms. Research by Taleb (2007) on “Black Swan” events shows how businesses often fail to anticipate and prepare for rare but transformative events, favoring past patterns over proactive adaptation. Similarly, during the COVID-19 pandemic, many companies delayed transitioning to remote work and digital operations, underestimating the pandemic’s long-term impact. The normalcy bias can lead to missed opportunities and heightened vulnerabilities during periods of rapid change.

About: The normalcy bias refers to a cognitive distortion that leads individuals to underestimate the possibility and severity of catastrophic events, thereby delaying or avoiding appropriate action.

This phenomenon stems from the psychological preference for stability and predictability, which can cause people to cling to the belief that their current circumstances will persist despite evidence to the contrary. Researchers such as Mileti and Sorensen (1990) have emphasized that this bias can impede effective disaster preparedness and response, as individuals often misinterpret warnings or fail to internalize their urgency. Kahneman and Tversky’s (1979) prospect theory further illuminates how individuals weigh risks conservatively, often underestimating rare but high-impact events.

This bias has implications across various domains, including natural disaster response, organizational crisis management, and public health planning.

Reproducibility: Mileti and Sorensen’s (1990) studies on disaster response found that individuals frequently disregard early warnings due to an ingrained belief that their circumstances will remain stable.

Perry and Lindell (2008) demonstrated similar tendencies in hurricane evacuation behavior, where residents delayed action despite clear warnings. Experimental research by Drabek (2013) corroborated these findings, showing that individuals exposed to simulated crises often misjudge the urgency of their situation. More recent studies, such as those by Meyer et al.

(2013), highlight how this bias operates during financial crises, where investors cling to past trends despite emerging market risks. These studies affirm the robustness of the normalcy bias and its relevance across diverse domains.

Trivia Example: The normalcy bias was starkly demonstrated during the eruption of Mount Vesuvius in A.D. 79. Despite observable signs of volcanic activity, the residents of Pompeii continued their daily routines, dismissing the possibility of disaster.

Similar patterns emerged during Hurricane Katrina in 2005, when many residents of New Orleans delayed evacuation, assuming the storm’s impact would not deviate significantly from previous hurricanes. Such historical and modern examples highlight how this bias persists across cultures and eras, shaping human behavior in critical moments.

Selected References

Drabek, T. E. (2013). The human side of disaster. CRC Press.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Meyer, R., Becker, M., & Mark, M. M. (2013). Predicting the impact of crisis events on insurance markets. Journal of Risk and Uncertainty, 46(3), 243–271.

Mileti, D. S., & Sorensen, J. H. (1990). Communication of emergency public warnings: A social science perspective and state-of-the-art assessment. Oak Ridge National Laboratory.

Perry, R. W., & Lindell, M. K. (2008). Preparedness for emergency response: Guidelines for the emergency planning process.

Disaster Management & Response, 3(4), 190–196.

Taleb, N. N. (2007). The Black Swan: The impact of the highly improbable. Random House.

Business Example: The normalcy bias often manifests during technological disruption or economic shifts.

Kodak’s failure to pivot to digital photography, despite clear market trends in the late 20th century, illustrates how organizations can cling 275

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OMISSION BIAS The tendency to judge harmful actions as worse, or less moral, than equally harmful omissions (inactions). of the month, and the film within 90 days."

"Why even think about it? I've seen that application on your desk for four weeks.

You should have filled it out and sent it already."

"But what's there to think about? I've only tried making a film once. It won't work out. And winning the competition is impossible. I have no experience. I don't even know where to start."

"Let's think logically," Rooney said, sitting beside her. "What are the chances you'll win this contest?"

"Minimal…" Ellie sighed.

"Alright, but it's still a positive chance, even if minimal, right?" "I agree," Ellie pondered again.

"And if you don’t participate, what are your chances?" Rooney continued.

"Zero..." Ellie admitted.

"Exactly! See, you need to participate! Any chance greater than zero means you should at least try!"

"I don't know," Ellie picked up the application from the desk and placed it on the shelf. "I'll think about it," she said.

"What's there to think about?" Rooney was determined. "You already have a script, I know. I'll help you shoot and edit it. I'll even help find actors. What do you say?

Are you in?"

"I don't know," Ellie sighed again. "I still need to think about it…"

"What are you thinking about?" Rooney asked, noticing that Ellie seemed deep in thought.

"I don't know what to do," Ellie shrugged. "I've been offered to participate in a short film competition. What do you think? The application has to be submitted by the end 276

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or entering emerging markets, fearing potential risks, even though inaction might result in missed opportunities or eventual obsolescence.

Research by DeScioli et al. (2011) on environmental risk management found that companies often delay adopting sustainable practices due to the perception that actions (e.g., implementing costly green technologies) pose greater risks than inaction, even when the longterm consequences of failing to act are more detrimental.

About: Omission bias is a cognitive bias in which individuals judge harmful actions as worse or less morally acceptable than equally harmful omissions (inactions). This bias stems from the human tendency to perceive active decisions as more culpable than passive ones, even when the outcomes are identical. Ritov and Baron (1990) highlighted this phenomenon in their seminal research, demonstrating how people consistently rate the moral acceptability of harmful omissions higher than that of harmful actions. Omission bias has significant implications in medical ethics, policymaking, and legal judgments, where inaction can be as consequential as deliberate action.

Psychologically, this bias is rooted in the aversion to guilt and blame associated with direct actions, compounded by the comfort of adhering to the status quo.

Reproducibility: Omission bias has been consistently replicated in experimental and applied settings. Ritov and Baron’s (1990) foundational studies demonstrated the bias in moral judgments across various scenarios. Subsequent research, such as that by Spranca et al. (1991), confirmed these findings in decision-making contexts, highlighting the bias’s influence in medical and legal settings. Experimental studies by Cushman et al. (2006) further explored the neural mechanisms underlying omission bias, showing that it involves distinct emotional and cognitive processes compared to judgments about harmful actions. These findings emphasize the omission bias relevance across domains such as public health, law, and organizational behavior.

Trivia Example: A classic illustration of omission bias occurs in vaccination hesitancy. Parents may avoid vaccinating their children due to fear of potential adverse reactions, even though the risk of harm from not vaccinating (e.g., contracting a preventable disease) is statistically higher. This preference for inaction stems from the perception that harm caused by a decision to vaccinate would be more culpable than harm resulting from inaction, despite evidence showing the benefits of vaccination far outweigh the risks.

References

Cushman, F., Young, L., & Hauser, M. (2006). The role of reasoning and intuition in moral judgments: Testing three principles of harm. Psychological Science, 17(12), 1082–1089.

DeScioli, P., Christner, J., & Kurzban, R. (2011). The omission strategy. Psychological science, 22(4), 442-446.

Ritov, I., & Baron, J. (1990). Reluctance to vaccinate: Omission bias and ambiguity. Journal of Behavioral Decision Making, 3(4), 263–277.

Spranca, M., Minsk, E., & Baron, J. (1991). Omission and commission in judgment and choice. Journal of Experimental Social Psychology, 27(1), 76–105.

Business Example: Omission bias can influence risk management and strategic decision-making. For instance, executives may avoid adopting new technologies 277

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OSTRICH EFFECT The decision to ignore dangerous or negative information by "burying" one's head in the sand, like an ostrich.

"You're eating sweets again!" Rooney looked disapprovingly at Ellie, who was finishing off a piece of apple pie with cream.

Ellie blushed, realizing she'd been caught redhanded.

"Listen, I didn't force you. You wanted to eat right and lead a healthy lifestyle."

"One piece of pie won't hurt!" Ellie declared, finding the strength to argue.

"Maybe not one, but the day before yesterday it was ice cream, yesterday a caramel milkshake, and today pie!"

"Are you keeping tabs on me?"

"That's not the point," Rooney retorted. "You asked me to help you avoid sweets! Do you know how much sugar is in all these - ice cream, milkshakes, pie? Let me find the numbers online," he said, grabbing his smartphone.

"I don’t want to know!" Ellie protested.

"No, let's look!" Rooney insisted.

"I don’t want to see anything!" Ellie moved away from Rooney and closed her eyes, clearly indicating she wasn't interested in the figures.

"Just remember, while you're burying your head in the sand like an ostrich and ignoring all this, your life won't change!"

"Alright!" Ellie pondered. "You're right. I swear – from tomorrow, no more sugar!"

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volatility, choosing to ignore updates on their investments rather than facing potentially distressing information. Similarly, managers in businesses may delay reviewing underperforming projects, fearing the need to make difficult decisions like scaling back operations or reallocating resources. This reluctance can lead to prolonged inefficiencies and financial losses, as avoiding problems does not eliminate their underlying causes.

About: The ostrich effect describes a cognitive bias in which individuals deliberately avoid information that may indicate potential problems or negative outcomes. This bias is metaphorically named after the mistaken belief that ostriches bury their heads in the sand to avoid danger. In reality, the ostrich effect highlights a human tendency to evade distressing or undesirable information, particularly in contexts such as financial decision-making, health-related concerns, or interpersonal conflicts. Researchers like Karlsson, Loewenstein, and Seppi (2009) identified this bias in their study of investors, noting that people often avoid monitoring their investments during volatile periods to reduce stress and anxiety. This phenomenon stresses the role of emotional regulation in decisionmaking, where individuals prioritize short-term comfort over long-term benefits.

Reproducibility: The ostrich effect has been reliably replicated across various settings, particularly in financial and health-related decision-making. Karlsson et al.’s (2009) research showed that investors are more likely to log in and monitor their portfolios during stable or positive market conditions, avoiding such behavior during downturns.

Additional studies, such as those by Sicherman et al. (2016), confirmed this pattern, demonstrating that selective information avoidance occurs even when awareness could lead to better decisionmaking. Experimental research by Golman, Hagmann, and Loewenstein (2017) further highlights the mechanisms underlying this bias, showing how emotional costs associated with receiving negative information drive avoidance behaviors. These findings confirm the ostrich effect’s robustness and emphasize its implications for individual and organizational decision-making.

Trivia Example: An everyday illustration of the ostrich effect occurs in personal health. Individuals may avoid regular health check-ups or screening tests, fearing a diagnosis of a serious illness, despite the fact that early detection could significantly improve outcomes. This avoidance behavior can lead to delayed interventions and poorer health outcomes, highlighting the psychological cost of information avoidance.

Business Example: The ostrich effect is particularly prominent in financial contexts, where investors may avoid checking their portfolios during market downturns to reduce stress. Karlsson et al. (2009) demonstrated that investors often engage in “selective ignorance” during periods of market

Selected References

Golman, R., Hagmann, D., & Loewenstein, G. (2017). Information avoidance. Journal of Economic Literature, 55(1), 96–135.

Karlsson, N., Loewenstein, G., & Seppi, D. (2009). The ostrich effect: Selective attention to information. Journal of Risk and Uncertainty, 38(2), 95–115.

Sicherman, N., Loewenstein, G., Seppi, D., & Utkus, S. (2016).

Financial attention. The Review of Financial Studies, 29(4), 863–897.

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PAREIDOLIA The tendency to interpret vague and random stimuli (often an image or sound) as something meaningful, e.g., seeing shapes in clouds.

"Great, I've spilled coffee on my skirt again," Ellie lamented, dabbing at the coffee stains on her skirt. "This always happens to me. Every time I wear a new skirt, I'm bound to stain it."

"Just go and soak the stain quickly; it'll come off.

I'll wait for you," Rooney said, offering Ellie another napkin.

"No way, I'm not going to the bathroom here.

Their sinks look like faces. I'll have nightmares about it," Ellie declared.

"What are you talking about? Faces! There are no faces on the sinks."

"I'm telling you, I'm not going there!"

"Okay," Rooney said confidently, "then let's go – we'll head to the café across the street.

Hopefully, the sinks there are normal, and you won't see faces in the bathroom!"

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design, with its curved frame and headlight “eyes,” is a classic case of intentional pareidolia, making the vehicle appear friendly and approachable. Similarly, packaging designs that subtly incorporate facial elements can enhance consumer attachment to products, leveraging the psychological comfort of recognizable patterns.

About: Pareidolia is a cognitive bias in which people perceive meaningful patterns, such as faces, in random or ambiguous stimuli. This phenomenon stems from the brain’s tendency to find structure and familiarity in chaotic environments, a survival mechanism that likely evolved to identify threats or social cues quickly. For instance, seeing a face in the moon or patterns resembling animals in clouds are classic examples of pareidolia. Research by Liu et al.

(2014) suggests that this bias is rooted in the human brain’s specialized ability to process facial patterns, even in abstract or distorted forms.

Pareidolia not only accentuates our perceptual biases but also reveals how our cognitive processes prioritize recognizable stimuli over randomness, often interpreting ambiguous inputs in ways that align with prior experiences.

Reproducibility: Pareidolia has been extensively studied and replicated in psychological and neuroscientific research.

Studies using neuroimaging techniques, such as those by Liu et al. (2014), show that pareidolia activates the fusiform face area of the brain, the same region responsible for recognizing human faces. Research by Taubert et al. (2017) further confirmed that pareidolia is a robust phenomenon, occurring even in lowresolution or distorted visual inputs. While cultural and individual differences influence the specific patterns recognized, the underlying bias to seek familiar shapes is universal, demonstrating the replicable and cross-cultural nature of pareidolia.

Trivia Example: Pareidolia is famously associated with cultural phenomena like seeing religious figures in everyday objects. For instance, in 2004, a grilled cheese sandwich reportedly bearing the image of the Virgin Mary was sold on eBay for $28,000.

Such occurrences demonstrate how this bias can intersect with personal beliefs and social narratives, amplifying its significance in collective culture.

Selected References

Liu, J., Li, J., Feng, L., Li, L., & Tian, J. (2014). Seeing Jesus in toast: Neural and behavioral correlates of face pareidolia.

Cortex, 53, 60–77.

Taubert, J., Wardle, S. G., & Flessert, M. (2017). Seeing faces where there are none: Pareidolia in the fusiform face area.

Journal of Cognitive Neuroscience, 29(7), 996–1007.

Kaplan, J. T., & Iacoboni, M. (2006). Getting a head start on the “who” system: Pattern recognition of facial features.

Cerebral Cortex, 16(5), 593–600.

Freud, E., & Behrmann, M. (2017). The face of pareidolia: Neural correlates of seeing faces in non-face objects. Social Cognitive and Affective Neuroscience, 12(5), 735–745.

Business Example: Businesses often harness pareidolia in branding and marketing strategies. For example, logos with human-like features or anthropomorphic designs evoke a sense of relatability and emotional connection. The Volkswagen Beetle’s

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REACTIVE DEVALUATION Devaluing proposals only because they purportedly originated with an adversary.

"Rooney, hi," Ellie called him late in the evening.

"Can you believe it? Crazy Katie is spreading wild rumors about you!"

"What rumors?" Rooney asked.

"Just imagine, she's been telling everyone today that you're leaving for Stockholm for a month. I can't stand Katie! She's always lying, it's disgusting! I told her straight away that if you were really going, you would have told me first. To make up such a thing – that takes some doing!"

"Ellie, the thing is, it's all true. I am indeed going to Sweden for a month." Silence fell on the other end of the line.

"Don't be upset," Rooney continued, "you see, Paul was supposed to go, but he fell ill at the last minute, so I'm going instead. Katie is Paul’s sister and she knows what's happening. So, you were wrong, she wasn't deceiving you. I was planning to tell you tomorrow in person, didn’t want to say it over the phone."

"And you call yourself a friend!" Ellie responded angrily. "Why am I always the last to know?"

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organizational settings demonstrates that parties often reject offers from competitors, even when the offers objectively align with their interests. This bias can hinder innovation, collaboration, and long-term profitability, as opportunities are missed due to distrust or prejudice toward the source.

About: Reactive devaluation is a cognitive bias where individuals devalue proposals or offers simply because they originate from an opposing party or perceived adversary. This bias often stems from distrust, preconceived notions, or emotional responses rather than objective evaluation of the proposal itself. Ross and Stillinger (1991) introduced the concept in conflict resolution contexts, showing that even identical proposals are judged more harshly when they come from opposing groups. Reactive devaluation plays a critical role in diplomacy, negotiations, and organizational decision-making, where biases against the source can obstruct constructive agreements. The bias reveals how emotions and group identity often supersede rational assessments in human interactions.

Reproducibility: The reactive devaluation effect has been repeatedly demonstrated in both experimental and real-world contexts. Ross and Stillinger (1991) conducted foundational research showing that participants devalued identical proposals when attributed to adversarial groups. More recently, Maoz et al. (2002) explored the phenomenon in Israeli-Palestinian peace negotiations, finding that offers from the “other side” were consistently perceived as less favorable. Studies by Curhan et al. (2006) further replicated these findings in organizational and interpersonal negotiations, showing the robustness of reactive devaluation across diverse settings. These studies highlight how deeply ingrained this bias is in human decision-making and its persistence across cultural and situational boundaries.

Trivia Example: A historical instance of reactive devaluation occurred during the Cold War when disarmament proposals from either the United States or the Soviet Union were often dismissed outright by the opposing side. Despite the potential benefits of such agreements, distrust and animosity led each side to question the motives and sincerity of the other, delaying meaningful progress.

Selected References

Bazerman, M. H., & Neale, M. A. (1992). Negotiating rationally.

Free Press.

Curhan, J. R., Neale, M. A., & Ross, L. (2006). Attribution in negotiation: How attributions about the source of the proposal can shape negotiation outcomes. Organizational Behavior and Human Decision Processes, 101(2), 152–167.

Maoz, I., Ward, A., Katz, M., & Ross, L. (2002). Reactive devaluation of an “enemy” offer in the Israeli–Palestinian conflict. Journal of Conflict Resolution, 46(4), 515–546.

Ross, L., & Stillinger, C. (1991). Barriers to conflict resolution.

Negotiation Journal, 7(4), 389–404.

Business Example: In business negotiations, reactive devaluation frequently manifests in mergers and acquisitions. For instance, when an offer to collaborate comes from a rival company, it may be dismissed due to perceived ulterior motives, even if the proposal is mutually beneficial.

Research by Bazerman and Neale (1992) in

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RISK COMPENSATION/PELTZMAN EFFECT The tendency to take greater risks when perceived safety increases.

"Are you not going to close the door?" Ellie asked. "It'll shut itself," Rooney replied nonchalantly.

"It might, but I wouldn’t leave the door wide open like that!"

"Don't worry. We got a new security system installed yesterday, so the house is fully protected. It's the best in the country."

"Just because you have a new security system doesn’t guarantee complete safety, and it doesn’t mean you should leave the door open like that! If you’ve become complacent and think the risk of burglary is low, it doesn’t necessarily mean it is."

"Alright, alright – I'll close the door now and let's head to the café!" Rooney said, shutting the door.

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Peltzman effect is seen when investors adopt riskier strategies during economic stability, assuming regulatory mechanisms or insurance will safeguard their investments. This behavioral response highlights the challenge of designing interventions that balance safety enhancements with behavioral incentives.

About: The risk compensation effect, also known as the Peltzman effect, describes a behavioral phenomenon where individuals adjust their behavior in response to perceived levels of risk.

When safety measures are introduced, people may engage in riskier behavior, effectively offsetting the intended safety benefits. This concept was first articulated by Sam Peltzman (1975) in the context of automobile safety regulations, where he argued that drivers compensated for increased safety features (e.g., seat belts) by driving more aggressively. Risk compensation has broad implications across public health, road safety, finance, and workplace practices, highlighting the complexities of human responses to interventions designed to reduce harm.

Reproducibility: The Peltzman effect has been validated through numerous empirical studies across various domains. Peltzman’s (1975) foundational work on automobile safety demonstrated that accident rates did not decrease significantly after the introduction of seat belt laws due to compensatory behaviors. Subsequent research

by Hedlund (2000) confirmed similar patterns in other areas, such as bicycle helmet use and financial risk-taking. Studies on examination of traffic safety further emphasize how perceived risk influences behavior (e.g., Grabiszewski and Horenstein, 2024). Research such as by Morrongiello et al. (2017), have replicated the effect in public health, showing how safety measures can sometimes lead to increased risky behaviors, highlighting the robustness of this phenomenon.

Trivia Example: One notable example of risk compensation is seen in sports, particularly in American football.

Research has shown that players wearing advanced protective gear, such as helmets and pads, may tackle with greater force, increasing the likelihood of injuries despite improved safety equipment. Similarly, skiers and snowboarders wearing helmets have been found to take more risks, like skiing at higher speeds or attempting dangerous slopes, counteracting the safety benefits of wearing protective headgear.

Selected References

Grabiszewski, K., & Horenstein, A. (2024). Unraveling the Peltzman Effect: The Significance of Agent’s Type. Review of Law & Economics, 20(1), 65-82.

Hedlund, J. (2000). Risky business: Safety regulations, risk compensation, and individual behavior. Injury Prevention, 6(2), 82–89.

Morrongiello, B. A., Walpole, B., & Lasenby, J. (2017).

Understanding children’s injury-risk behavior: Wearing safety gear can lead to increased risk taking. Accident Analysis & Prevention, 39(3), 617–623.

Peltzman, S. (1975). The effects of automobile safety regulation.

Journal of Political Economy, 83(4), 677–725.

Business Example: Risk compensation is evident in workplace safety initiatives. For example, when companies implement robust safety measures, such as automatic shut-off systems or protective equipment, workers may take more shortcuts or become less vigilant, believing the equipment will mitigate risks. In the financial sector, the 285

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RHYME AS REASON EFFECT Rhyming statements are perceived as more truthful. ”It happened again… My work was selected for the local exhibition, not the international one," Ellie said, disappointed. "But maybe it's for the best? My grandma used to say, 'East or west, home is best’... There's no place like home, right?"

"Listen to yourself, what nonsense are you talking about!" Rooney countered. "What kind of logic is that? So they didn’t pick your work this time, they might next time.

You’ve only submitted your work to two contests and you’re already giving up. And you're using some old rhymed proverb as your argument! That's silly. You need to create more artwork and submit it to various selections. Eventually, they will start accepting them. You’ll see! Don't fall apart. Pull yourself together."

"Okay," Ellie smiled, "I'll give it a try."

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fluency with credibility. For instance, insurance giant Nationwide’s slogan, “Nationwide is on your side,” effectively employs rhyme to foster trust and relatability. Research by Song and Schwarz (2008) suggests that consumers are more likely to trust rhyming claims in advertisements, even when the underlying content is identical to non-rhyming versions, highlighting the strategic advantage of using rhyme in competitive markets.

About: The rhyme-as-reason effect refers to a cognitive bias where people are more likely to judge rhyming statements as truthful or persuasive compared to non- rhyming ones, even when the content is identical. This phenomenon is rooted in the human preference for fluency—the ease with which information is processed— which enhances the perceived credibility and appeal of the message. McGlone and Tofighbakhsh (2000) explored this effect through experiments demonstrating that participants rated rhyming aphorisms (e.g., “What sobriety conceals, alcohol reveals”) as more accurate than their nonrhyming counterparts. The bias has significant implications for marketing, legal arguments, and political communication, where rhetorical strategies leveraging rhyme can disproportionately influence judgments and decisions.

Reproducibility: The rhyme-as-reason effect has been consistently replicated in psychological research.

McGlone and Tofighbakhsh’s (2000) experiments provided the first robust evidence of the effect, showing that rhyming aphorisms were judged as more accurate across diverse participant groups. Subsequent studies by Song and Schwarz (2008) demonstrated the effect in consumer decision-making, where rhyming product descriptions were rated as more believable. The cross-cultural consistency of this bias further emphasizes its robustness, as studies have found similar patterns in languages with strong poetic traditions, such as Mandarin and Spanish (Schindler and Gollwitzer, 2020). These findings confirm the reliability of the rhyme-asreason effect as a pervasive and influential cognitive bias.

Trivia Example: An example of the rhyme-as-reason effect is the enduring popularity of advertising slogans like “A Mars a day helps you work, rest, and play.”

Despite lacking substantive evidence, the slogan’s rhyming structure makes it memorable and persuasive, contributing to the product’s branding success. Similarly, rhyming phrases like “If the glove doesn’t fit, you must acquit” famously influenced jury perceptions during the O.J. Simpson trial, demonstrating the rhetorical power of rhyme in shaping legal judgments.

Selected References

McGlone, M. S., & Tofighbakhsh, J. (2000). Birds of a feather flock conjointly (?): Rhyme as reason in aphorisms.

Psychological Science, 11(5), 424–428.

Schindler, I., & Gollwitzer, M. (2020). The persuasive power of rhymes: Effects on judgment across cultures. Journal of Experimental Social Psychology, 89, 103994.

Song, H., & Schwarz, N. (2008). Fluency and the detection of misleading questions: Low processing fluency attenuates the Moses illusion. Social Cognition, 26(6), 791–799.

Business Example: The rhyme-as-reason effect plays a critical role in branding and marketing. Companies often employ rhyming slogans or jingles to create memorable associations with their products, capitalizing on the cognitive bias that equates 287

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SUBJECTIVE VALIDATION Perception that something is true if a subject's belief demands it to be true. Also associated with the validation of statements by personal belief and desire.

"Just don’t feel like it."

"Alright, spill it. What’s going on?" Rooney insisted.

"Nothing's wrong. It’s just that my horoscope for tomorrow says I should avoid social gatherings and hanging out with friends," Ellie said earnestly.

"You’re not seriously going to stay home just because of what your horoscope says!"

Rooney thought Ellie was joking.

"You might not believe it, but my horoscopes always come true." Rooney realized this was no joke.

"What else have you come up with?"

"I’m not making it up. Remember when I twisted my ankle at the gym three weeks ago? My horoscope that day warned me to be cautious about physical activity and sports. And remember when I caught a cold after eating ice cream? My horoscope had advised me to take care of my health that day."

"Ellie, that’s just self-fulfilling prophecy!

Horoscopes are always vague. You know that. These are just random coincidences.

It doesn’t mean the horoscopes actually come true. You should stop reading them.

Come on, let’s go to the party. You can’t seriously stay home because of some horoscope!"

"I’ll think about it," said Ellie. "I’ll call you tomorrow."

Hey, are you coming to the party tomorrow?"

Rooney asked. "I can swing by and pick you up if you want."

"No," Ellie responded, "I'm not going anywhere."

"Why's that?"

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predictive algorithms can amplify this effect by presenting general insights as personalized recommendations, increasing user engagement and sales. Research by Kruger et al. (2004) demonstrated that subjective validation plays a role in the perceived accuracy of product descriptions, influencing purchasing decisions.

About: Subjective validation, also known as the Forer effect, describes the cognitive bias where individuals perceive vague or general statements as personally meaningful and accurate when they align with their beliefs or desires. This bias highlights how people are inclined to find patterns and relevance in ambiguous information, especially when they believe it pertains to them directly. First identified in personality assessments and horoscopes, subjective validation is driven by a combination of cognitive heuristics and emotional factors, including a preference for confirmation and the illusion of control. Snyder and Larson (1972) found that subjective validation explains why people accept generalized personality descriptions as uniquely accurate, revealing vulnerabilities in critical thinking.

Reproducibility: The phenomenon of subjective validation has been consistently replicated in experimental studies. Forer’s (1949) classic experiment demonstrated that individuals rated vague personality assessments as highly accurate when they believed the statements were uniquely tailored to them. More recent research by Furnham and Schofield (2018) confirmed the robustness of this bias in personality assessments and its persistence across cultural contexts. Studies in digital marketing, such as by Michailova et al. (2021), have further validated the application of subjective validation in online consumer behavior, emphasizing its widespread influence in modern communication.

Trivia Example: The pervasive belief in astrology and fortunetelling offers a prime example of subjective validation. Statements like, “You are sometimes outgoing but also enjoy solitude,” resonate with a wide audience, as they are sufficiently ambiguous to match nearly everyone’s experiences. Despite lacking scientific support, these practices thrive due to subjective validation, making them psychologically persuasive.

Selected References

Forer, B. R. (1949). The fallacy of personal validation: A classroom demonstration of gullibility. Journal of Abnormal and Social Psychology, 44(1), 118–123.

Furnham, A., & Schofield, S. (2018). Individual differences in gullibility: A replication and extension. Personality and Individual Differences, 128, 23–27.

Kruger, J., Wirtz, D., & Miller, D. T. (2004). Subjective validation: Explaining how people come to accept false beliefs.

Journal of Personality and Social Psychology, 88(2), 319– 334.

Michailova, A., Mayr, E., & Huber, S. (2021). The role of subjective validation in digital marketing strategies. Journal of Interactive Marketing, 55, 14–27.

Snyder, M., & Larson, M. (1972). Subjective validation and personality inventories: When self-perception meets suggestion. Journal of Applied Psychology, 56(2), 143–151.

Business Example: Subjective validation is often exploited in marketing strategies.

For instance, advertisements using broad claims like “This product is perfect for those who value innovation and style” appeal to a wide range of consumers.

Similarly, tailored digital ads that employ 289

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SEMMELWEIS REFLEX The tendency to reject new evidence or new knowledge because it contradicts established norms, beliefs, or paradigms.

"Hey, Rooney, come in," Ellie welcomed Rooney into the hallway and closed the door, "come to the kitchen. I was just about to have breakfast. Want me to make you some eggs? Are you going to eat?"

"No, thanks, and you shouldn’t be having eggs every day for breakfast either.

You know, they're high in cholesterol."

"Rooney, where did you get such outdated ideas?

Recent studies have proven that eggs are practically the perfect food. They’re not only rich in protein but also help the body absorb more vitamins."

Rooney shook his head skeptically: "Why 'outdated'? I don't know about that.

Everyone has always told me since I was a kid that eggs are bad for you."

"Well, they told you wrong! Last time I’m asking – do you want some eggs?"

"No, thanks!" Rooney said, settling at the table, "but I wouldn’t say no to some coffee."

"You’d be better off cutting down on the coffee!"

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organizations can resist adopting new methodologies, such as remote work or AI- based tools, due to entrenched processes and cultural inertia, even when evidence suggests potential benefits.

About: The Semmelweis reflex refers to the human tendency to reject new information or ideas that contradict established norms or beliefs, often without proper consideration or evaluation. This cognitive bias is named after Ignaz Semmelweis, a 19th-century Hungarian physician who discovered the importance of handwashing in preventing infections. Despite clear evidence of its effectiveness, his findings were dismissed by the medical community of his time, as they conflicted with prevailing theories. The Semmelweis reflex highlights resistance to change and innovation, particularly when new evidence challenges long-held traditions or authority.

Reproducibility: The Semmelweis reflex has been consistently observed in studies of organizational change and innovation resistance. Research by Oreg (2003) identified psychological and cultural factors that contribute to resistance to change, including fear of uncertainty and loss of control. Experiments

by Kahneman and Tversky (1979) on status quo bias further demonstrate how individuals favor existing conditions over alternatives, even when evidence supports the latter. Case studies in healthcare, such as those by Greenhalgh et al.

(2004), show how the medical field often resists evidence-based practices due to professional norms and hierarchical structures. These findings collectively validate the robustness and prevalence of the Semmelweis reflex across domains.

Trivia Example: A historical example of the Semmelweis reflex is the initial rejection of germ theory by the medical community. Although Louis Pasteur and Joseph Lister later validated the theory, early proponents like Semmelweis faced widespread skepticism. His advocacy for hand hygiene was mocked, and his findings were ignored, delaying critical advancements in public health and medicine. This bias highlights the challenges of introducing paradigm-shifting ideas in any field.

Selected References

Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of innovations in service organizations: Systematic review and recommendations.

Milbank Quarterly, 82(4), 581–629.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Oreg, S. (2003). Resistance to change: Developing an individual differences measure. Journal of Applied Psychology, 88(4), 680–693.

Semmelweis, I. (1861). Die Aetiologie, der Begriff und die Prophylaxis des Kindbettfiebers. Hartleben.

Waring, J. J., & Bishop, S. (2010). Resistance and resilience in healthcare. Social Science & Medicine, 71(5), 728–735.

Business Example: The Semmelweis reflex often manifests as resistance to adopting disruptive technologies.

For instance, Kodak initially rejected the digital camera, a technology it had developed internally, fearing it would cannibalize its film business.

This hesitation allowed competitors to dominate the digital photography market, ultimately contributing to Kodak’s decline. Similarly, 291

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SELECTIVE PERCEPTION The tendency not to notice and more quickly forget stimuli that cause emotional discomfort and contradict our prior beliefs.

“Hey, Ellie, I'm surprised to see you here!"

Rooney beamed as Ellie walked into the robotics club’s demo day.

"I wasn't planning to initially, but your enthusiasm yesterday was pretty infectious!" Ellie admitted.

"So, what do you think? Impressed?"

"The projects are fantastic. But I'm curious, why was Linda’s project the main event? Lee’s seemed far more innovative."

Rooney chuckled. "Oh, you're just not seeing the bigger picture. Linda's been with us for three years; her ideas are always a step ahead."

Ellie frowned slightly. "I think you're not giving Lee enough credit. His robot was more complex, and he did the whole presentation on his own. Isn’t that obvious?"

"It's not about complexity, Ellie. Linda's project aligns more with our club's vision," Rooney argued, his tone suggesting an underlying bias.

Ellie, sensing the selective perception, pressed further. "But don’t you think you might be a bit biased? Maybe because you helped Linda? Lee’s project was technically superior, and it feels like you’re overlooking it because of your involvement with Linda’s work."

Rooney paused, taken aback. "I guess I never saw it that way. You think I’m favoring her project over Lee’s?"

"It seems like it. Sometimes we see what we want to see, right?" Ellie offered a gentle smile, encouraging Rooney to reconsider his viewpoint.

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study by Wedel and Pieters (2007) demonstrated how selective attention to branding elements, such as logos and colors, influences product recall and purchase decisions. This bias highlights the importance of consistent branding in maintaining consumer loyalty, as it filters out competing messages.

About: Selective perception refers to the cognitive bias in which individuals interpret information in a way that aligns with their pre-existing beliefs, preferences, or attitudes, while ignoring or minimizing contradictory evidence. This phenomenon is deeply tied to the brain’s tendency to filter overwhelming sensory data and prioritize information that aligns with personal experiences or expectations. Early studies by Hastorf and Cantril (1954) on sports fans demonstrated how selective perception influences even ostensibly neutral observers, as fans of opposing teams interpreted the same game events differently. This bias has profound implications in areas like politics, marketing, and interpersonal relationships, where subjective interpretations of the same information can lead to vastly divergent conclusions.

Reproducibility: Hastorf and Cantril’s (1954) foundational study on football games remains a cornerstone of this field, demonstrating how perception is influenced by team allegiance. More recent studies, such as those by Fazio et al. (2015), have explored the neural mechanisms underlying this bias, showing how confirmation bias and selective attention reinforce selective perception. Research in political psychology by Redlawsk (2002) has also replicated these findings, illustrating how voters process information in ways that align with their existing preferences. These studies confirm the robustness of selective perception across diverse contexts and populations.

Trivia Example: Selective perception is vividly illustrated in media consumption. During political debates, individuals often perceive their preferred candidate as the clear winner, regardless of objective performance metrics. This bias contributes to partisan divides, as audiences selectively focus on statements that reinforce their ideological stance while disregarding opposing viewpoints. The rise of echo chambers on social media platforms exacerbates this effect, as algorithms prioritize content that aligns with user preferences.

Selected References

Fazio, L. K., Dolan, P., & Marsh, E. J. (2015). Learning errors from fiction: Why we make errors about fictional stories.

Memory & Cognition, 43(5), 725– 737.

Hastorf, A. H., & Cantril, H. (1954). They saw a game: A case study.

Journal of Abnormal and Social Psychology, 49(1), 129– 134.

Redlawsk, D. P. (2002). Hot cognition or cool consideration?

Testing the effects of motivated reasoning on political decision making. Journal of Politics, 64(4), 1021–1044.

Wedel, M., & Pieters, R. (2007). Visual marketing: From attention to action. Lawrence Erlbaum Associates.

Westen, D., Blagov, P. S., Harenski, K., Kilts, C., & Hamann, S. (2006). Neural bases of motivated reasoning: An fMRI study of emotional constraints on partisan political judgment in the 2004 U.S. Presidential election. Journal of Cognitive Neuroscience, 18(11), 1947–1958.

Business Example: Selective perception plays a crucial role in shaping consumer behavior. For instance, brand loyalty can lead consumers to focus on positive reviews and advertisements for their preferred products while disregarding negative feedback. A 293

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STATUS QUO BIAS The preference to keep things the way they are rather than change.

"I had a big argument with my dad yesterday," Ellie said sadly. "What about?" asked Rooney.

"Well, he recently complained that we're using too much electricity and that we all need to start saving."

"I see, but what was the argument about?"

Rooney still didn’t grasp the core of the issue.

"So, I spent a few days researching and found out that if we switch our electricity provider, we could save over 30% on our bills. We're currently paying way too much."

"That sounds great, so you should change providers." "That’s what I thought, but my dad flat-out refused." "Why?" Rooney was genuinely surprised.

"He came up with all sorts of excuses – 'the other company might be worse,' 'we don’t know the real price per kilowatt,' 'their customer service is poor.' He just doesn’t want to change anything!"

"Don't be upset," Rooney patted Ellie on the shoulder. "It happens a lot. Many people dislike change, even when the benefits are clear."

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operations, as employees may resist change due to a preference for familiar routines, even if the proposed innovations could improve efficiency.

About: Status quo bias refers to the preference for maintaining one’s current state or decisions, even when alternative options may offer greater benefits. This cognitive bias is driven by loss aversion, cognitive inertia, and fear of uncertainty. Samuelson and Zeckhauser (1988) conducted foundational research on status quo bias, illustrating how individuals disproportionately favor default options over change. This phenomenon has significant implications in personal decision- making, public policy, and organizational behavior. It shows a tendency to avoid perceived risks associated with change, even when change might improve outcomes.

Reproducibility: Research on status quo bias has been widely replicated, establishing its robustness across domains. Samuelson and Zeckhauser (1988) provided empirical evidence in scenarios involving financial and health-related decisions.

More recent studies, such as by Kahneman et al.

(1991), explored the neural and psychological underpinnings of the bias, linking it to loss aversion and the endowment effect.

Experimental work by Dinner et al. (2011) demonstrated how default settings in decision environments exploit the bias to influence behavior, particularly in policy-making and consumer choices. These findings confirm the consistency and cross-cultural relevance of status quo bias in human cognition.

Trivia Example: A classic example of status quo bias can be seen in organ donation policies. In countries with optout systems, where organ donation is the default, participation rates are significantly higher compared to opt-in systems, where individuals must actively register. This stark contrast highlights how the default option can influence behavior by leveraging the bias toward maintaining the status quo.

Selected References

Dinner, I., Johnson, E. J., Goldstein, D. G., & Liu, K. (2011).

Partitioning default effects: Why people choose not to choose. Journal of Experimental Psychology: Applied, 17(4), 332–341.

Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1991). Anomalies: The endowment effect, loss aversion, and status quo bias.

Journal of Economic Perspectives, 5(1), 193–206.

Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of Risk and Uncertainty, 1(1), 7– 59.

Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Penguin Books.

Tversky, A., & Kahneman, D. (1991). Loss aversion in riskless choice: A reference-dependent model. Quarterly Journal of Economics, 106(4), 1039–1061.

Business Example: Status quo bias impacts consumer behavior and product adoption. For instance, users of subscription-based services like streaming platforms often stick with their existing plans even when better or cheaper options are available, simply because switching requires effort. Similarly, companies face challenges when introducing new technologies or restructuring

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ZERO-RISK BIAS Preference for reducing a small risk to zero over a greater reduction in a larger risk.

Ellie had been helping Rooney choose a new camera lens for an hour. After much deliberation, he settled on a 50mm Canon lens for portrait photography.

However, they faced a dilemma about where to buy it. One online store offered it for $559, while another listed it for $300.

"This is silly, we should get it from the website selling it for $300," Ellie argued.

"It's the same lens! Brand new and almost half the price! Think about it!"

"No!" Rooney countered, "We should buy the one for $559. Look, they offer a 30-day guarantee. It's risk-free. The other might be $300, but there's no guarantee at all."

"Why do you need a store guarantee when both lenses are the same and come with the manufacturer's warranty?" Ellie insisted on her point.

"Don't argue – I'm getting the one for $559. That's final!" Rooney declared and clicked the 'order' button.

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rather than optimizing overall safety and efficiency.

About: Zero-risk bias is a cognitive bias where individuals prefer options that completely eliminate risk in one area, even when other choices might reduce overall risk more effectively. This bias arises from a psychological need for certainty and the emotional comfort of perceived safety. Researchers like Slovic et al.

(1984) identified zero-risk bias in risk management scenarios, showing that people disproportionately favor eliminating small risks rather than addressing larger, more impactful ones. This bias is particularly relevant in fields such as public health, environmental policy, and financial decision-making, where trade-offs between competing risks are common.

Reproducibility: Slovic et al. (1984) demonstrated the bias in environmental risk assessments, where participants consistently preferred eliminating specific pollutants over reducing overall pollution levels. Kahneman and Tversky’s (1979) work on prospect theory provides additional support, as it highlights how individuals overvalue certainty. More recent research by Gigerenzer and Garcia-Retamero (2017) has explored the practical implications of zero-risk bias in health and safety decision-making, confirming its persistence across different cultural and decision- making contexts. These findings validate the replicability and significance of the bias in real-world scenarios.

Trivia Example: An illustrative example of zero-risk bias can be seen in food safety decisions. Consumers often prefer products labeled as “100% pesticide- free,” even if alternative methods, such as integrated pest management, could reduce overall health risks more effectively. The complete elimination of pesticides offers a psychological appeal, even though it may not address broader food safety concerns.

Selected References

Gigerenzer, G., & Garcia-Retamero, R. (2017). Cassandra’s regret: The psychology of not wanting to know. Psychological Review, 124(2), 179–196.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Slovic, P., Fischhoff, B., & Lichtenstein, S. (1984). Behavioral decision theory perspectives on risk and safety. Acta Psychologica, 56(1-3), 183–203.

Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Penguin Books.

Wakker, P. P., & Tversky, A. (1993). An axiomatization of cumulative prospect theory. Journal of Risk and Uncertainty, 7(2), 147–176.

Business Example: Zero-risk bias influences organizational decisionmaking, particularly in risk management. For instance, companies might invest heavily in eliminating a specific cybersecurity threat, such as phishing, while neglecting broader vulnerabilities in their IT infrastructure.

Similarly, financial institutions may focus on eliminating minor operational risks while overlooking systemic risks that could have more severe consequences. This bias can result in inefficient resource allocation, as efforts are concentrated on achieving zero risk in one area 297

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INFERENCES ARE KEY

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AMBIGUITY EFFECT The avoidance of options for which missing information makes the probability seem "unknown." handing her a cup of coffee.

"Many people prefer familiar surroundings and don't want to change their lives." "I'd choose Switzerland," Ellie stated confidently.

"I'm not so sure," Rooney replied, smiling.

"What do you mean?"

"Imagine this," he began, "suppose I offer you a game. You have two baskets with colored balls. Each basket has 10 balls. The first basket has 5 blue and 5 yellow balls. In the second, the number of blue and yellow balls is determined randomly. You win $20 if you pick a blue ball. Which basket would you choose – the first or the second?"

"The first, of course," Ellie said confidently.

"Why?" "Because in the first case, I know there are 5 blue balls out of 10. In the second, I don't know the exact number of blue balls."

"See! You also chose the option where the probability of winning is known. Although if we randomly determine the number of blue and yellow balls, it's very likely that the second basket would also have 5 blue balls. But most people prefer certainty. I'd also choose the first basket. That's what your brother did too; he chose the familiar over the uncertain."

"Interesting," Ellie mused, sipping her coffee. "I never thought about it like that…"

"I don't understand why my brother decided to stay in our town. He had a job offer in Switzerland," Ellie shrugged.

"What's so strange about that?" Rooney said, 300

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decisions, leading individuals to prefer familiar assets like government bonds over innovative investment vehicles.

About: The ambiguity effect describes the cognitive bias in which people tend to avoid options with unknown probabilities of outcomes, preferring choices with clear and defined risks. Introduced

by Ellsberg (1961), this bias demonstrates the human discomfort with uncertainty, particularly in decision-making scenarios where ambiguous options are perceived as riskier, despite potentially higher payoffs. The ambiguity effect plays a crucial role in areas such as finance, healthcare, and consumer behavior, as it often leads to suboptimal choices by undervaluing uncertain but potentially beneficial opportunities.

Reproducibility: The ambiguity effect has been consistently replicated in experimental and real-world contexts. Ellsberg’s (1961) seminal work, known as the Ellsberg paradox, remains foundational in demonstrating this bias. Subsequent studies by Camerer and Weber (1992) extended these findings, showing that ambiguity aversion persists across cultures and decision-making domains, including healthcare and policymaking. Additionally, Fox and Weber (2002) confirmed the robustness of this bias in consumer and financial decisions, linking it to psychological mechanisms like fear of the unknown. These studies collectively validate the ambiguity effect as a universal and persistent cognitive bias (e.g., Nobandegani et al., 2024).

Trivia Example: A classic example of the ambiguity effect is seen in gambling scenarios. Given the choice between a lottery where the odds of winning are explicitly stated (e.g., a 50% chance) and another where the odds are unknown, most people choose the former, even if the unknown odds could be more favorable. This preference illustrates how aversion to ambiguity can override rational calculations.

Selected References

Camerer, C., & Weber, M. (1992). Recent developments in modeling preferences: Uncertainty and ambiguity.

Journal of Risk and Uncertainty, 5(4), 325–370.

Ellsberg, D. (1961). Risk, ambiguity, and the Savage axioms.

Quarterly Journal of Economics, 75(4), 643–669.

Fox, C. R., & Tversky, A. (1995). Ambiguity aversion and comparative ignorance. Quarterly Journal of Economics, 110(3), 585–603.

Fox, C. R., & Weber, M. (2002). Ambiguity aversion: A neglected dimension of decision-making. Organizational Behavior and Human Decision Processes, 88(1), 292–324.

Heath, C., & Tversky, A. (1991). Preference and belief: Ambiguity and competence in choice under uncertainty. Journal of Risk and Uncertainty, 4(1), 5–28.

Nobandegani, A. S., Rish, I., & Shultz, T. (2024). Decision-making paradoxes in humans vs machines: The case of the allais and ellsberg paradoxes. In Proceedings of the annual meeting of the cognitive science society (Vol. 46).

Business Example: The ambiguity effect impacts investment decisions. Investors frequently favor established markets with predictable returns over emerging markets with unclear risks, even when the latter offer higher potential growth. Similarly, in marketing, consumers often choose products with transparent reviews or certifications over newer, less-documented alternatives. Research

by Fox and Tversky (1995) highlights how ambiguity aversion influences financial

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ALLAIS PARADOX: COMMON CONSEQUENCE EFFECT A change in a person's preference between two options when a third option is presented, which has an effect common to the original options. between ticket three and four. Ticket three gives you an 11% chance of winning one million or an 89% chance of nothing; ticket four offers a 10% chance of five million or a 90% chance of nothing. Which one would you pick?"

"Ticket four!" Ellie exclaimed.

"Right, but if you prefer ticket one over two, then logically, you should find ticket three more appealing than four. See why?"

"Not really. What does this have to do with the common consequence?"

"To understand, it's better to draw it out. When I first read about this paradox, I didn't get it either. A diagram helps." Rooney took a piece of paper and sketched two lottery tickets. Ticket 1: 89% chance of 1 million.

Ticket 2: 10% chance of 5 million, 89% chance of 1 million, 1% chance of getting nothing.

"See, these two options share a common outcome – one million with an 89% probability."

"Got it," Ellie said, and proceeded to draw the second pair herself. Ticket 3: 10% of 1 million, 89% of 0, and 1% of 1 million. Ticket 4: 10% of 5 million, 89% of 0, and 1% of 0 "So," Ellie continued, "ticket three is an 11% chance of a million or nothing, and ticket four is a 10% chance of five million or nothing."

"Exactly," Rooney smiled. "When we replace one common outcome (one million with an 89% chance) with another (zero with an 89% chance), your preferences between the two options sh57o9uldn't change, but for most people, they do. Choosing the first ticket should lead to choosing the third, but they choose the fourth. That's why it's a paradox."

"Hey, do you remember the common consequence effect paradox?" Ellie asked Rooney. "It sounds familiar, but I can't quite recall it." "I do. Why do you ask?"

"Just came across the term recently in my psychology class. Can you explain it?"

"Sure! Imagine I offer you two lottery tickets.

Ticket number one guarantees you a million dollars. Ticket number two gives you a 10% chance of winning five million, an 89% chance of one million, and a 1% chance of nothing. Which would you choose?"

"Ticket one, of course!" Ellie confidently replied.

"Most people would. Now, imagine a new choice 302

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gains, even when the expected value of stocks is higher. Marketers exploit this bias by emphasizing guaranteed benefits in promotions, such as cashback offers or no-risk trials, which align with consumers’ preference for certainty.

About: The Allais paradox, introduced by Maurice Allais in 1953, challenges the assumptions of expected utility theory by revealing inconsistencies in how people evaluate risky choices. The common consequence effect, a core feature of the paradox, describes how individuals violate the independence axiom by changing their preferences when equivalent outcomes are added to multiple options. This phenomenon demonstrates how people prioritize certainty over probabilistic gains, even when such preferences contradict rational decision-making models. The Allais paradox has profound implications for understanding human risk behavior and refining economic theories.

Reproducibility: Allais (1953) originally demonstrated the paradox using hypothetical scenarios, and subsequent studies, such as by Kahneman and Tversky (1979), confirmed its robustness across diverse contexts.

Cross-cultural experiments by Wu et al. (2011) further demonstrated the universality of the common consequence effect, highlighting its persistence even in populations with differing risk attitudes. More recent research has explored the neural basis of the paradox, with studies like those by Hsu et al. (2005) linking it to brain regions involved in emotion and decisionmaking. Yet, a meta-analysis by Blavatskyy et al.

(2022) found that the phenomenon was sensitive to experimental design.

Trivia Example: The paradox can be illustrated with a simple lottery example. When asked to choose between a guaranteed $1 million and an 89% chance of winning $1 million with an 11% chance of winning $5 million, most people opt for the certainty of $1 million. However, when equivalent probabilities are added to both options, the preference reverses, highlighting the inconsistency. This shift exemplifies the common consequence effect, as the addition of identical outcomes affects preference in ways expected utility theory cannot explain.

Selected References

Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’école Américaine. Econometrica, 21(4), 503–546.

Blavatskyy, P., Ortmann, A., & Panchenko, V. (2022). On the experimental robustness of the Allais paradox. American Economic Journal: Microeconomics, 14(1), 143-163.

Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., & Camerer, C. F. (2005).

Neural systems responding to degrees of uncertainty in human decision- making. Science, 310(5754), 1680–1683.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Quiggin, J. (1982). A theory of anticipated utility. Journal of Economic Behavior & Organization, 3(4), 323–343.

Wu, G., Zhang, J., & Gonzalez, R. (2011). Decision under risk.

Journal of Experimental Psychology: General, 140(2), 173– 193.

Business Example: The Allais paradox influences consumer decisions in marketing and finance. For example, a customer might prefer a guaranteed discount over a lottery with a higher potential discount.

Similarly, investors often prefer bonds with guaranteed returns over stocks with probabilistic 303

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ALLAIS PARADOX: COMMON RATIO EFFECT A change in preferences between two alternatives when the probabilities of outcomes are multiplied by a common factor, contradicting the expected utility hypothesis.

"And what is that?"

"It's a kind of paradox. Look: imagine you're given a choice between two options.

Option A where you get $30 with a 100% chance, and option B where you can win $40 with an 80% chance. What would you choose?"

"Option A, of course! I always tell you I hate lotteries."

"Wait, that's not the point here," Ellie continued, "Now, imagine I offer you a choice between option X and option Y. Option X is a lottery where you can win $30 with a 25% chance. Option Y is a lottery where you can win $40 with a 20% chance.

What would you choose?"

Rooney pondered: "Probably option Y." "See!" Ellie said triumphantly, "You made inconsistent choices. That's the paradox.

Option X results if you take option A and divide all probabilities by 4; option Y results if you divide all probabilities in option B by 4. If you think A is better than B, then…"

"I get it, if A is better than B, then X should be better than Y. Because X is equivalent to A, and Y is equivalent to B." "Exactly!"

"And I chose Y. Interesting... Can I read that book too?"

"What are you reading?" Rooney asked, peeking at the book lying on the living room table in front of Ellie, "Looks interesting…"

"My brother gave it to me to read," Ellie replied cheerfully, "Actually, it's a very interesting book! For instance, do you know what the common ratio effect is?"

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are identical. Similarly, investment firms often leverage this bias by presenting scaled probabilities in a manner that encourages clients to take higher risks, framing choices to appear more attractive when proportions are altered.

About: The common ratio effect, a key aspect of the Allais paradox, reveals how individuals’ preferences for risky choices violate the predictions of expected utility theory when the probabilities of outcomes are proportionally scaled down. This phenomenon highlights an inconsistency in decision-making: people may prefer a certain gain over a gamble but reverse their preference when both options are proportionally adjusted, despite the expected utility remaining unchanged. Maurice Allais first identified this paradox in 1953, and it has since become a cornerstone of behavioral economics and decision theory, challenging classical assumptions about rationality.

Reproducibility: The common ratio effect has been extensively validated in empirical studies. Allais (1953) initially demonstrated the paradox with thought experiments, and subsequent experiments by Kahneman and Tversky (1979) provided robust evidence through real-world decision-making scenarios. Gonzalez and Wu (1999) replicated the effect across diverse contexts, emphasizing its universality in human behavior. Neuroeconomic research by Hsu et al. (2005) further supported the phenomenon, linking preference reversals to emotional and cognitive processes in the brain.

These findings confirm the reproducibility and cross-disciplinary significance of the common ratio effect.

Trivia Example: A classic demonstration involves two choices: (A) a guaranteed $3,000 versus (B) an 80% chance of winning $4,000. Most people choose (A), reflecting risk aversion. However, when these probabilities are scaled down (e.g., a 25% chance of $3,000 versus a 20% chance of $4,000), many shift to preferring (B). This reversal exemplifies the common ratio effect, where proportional scaling alters preferences contrary to rational decision-making models.

Selected References

Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’école Américaine. Econometrica, 21(4), 503–546.

Gonzalez, R., & Wu, G. (1999). On the shape of the probability weighting function. Cognitive Psychology, 38(2), 129–166.

Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., & Camerer, C. F. (2005).

Neural systems responding to degrees of uncertainty in human decision- making. Science, 310(5754), 1680–1683.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Quiggin, J. (1982). A theory of anticipated utility. Journal of Economic Behavior & Organization, 3(4), 323–343.

Business Example: The common ratio effect influences how consumers evaluate discounts or rewards. For example, a 50% discount on a $10 product is perceived more favorably than a 25% discount on a $20 product, even though the absolute savings

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ELLSBERG PARADOX People's preference for known risks over unknown risks (ambiguity).

“No! I didn’t. But it’s weird—they’re obsessed with lottery tickets when the ball machines are clearly a better bet.”

“Ball machines?”

“Yeah, those colorful “bingo blower” machines where you bet on a color and win if it pops out. You can see the proportions—much easier to win.”

"But that is not strange because most people prefer to know the probability of winning.

Look, imagine I take a box and put in one red ball and two balls of unknown colors.

These two balls could both be blue, both yellow, or one blue and one yellow. Now, imagine I offer you $10 if you blindly pull out a red ball or $10 if you pull out a blue ball. Which color would you bet on?"

"Red. Because I know for sure there's one red ball," Ellie thought out loud.

"Alright," Rooney continued, "now imagine I offer you $10 if you pull out a red or yellow ball or $10 if you pull out a blue or yellow ball. Which colors would you bet on?"

"Blue and yellow, because I know there could be two blue or yellow balls."

"See!" Rooney said, "In both cases, you chose the option where you knew the probability of winning. But think about it: if you chose red in the first case, thinking the probability of pulling a red ball is higher than pulling a blue ball, then the probability of pulling a red or yellow ball should be higher than pulling a blue or yellow ball."

"So you're saying many people choose the lottery where they know the probability."

"Exactly!"

"Wow, I've never thought about it like that!"

“Hey, how was your trip? Did you enjoy it?”

Rooney asked.

“Terrible. There was no one to talk to. Everyone just sat in cafés buying lottery tickets.”

“Lottery tickets? Don’t tell me you bought some again.”

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choices: customers may favor established brands with clear reputations over newer brands with limited information, regardless of product quality.

About: The Ellsberg paradox, introduced by Daniel Ellsberg in 1961, challenges classical decisionmaking models by demonstrating ambiguity aversion—a preference for known risks over unknown probabilities. The paradox arises when individuals faced with two options, one with clear probabilities and another with ambiguous probabilities, consistently choose the former, even when rational utility models suggest indifference. This behavior contradicts the independence axiom of expected utility theory and shows how ambiguity can influence decision making. The Ellsberg paradox has profound implications for economics, psychology, and behavioral finance, as it reveals a fundamental human discomfort with uncertainty.

Reproducibility: The Ellsberg paradox has been consistently replicated and remains a cornerstone of behavioral decision theory. Ellsberg’s (1961) original experiments have been validated through numerous studies, including Camerer and Weber (1992), which demonstrated the universality of ambiguity aversion across cultures and decision-making contexts.

Neuroeconomic research by Hsu et al. (2005) identified specific brain regions, such as the amygdala and prefrontal cortex, associated with processing ambiguity, further substantiating the paradox’s psychological and neural underpinnings. These findings confirm the robustness and cross-disciplinary significance of the Ellsberg paradox (e.g., Kovářík et al., 2016).

Trivia Example: Ellsberg illustrated the paradox with the famous urn experiment. Participants were asked to choose between two urns for a chance to win money. Urn A contained 50 red and 50 black balls, while Urn B contained 100 balls in unknown proportions of red and black. Most participants preferred Urn A, reflecting ambiguity aversion, even though the probabilities of winning could theoretically be identical. This experiment highlights how uncertainty can drive human preferences, often at the expense of rationality.

Selected References

Camerer, C., & Weber, M. (1992). Recent developments in modeling preferences: Uncertainty and ambiguity.

Journal of Risk and Uncertainty, 5(4), 325–370.

Ellsberg, D. (1961). Risk, ambiguity, and the Savage axioms.

Quarterly Journal of Economics, 75(4), 643–669.

Fox, C. R., & Tversky, A. (1995). Ambiguity aversion and comparative ignorance. Quarterly Journal of Economics, 110(3), 585–603.

Heath, C., & Tversky, A. (1991). Preference and belief: Ambiguity and competence in choice under uncertainty. Journal of Risk and Uncertainty, 4(1), 5–28. https://doi.org/10.1007/BF00057884 Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., & Camerer, C. F. (2005).

Neural systems responding to degrees of uncertainty in human decision- making. Science, 310(5754), 1680–1683.

Kovářík, J., Levin, D., & Wang, T. (2016). Ellsberg paradox: Ambiguity and complexity aversions compared. Journal of Risk and Uncertainty, 52(1), 47-64.

Business Example: Ambiguity aversion, as demonstrated by the Ellsberg paradox, affects investment and market behavior. Investors often prefer assets with clear, transparent risk profiles, such as government bonds, over less familiar alternatives like cryptocurrencies or emerging market funds, even when potential returns are higher. Similarly, ambiguity aversion influences consumer 307

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ST PETERSBURG PARADOX A situation in which a naive decision theory, which takes only expected value into account, predicts a course of action that presumably no actual person would be willing to take. each time."

Intrigued, Ellie closed her book, pondering the scenario. "So, the prize money increases the longer it takes to get heads. Sounds promising."

"Exactly," Rooney said. "The paradox lies in determining how much one would pay to enter this game. Mathematically, the expected win is infinite. So in theory, one should be willing to pay a huge amount of money to play. But realistically, nobody does, people usually offer between 8 and 10 dollars to play the game."

"Why's that?" Ellie asked, genuinely intrigued, her book forgotten in her lap. "It's the clash between mathematical logic and human intuition," Rooney elaborated. "Our instincts tell us that the odds of winning big are low, despite the theoretically infinite winnings.” ”But why do they call it the St. Petersburg Paradox?"

Rooney replied knowledgeably, "It's named after the city where Daniel Bernoulli, who extensively analyzed the problem, lived and published his work. But actually, the paradox was invented by his cousin, Nicolas Bernoulli. Nicolas first stated it in a letter in 1713, and Daniel provided his analysis in 1738 in the publications of the Imperial Academy of Science of Saint Petersburg."

Ellie nodded thoughtfully. "It’s a cool paradox."

”Would you like a break from your physics revision?” asked Rooney. “Sure,” said Ellie.

“Have you heard about the St. Petersburg Paradox?"

Ellie, her eyes lifting from her physics textbook, shook her head with interest. "No, what's that about?"

Rooney, eager to share, began explaining.

"Imagine a game where a fair coin is tossed repeatedly until it lands heads up. If it comes up heads on the first toss, you win $2. If on the second, $4, and so on, doubling 308

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returns, favoring lower-risk options.

About: The St. Petersburg paradox, first described by Daniel Bernoulli in 1738, illustrates a fundamental issue in decision theory where classical expected value calculations fail to align with human intuition. The paradox arises in a hypothetical lottery game where a fair coin is tossed until it lands heads, with the payoff doubling for each toss. The expected value of this game is infinite, yet most people are only willing to pay a modest sum to play, demonstrating the disconnect between theoretical and practical valuation. Bernoulli resolved this paradox by introducing the concept of diminishing marginal utility, a foundational idea in modern economics.

Reproducibility: The paradox’s foundational insights have been widely validated and remain influential in behavioral economics and decision theory.

Bernoulli’s (1738) original formulation has been revisited in experiments, such as by Camerer and Ho (1994), which confirmed that diminishing marginal utility and psychological factors explain participants’ reluctance to pay high amounts for the game. More recent work by Rieger and Wang (2008) has explored cultural differences in risk attitudes, reinforcing the paradox’s universal applicability. These studies confirm that the St. Petersburg paradox consistently reveals the limitations of expected value theory in predicting real-world decisionmaking (e.g., Karadimas, 2025).

Trivia Example: Imagine a game where you pay an entry fee to participate in the coin toss lottery. While the mathematical expected value is infinite, most individuals would not pay more than a few dollars to play, as the likelihood of achieving a significant payoff decreases exponentially with each toss. This mismatch between theory and behavior highlights the practical implications of the paradox, particularly in understanding risk aversion.

Selected References

Bernoulli, D. (1738). Specimen theoriae novae de mensura sortis.

Commentarii Academiae Scientiarum Imperialis Petropolitanae, 5, 175–192. (Translated as “Exposition of a new theory on the measurement of risk,” Econometrica, 22(1), 23–36.)

Camerer, C., & Ho, T. H. (1994). Violations of the betweenness axiom and nonlinearity in probability. Journal of Risk and Uncertainty, 8(2), 167–196. https://doi.org/10.1007/BF01065371 Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Karadimas, P. (2025). St Petersburg paradox, personality and military decision-making. Constitutional Political Economy, 1-25.

Rieger, M. O., & Wang, M. (2008). What is behind the St. Petersburg paradox? A test of the utility theory. Journal of Risk and Uncertainty, 36(2), 145–163.

Thaler, R. H. (1985). Mental accounting and consumer choice.

Marketing Science, 4(3), 199–214.

Business Example: The St. Petersburg paradox is relevant in insurance and investment contexts.

Insurance companies leverage consumers’ risk aversion to offer policies with premiums exceeding the statistically fair price, banking on people’s unwillingness to face low-probability, high-impact risks. Similarly, in finance, the paradox explains why investors often avoid highvolatility assets with theoretically high expected

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VIOLATION OF TRANSITIVITY The inconsistency that occurs when one prefers A over B, B over C, but then, inconsistently, C over A. and an orange.

"And how do you play?" Ellie leaned in, intrigued.

"Here's how it works," Rooney explained. "I show Oliver the apple and banana and ask him to choose one. He picks the banana.

Then, I show him the banana and orange, and he chooses the orange. Finally, when I show him the orange and apple, logically he should choose the orange, but he picks the apple instead."

"What's so strange about that?" Ellie wondered.

Rooney looked puzzled. "Well, if you prefer a banana over an apple and an orange over a banana, you should choose the orange over the apple, right? But Oliver keeps choosing the apple."

"I get your point, but there's nothing odd here," Ellie responded. "You're assuming everyone's preferences are what behavioral scientists call “transitive”. But that's not always the case. Many people don't choose based on transitivity. You think if A is better than B, and B is better than C, then A must be better than C. But not everyone prioritizes that way."

Rooney paused, considering this. "I hadn't thought of that... You're right. Many people think differently. Maybe I should try different items with Oliver, like animals or shapes," he mused.

"Hey, what's in that box?" Ellie asked, curious.

"It's a game I made for Oliver," Rooney replied. "A game? Does he like it?" Ellie inquired.

"It's a logic game. Last time, though, Oliver didn't quite get the rules. Look." Rooney opened the box filled with rubber toys and took out three plastic fruits: an apple, a banana, 310

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Similarly, hiring managers may face this bias when comparing candidates in a group versus individually, leading to inconsistent evaluations.

About: The violation of transitivity refers to instances where individuals’ preferences do not follow the logical principle of transitivity. According to this principle, if someone prefers option A over B and B over C, they should also prefer A over C. However, behavioral studies, such as Tversky’s (1969) foundational research, demonstrate that individuals often exhibit inconsistent preferences, especially in complex or emotionally charged decisions. This paradox challenges classical economic models of rational choice, indicating that preferences are not always stable or consistent across contexts.

Reproducibility: The reproducibility of the violation of transitivity has been demonstrated across various domains (e.g., May et al., 2025). Tversky (1969) conducted experiments on multi-attribute decisionmaking, showing that individuals’ preferences depend on the context of comparison. Loomes and Sugden’s (1982) regret theory further explained how anticipation of regret can cause inconsistencies in preferences. Neuroeconomic studies, such as De Martino et al. (2006), identified the emotional underpinnings of these decisions, showing activity in the amygdala when people faced complex trade-offs. Zhang and Slovic (2017) extended these findings, emphasizing the role of context and framing in decision-making processes.

Trivia Example: Imagine someone choosing between cars. They prefer Car A (luxury features) over Car B (fuel efficiency), and Car B over Car C (affordability).

However, when comparing Car A and Car C directly, they opt for Car C due to its affordability.

This inconsistency illustrates a violation of transitivity, as preferences are shaped by the context and the specific trade-offs presented during the decision.

Selected References

De Martino, B., Kumaran, D., Seymour, B., & Dolan, R. J. (2006).

Frames, biases, and rational decision-making in the human brain. Science, 313(5787), 684–687.

Loomes, G., & Sugden, R. (1982). Regret theory: An alternative theory of rational choice under uncertainty. Economic Journal, 92(368), 805–824.

May, B., Palace, M., Milne, R., Dalton, G., Meenaghan, A., & Terbeck, S. (2025). Virtue, choice, and storytelling: how ethics, decision modalities and narrative framing influence decision inertia in a 360 degree extended reality environment. Cognition, Technology, Work.

Tversky, A. (1969). Intransitivity of preferences. Psychological Review, 76(1), 31–48.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453–458.

Zhang, J., & Slovic, P. (2017). Context effects in decision-making: A review of behavioral and neural models. Journal of Behavioral Decision Making, 30(5), 919–934.

Business Example: In marketing, companies exploit this bias by introducing “decoy” products. For example, a tech company might introduce a slightly inferior product to its flagship item, making the flagship appear more desirable in comparison. Research

by Loomes and Sugden (1982) in regret theory provides insight into how emotional factors like regret influence such preference reversals, helping marketers predict consumer behavior.

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VIOLATION OF INDEPENDENCE

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The principle that irrelevant alternatives should have no effect on the choice between preferred options "Hey Rooney, can you explain the independence axiom to me?" Ellie asked. "Of course, but why do you need it?" Rooney inquired.

"I need it for my psychology presentation," Ellie replied.

"The axiom states that if you have a specific preference between two options A and B (like preferring lottery A over lottery B), and if I modify both options in the same way (say, by adding a common element to both lotteries, or by multiplying or dividing the probabilities of winning in these lotteries by the same number), then your preferences should not change. In other words, if lottery A looked better to you than lottery B, then the modified lottery A should also look better than the modified lottery B. But many people change their preferences when such modifications are made; that is, often for them, the modified lottery B looks better than the modified lottery A, even though it should be the other way around."

"Got it, thanks!" Ellie said, understandingly.

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often nudges consumers toward the premium product. This tactic, referred to as the decoy effect, leverages consumers’ irrational preference shifts.

About: The violation of independence, also known as the independence axiom violation, occurs when individuals’ choices between two options are influenced by the introduction of a third, irrelevant option. Expected utility theory posits that preferences should remain consistent regardless of external changes, provided the new option does not directly affect the original alternatives. However, real-world decisionmaking often defies this principle, as preferences shift depending on context or framing. This phenomenon, extensively studied by Allais (1953) and Kahneman and Tversky (1979), reveals the complexity of human cognition and highlights the limitations of classical economic models.

Reproducibility: Allais (1953) first demonstrated this phenomenon as a part of the Allais paradox, through lottery-based experiments. Kahneman and Tversky (1979) expanded on these findings, illustrating violations in both financial and everyday decision-making contexts.

Contemporary studies, such as those by Birnbaum (2008), have further validated these insights, showing that independence violations persist across diverse populations and are influenced by emotional and cognitive biases.

Neuroeconomic research, including De Martino et al. (2006), identified brain activity associated with emotional processing during such preference shifts, supporting the psychological underpinnings of this phenomenon (e.g., Federico et al., 2020).

Trivia Example: A classic example involves a decision between two lotteries: (A) a guaranteed $500, and (B) a 50% chance of $1,000. Many people prefer (A).

However, when a third lottery (C) with a 75% chance of $500 and a 25% chance of $0 is introduced, individuals’ preferences often shift, violating the independence axiom. The added option reframes the perceived attractiveness of (A) and (B), even though their relative probabilities remain unchanged.

Selected References

Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’école Américaine. Econometrica, 21(4), 503–546.

Birnbaum, M. H. (2008). New paradoxes of risky decision making.

Psychological Review, 115(2), 463–501.

De Martino, B., Kumaran, D., Seymour, B., & Dolan, R. J. (2006).

Frames, biases, and rational decision-making in the human brain. Science, 313(5787), 684–687.

Federico, G., Morton, F. S., & Shapiro, C. (2020). Antitrust and innovation: Welcoming and protecting disruption. Innovation Policy and the Economy, 20(1), 125-190.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Simonson, I. (1989). Choice based on reasons: The case of attraction and compromise effects. Journal of Consumer Research, 16(2), 158–174.

Business Example: In marketing, companies exploit violations of independence by introducing a “decoy” product to influence consumer choices. For example, if a consumer is deciding between two smartphones—one with better features but a higher price, and another with fewer features at a lower price—introducing a third phone with poor features at a price close to the expensive option 313

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VIOLATION OF DOMINANCE

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Preference reversals between two options when a third option is presented.

"I just don't get how people can make irrational decisions," Rooney said in disbelief.

"As if you always make rational choices," Ellie retorted.

"Maybe. Sometimes. Like when I'm faced with a tough problem."

"I don't think it depends on the complexity of the problem," replied Ellie. "What do you mean?"

"Look!," Ellie said thoughtfully, "Suppose I offer you a very simple choice, but I'm not sure you'll pick the obviously rational answer."

"Try me!" Rooney smiled.

"Imagine I offer you a choice between $10 and $10.01. What would you choose?"

Rooney pondered: "I see," Rooney said after considering the situation, "10 dollars and one cent is more than 10 dollars. But despite this, many people would probably choose the 10 dollars. It's hard to find a use for one cent, and carrying around a coin is inconvenient.

In short, you're saying there are examples where people choose a clearly losing option, even when faced with a simple task?"

"Exactly!" Ellie nodded.

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former in both cost and returns—a choice driven by marketing rather than rational evaluation.

About: The violation of dominance occurs when individuals choose an option that is inferior in every respect to another available option, contradicting the principle of dominance in decision theory. According to this principle, if option A is better than option B in all attributes, A should always be preferred. However, realworld decision-making often deviates from this rational model due to psychological influences, framing effects, or cognitive overload. Early studies by Kahneman and Tversky (1979) highlighted such violations in risk-related decisions, revealing that human preferences are not always consistent or rational.

Reproducibility: The violation of dominance has been repeatedly validated in experimental and real-world settings. Kahneman and Tversky (1979) demonstrated the phenomenon through riskbased scenarios, while Hsee (1996) showed how evaluability affects decision-making, leading to dominance violations. Birnbaum (2008) expanded these findings by examining how context-dependent preferences drive such irrational choices. Neuroeconomic research by De Martino et al. (2006) further explained the emotional and neural basis of these violations, emphasizing the role of framing and affective processing. These studies highlight the robustness of dominance violations across contexts and populations (e.g., QuispeTorreblanca et al., 2025).

Trivia Example: Imagine a scenario where an individual is offered two health insurance plans. Plan A provides lower premiums and more comprehensive coverage, while Plan B has higher premiums and fewer benefits. Logically, Plan A dominates Plan B. Yet, if Plan B is marketed with emotionally compelling language or framed as a premium product, some individuals may still choose it, violating the dominance principle.

Selected References

Birnbaum, M. H. (2008). New paradoxes of risky decision making.

Psychological Review, 115(2), 463–501.

De Martino, B., Kumaran, D., Seymour, B., & Dolan, R. J. (2006).

Frames, biases, and rational decision-making in the human brain. Science, 313(5787), 684–687.

Hsee, C. K. (1996). The evaluability hypothesis: An explanation for preference reversals between joint and separate evaluations of alternatives. Organizational Behavior and Human Decision Processes, 67(3), 247–257.

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.

Quispe-Torreblanca, E., Stewart, N., & Birnbaum, M. H. (2025).

Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration. Judgment and Decision Making, 20, e4.

Simonson, I. (1989). Choice based on reasons: The case of attraction and compromise effects. Journal of Consumer Research, 16(2), 158–174.

Business Example: In marketing, companies often exploit violations of dominance by using psychological nudges. For example, a consumer might choose a subscription service with fewer features and a higher price because it is advertised as “premium” or “exclusive,” even when a better and cheaper option is available. Similarly, in investment decisions, retail investors may prefer actively managed funds over index funds despite evidence that the latter often outperform the

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ANTHROPOCENTRIC THINKING Considering human beings as the most significant entity of the universe and interpreting or regarding the world in terms of human values and experiences.

Why did you get plastic straws?" Ellie asked, casting a disapproving glance at Rooney.

"What's wrong with the straws?" Rooney looked puzzled, shrugging his shoulders as he set down a tray with two paper cups of drinks.

"How can you ask that?" Ellie's tone grew more stern. "They're plastic straws. Don't you know the harm plastic causes to our oceans? As responsible individuals, we should be aware that our actions impact the future of this planet. It's our mission to leave Earth in a better state for future generations than how we inherited it from our ancestors. Aren't you concerned about global warming?"

"Of course, I am!" Rooney replied. ”I did not realize it was that serious: I promise I won't use plastic straws again. I honestly didn't notice they were plastic and not paper."

"

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About: Anthropocentric thinking refers to the tendency to interpret and evaluate the world from a human-centered perspective, often projecting human attributes, motives, and emotions onto non-human entities or phenomena. This bias stems from the cognitive ease of understanding the world through the lens of personal human experience, which can lead to misconceptions about nature, animals, or even artificial intelligence. Anthropocentrism is prevalent in various domains, including environmental decision-making, ethical considerations, and technological development, shaping how humans relate to the world.

Reproducibility: Anthropocentric thinking is well-documented and replicable across experimental settings (e.g., Fortuna et al., 2024). Research by Epley et al.

(2007) demonstrated that individuals frequently anthropomorphize objects or phenomena when seeking to make sense of the unknown. Studies in environmental psychology, such as those by Tam et al. (2013), have shown how anthropocentric attitudes can hinder environmental conservation efforts, as people prioritize human needs over ecological balance.

Neuroimaging studies further reveal that anthropocentric interpretations engage brain regions associated with social cognition, including the medial prefrontal cortex, confirming the robust psychological basis for this bias.

Trivia Example: One well-known example of anthropocentric thinking is the attribution of human emotions to pets. Owners often interpret their dog’s wagging tail or cat’s purring as indicative of complex emotions like guilt or happiness, even though these behaviors may be instinctual responses rather than reflective of human-like emotional states. This bias can lead to overly simplistic or incorrect assumptions about animal behavior.

Selected References

Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864–886.

Fortuna, P., Wróblewski, Z., Gut, A., & Dutkowska, A. (2024). The relationship between anthropocentric beliefs and the moral status of a chimpanzee, humanoid robot, and cyborg person: the mediating role of the assignment of mind and soul. Current Psychology, 43(14), 12664-12679.

Guthrie, S. E. (1995). Faces in the clouds: A new theory of religion.

Oxford University Press.

Tam, K. P., Lee, S. L., & Chao, M. M. (2013). Saving Mr. Nature: Anthropomorphism enhances connectedness to and protection of nature. Journal of Experimental Social Psychology, 49(3), 497–501.

Waytz, A., Cacioppo, J. T., & Epley, N. (2010). Who sees human?

The stability and importance of individual differences in anthropomorphism. Perspectives on Psychological Science, 5(3), 219–232.

Zeller, T. (2010). The anthropocentric bias in environmental ethics. Ethics and the Environment, 15(2), 1–19.

Business Example: Anthropocentric thinking impacts technology design and marketing. Developers often create humanoid robots or AI interfaces with humanlike features to make them relatable, such as virtual assistants that mimic human speech patterns or facial expressions. However, these designs can foster unrealistic expectations about the capabilities of such systems. For instance, consumers may expect AI-powered chatbots to understand nuanced human emotions, leading to frustration when the systems fail to meet these expectations.

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ANTHROPOMORPHISM OR PERSONIFICATION The attribution of human traits, emotions, or intentions to non-human entities.

"It was such a cool idea to visit your uncle's farm," said Ellie.

"Yeah, I thought you'd be interested in seeing the ostriches he's raising, but it seems like you made friends with his cat," Rooney said with a smile, handing Ellie a cup of tea.

"The ostriches were cool, but the cat - he's just like a person! Did you see how he looked out the window and tapped on the glass with his paw? He was so happy to see us!"

"I remember!"

"And do you remember how he tried to drink the water from the aquarium to get to the fish but got tired, drank too much water, and fell asleep on his back? He's so adorable!"

"I get it, you didn't just like the cat; now he's your new best friend." "Exactly!" Ellie replied joyfully.

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systems, leading to dissatisfaction when they fail to meet those expectations.

About: Anthropomorphism, or personification, refers to the attribution of human traits, emotions, intentions, or characteristics to non-human entities such as animals, objects, or abstract concepts. Rooted in human psychology, this bias simplifies the interpretation of unfamiliar entities by relating them to familiar human experiences. Epley, Waytz, and Cacioppo (2007) theorized that anthropomorphism arises from a combination of the need for social connection, the presence of salient cues, and a tendency to project human-like reasoning.

While anthropomorphism can foster empathy and understanding, it can also lead to misconceptions, especially in interactions with technology or the natural world.

Reproducibility: The phenomenon of anthropomorphism is welldocumented across cultures and contexts (e.g., Damholdt et al., 2023). Research by Waytz et al.

(2010) demonstrated consistent patterns in attributing human characteristics to non- human agents, particularly under conditions of social isolation or ambiguity. Neuroimaging studies, such as those by Harris and Fiske (2006), revealed that anthropomorphism engages brain regions associated with social cognition, such as the medial prefrontal cortex. Recent studies have extended these findings to human interactions with AI and robots, confirming the robust and replicable nature of anthropomorphic tendencies in diverse populations.

Trivia Example: A famous example of anthropomorphism is the habit of naming hurricanes. Studies show that people may perceive hurricanes with human-like names as less threatening, potentially affecting evacuation behavior (Jung et al., 2014). Similarly, individuals often ascribe emotions like “anger” to malfunctioning machines, such as a car that won’t start or a computer that freezes.

References

Damholdt, M. F., Quick, O. S., Seibt, J., Vestergaard, C., & Hansen, M. (2023). A scoping review of HRI Research on ‘anthropomorphism’: contributions to the method debate in HRI. International Journal of Social Robotics, 15(7), 1203-1226.

Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864–886.

Harris, L. T., & Fiske, S. T. (2006). Dehumanizing the lowest of the low: Neuroimaging responses to extreme out-groups.

Psychological Science, 17(10), 847–853.

Jung, K., Shavitt, S., Viswanathan, M., & Hilbe, J. M. (2014).

Female hurricanes are deadlier than male hurricanes.

Proceedings of the National Academy of Sciences, 111(24), 8782–8787.

Tam, K. P., Lee, S. L., & Chao, M. M. (2013). Saving Mr. Nature: Anthropomorphism enhances connectedness to and protection of nature. Journal of Experimental Social Psychology, 49(3), 497–501.

Waytz, A., Cacioppo, J. T., & Epley, N. (2010). Who sees human?

The stability and importance of individual differences in anthropomorphism. Perspectives on Psychological Science, 5(3), 219–232.

Business Example: Anthropomorphism plays a significant role in branding and advertising. Mascots like the Michelin Man or the Geico Gecko are designed to create relatable, human-like personas for brands, increasing consumer trust and engagement. In technology, virtual assistants like Amazon’s Alexa or Apple’s Siri are imbued with human-like voices and conversational abilities to make interactions more intuitive.

However, anthropomorphism can backfire; users may develop unrealistic expectations of these 319

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FUNCTIONAL FIXEDNESS The tendency to see objects as only working in a particular way.

"How did your tennis tournament go?" asked Ellie. "Can I congratulate you?" "Yes, you can. I won the tournament," Rooney replied proudly.

"Well, tell me all about it!"

"What's there to tell? I already sent you the photos."

"What photos? - Rooney pulled out his smartphone. "You asked for a selfie, so I took one."

"That's a selfie?" Ellie exclaimed, looking at the photo. "I can only see a quarter of your face!"

"I don’t know how you take these selfies. I can take a photo with a regular camera anytime, but I'm no expert with a phone."

"It doesn’t take an expert. Look," Ellie said, taking his phone. "You turn on the camera, flip it to face you, and click. What's so hard about that?"

"Wait, you can flip the camera to face you? I was trying to get myself into the frame?"

"You mean to say you were trying to take a selfie with the camera facing away from you?

What, were you born yesterday?"

"I just don't know how to use phone cameras, I told you! I usually use real cameras."

"Even little kids know how to flip a phone camera to selfie mode." "Alright, alright, I get it – I'll know for next time!"

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highlight the role of functional fixedness in limiting adaptive strategies.

About: Functional fixedness is a cognitive bias that restricts individuals to perceiving an object solely in terms of its conventional function, thereby limiting creativity and problem-solving.

First studied by Duncker (1945), functional fixedness has become a cornerstone of research on cognitive constraints and innovation. It often emerges when people encounter challenges requiring them to think outside established norms or frameworks. By anchoring to predefined uses, individuals may fail to explore alternative or innovative solutions, particularly in high-stakes or resource-limited scenarios.

Reproducibility: Duncker’s (1945) early experiments remain foundational, but subsequent research has expanded its applicability (e.g., Kroneisen et al., 2021). German and Barrett (2005) demonstrated the bias in technologically sparse cultures, suggesting it is a universal limitation rather than a culturally specific phenomenon. Neuroimaging studies (e.g., Chrysikou et al., 2013) have identified neural patterns associated with fixedness, linking it to reduced activity in the prefrontal cortex during tasks requiring divergent thinking. Further, Wiley (1998) showed that functional fixedness can be exacerbated by expertise, as domain knowledge sometimes reinforces rigid thinking patterns, emphasizing the tension between expertise and creativity.

Trivia Example: Duncker’s “candle problem” is a quintessential illustration of functional fixedness. Participants are provided with a candle, a box of tacks, and matches and asked to fix the candle to the wall so it burns without dripping wax onto the table.

Most fail to consider using the box as a candle holder, instead perceiving it only as a container for tacks. Overcoming this fixed mindset enables creative problem-solving.

Selected References

Chrysikou, E. G., Motyka, K., Smith, S., & Thompson-Schill, S. L. (2013). Functional fixedness and creativity in problem solving. Cognitive Psychology, 66(3), 207–234.

Duncker, K. (1945). On problem-solving. Psychological Monographs, 58(5), 1–113.

German, T. P., & Barrett, H. C. (2005). Functional fixedness in a technologically sparse culture. Psychological Science, 16(1), 1–5.

Kroneisen, M., Kriechbaumer, M., Kamp, S. M., & Erdfelder, E. (2021). How can I use it? The role of functional fixedness in the survival-processing paradigm. Psychonomic Bulletin & Review, 28(1), 324-332.

Smith, S. M. (1995). Getting into and out of mental ruts: A theory of fixation, incubation, and insight. The Nature of Insight, 3(2), 229–251.

Wiley, J. (1998). Expertise as mental set: The effects of domain knowledge in creative problem-solving. Memory & Cognition, 26(4), 716–730.

Business Example: Functional fixedness frequently stymies innovation in industries like construction and resource management. For example, in disaster relief, traditional thinking might prevent responders from using available materials in unconventional ways, such as repurposing shipping containers into emergency shelters.

Similarly, in marketing, campaigns often fail to leverage unconventional media (e.g., guerilla marketing) due to reliance on standard channels like TV and online ads. These constraints 321

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DREAD AVERSION Preferring to avoid the feeling of dread by choosing options perceived as less feared even if they carry a greater risk.

Rooney's room, as always, was a paragon of cleanliness. On the bookshelf, neatly arranged books stood in tidy rows, accompanied by notebooks with colorful covers and boxes of various sizes.

"Wow, look what I found!" exclaimed Ellie, pulling a red envelope from the top shelf.

"Didn't you ever use my gift? I gave you this skydiving voucher last year!"

"I just never found the time at first, and then I completely forgot about it," Rooney pondered.

"Be honest - did it just scare you? Chickened out?"

"Not at all!" Rooney retorted, slightly irritated.

"Actually, if something goes wrong, it wouldn't exactly be a pleasant experience!"

"Just imagine!" Ellie said dreamily, "It must be so incredible. Jumping and having the whole city in the palm of your hand!"

"That's if everything goes right. But if there's some kind of unexpected problem, like the parachute not opening, then I doubt I’d enjoy the cityscape much."

"There you go, I told you - you got scared!" Ellie teased, clearly provoking him. "You're always talking about probabilities. Well, the likelihood of something going wrong during a skydive is very low. Plus, there'll be an instructor."

"I'm not scared of anything," Rooney declared firmly, snatching the red envelope from Ellie. "I'll go and jump tomorrow. End of discussion."

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terrifying (e.g., Ebola) more successfully than those for statistically more prevalent but less dreaded conditions, such as the seasonal flu.

About: Dread aversion refers to the heightened emotional response and avoidance behaviors triggered by events or risks perceived as catastrophic or uncontrollable. This bias causes individuals to disproportionately fear and avoid scenarios that evoke dread, even if the statistical likelihood of those events occurring is low.

Loewenstein et al. (2001) linked dread aversion to the emotional component of risk perception, suggesting that this bias often overrides rational evaluation. Commonly associated with risks involving nuclear power, terrorism, or pandemics, dread aversion shapes public attitudes, policy preferences, and personal decision-making.

Reproducibility: Slovic et al. (1987) identified the emotional dimensions of risk perception, emphasizing the role of dread in decision-making. Loewenstein et al. (2001) provided evidence for the neural basis of this bias, showing that dread responses engage the amygdala, a brain region associated with fear and emotional processing. More recent studies, such as those by Fischhoff et al. (2013), confirmed the impact of dread aversion on public health responses, including vaccine hesitancy and risk communication strategies during crises like COVID-19. These findings highlight the replicability of dread aversion across various contexts (e.g., Hedley et al., 2025).

Trivia Example: A vivid example of dread aversion is public fear of plane crashes. Although air travel is statistically one of the safest modes of transportation, many individuals dread flying due to the catastrophic nature of aviation accidents. This fear contrasts with their relative comfort with car travel, which statistically poses far greater risks but lacks the concentrated dread factor.

Selected References

Fischhoff, B., Wong-Parodi, G., Garfin, D. R., & Holman, E. A. (2013). Risk perception and communication during crises.

Annual Review of Public Health, 34, 167–183.

Hedley, F. E., Ngai, H. H. T., & Jin, J. (2025). Looking around in distress: Judgmental and attentional biases in multievidence decision making revealed in anxiety. Journal of Psychopathology and Clinical Science.

Loewenstein, G. F., Weber, E. U., Hsee, C. K., & Welch, N. (2001).

Risk as feelings. Psychological Bulletin, 127(2), 267–286.

Slovic, P., Fischhoff, B., & Lichtenstein, S. (1987). Perceived risk: Psychological factors and social implications. Science, 236(4799), 280–285.

Sunstein, C. R. (2003). Terrorism and probability neglect. Journal of Risk and Uncertainty, 26(2–3), 121–136.

Viscusi, W. K. (1993). The value of risks to life and health. Journal of Economic Literature, 31(4), 1912–1946.

Business Example: Dread aversion significantly influences industries like insurance and healthcare. For instance, individuals are more likely to purchase policies covering rare, catastrophic events (e.g., natural disasters) than common, less dramatic risks like car accidents or chronic illnesses.

Similarly, pharmaceutical companies often market vaccines against diseases perceived as

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EMPATHY GAP The tendency to underestimate the influence or strength of feelings, in either oneself or others.

"Hey!" Ellie sat down on the bench next to Rooney. "Why the long face?" "You see, I did something stupid. I hurt someone's feelings unnecessarily." "I understand. Who are we talking about?"

"Remember Yanzhen? I play tennis with her."

"Of course, I remember. What happened? How did you upset her?"

"Well, at yesterday’s practice, we were playing a team tennis match. We lost in the team score, and I don't know what got into me, but I ended up yelling at everyone. Not just at Yanzhen... at the others too... I felt so frustrated. The score was so close. I don’t know what came over me, what bug bit me?

I got so angry. I've never shouted like that at anyone before. Now I feel bad. What should I do?" Rooney hung his head.

Ellie smiled and said, "I think there's only one way out of such situations."

"What’s that?"

"The usual way. Just go and apologize! Everyone has tough days - you just need to own up to your mistakes."

"You're right. I'll apologize first thing tomorrow. I hope Yanzhen and the others aren't too upset with me."

"I'm sure everything will be fine," Ellie said, patting Rooney on the shoulder.

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workloads (Small & Loewenstein, 2005).

Similarly, brands that fail to account for customers’ emotional triggers often create marketing campaigns that feel disconnected from real consumer concerns, leading to poor engagement.

About: The empathy gap is a cognitive bias in which individuals struggle to accurately predict or understand emotional states, whether their own in a different context or those of others. Coined by Loewenstein (1996), this bias arises when people in a “cold” (neutral) state underestimate the influence of “hot” (emotional) states like anger, hunger, or stress, and vice versa. For example, when not in pain, one might underestimate how debilitating chronic pain can feel, leading to insufficient support or planning. This disconnect can distort decision-making, interpersonal interactions, and policy development, with implications for healthcare, addiction recovery, and workplace relations.

Reproducibility: The empathy gap has been extensively validated through experimental studies. Loewenstein (1996) demonstrated its role in visceral states like hunger and fatigue, while Nordgren et al. (2009) found similar patterns in health-related decisionmaking, such as addiction counseling.

Neuroimaging research by Wager et al. (2008) confirmed that this bias involves reduced engagement of brain areas linked to emotional understanding. These findings have been replicated across various cultural and situational contexts (e.g., Niven and López-Pérez, 2025).

Trivia Example: A common illustration of the empathy gap is the phenomenon of overconfidence during addiction recovery. Nordgren et al. (2009) demonstrated that individuals in a calm state consistently underestimated the intensity of future cravings, leading to ineffective relapse prevention strategies. Similarly, people often fail to recognize the impact of stress on decisionmaking until they experience it themselves, a problem prevalent in high-stakes professions like aviation or emergency medicine.

Selected References

Loewenstein, G. (1996). Out of control: Visceral influences on behavior. Organizational Behavior and Human Decision Processes, 65(3), 272–292.

Niven, K., & López-Pérez, B. (2025). Interpersonal emotion regulation: Reflecting on progress and charting the path forward. Emotion, 25(2), 277.

Nordgren, L. F., van der Pligt, J., & van Harreveld, F. (2009). The restraint bias: How the illusion of self-restraint promotes impulsive behavior. Psychological Science, 20(12), 1523– 1528.

Small, D. A., & Loewenstein, G. (2005). The devil you know: The effects of identifiability on punishment. Journal of Behavioral Decision Making, 18(5), 311–318.

Wager, T. D., Davidson, M. L., Hughes, B. L., Lindquist, M. A., & Ochsner, K. N. (2008). Prefrontal-subcortical pathways mediating successful emotion regulation. Neuron, 59(6), 1037–1050.

Business Example: In business contexts, the empathy gap can hinder effective leadership and marketing strategies.

For instance, managers operating under normal conditions may underestimate the stress and fatigue their employees experience during peak

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IMPACT BIAS Overestimating the length or the intensity of the impact of future feeling states.

"What are you looking at?" Ellie asked, glancing at the magazine Rooney was holding.

"Check this out, it’s amazing! This is a Canon 800mm f/5.6L IS USM lens. It's literally a dream! It costs about $13,000 and weighs more than 5 kilograms. One day, I'll definitely earn enough money to buy it for myself. Imagine how cool that would be," Rooney said, closing his eyes dreamily.

"Once I have it, I’ll never need anything else. I'll have the coolest lens in the world!"

"I highly doubt that," Ellie replied. "Remember when you wanted that Leica camera? You said the same thing back then – that getting a Leica would bring you “ultimate happiness”. It was exactly like now. You also said you'd never want anything else.

But then, of course, you wanted different lenses and more cameras. So, I think you won’t stop at just this. But really, the lens is indeed fantastic! Hope you'll save up for it soon."

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About: The impact bias refers to the tendency of individuals to overestimate the intensity and duration of their emotional reactions to future events. Coined by Gilbert et al. (1998), this bias manifests when people believe that a positive or negative event, such as receiving a promotion or experiencing a breakup, will have a more significant and lasting impact on their happiness than it actually does. The phenomenon arises from a failure to account for psychological resilience and the adaptive processes that help individuals recover emotionally over time. This bias is prevalent in various life domains, including career decisions, financial investments, and personal relationships, and highlights the limitations of human foresight in emotional predictions.

emotional appeals in advertising often overstate the enduring emotional benefits of their products, potentially leading to customer dissatisfaction when the predicted joy fades.

Trivia Example: One classic example of the impact bias is observed in lottery winners and paraplegics.

Research by Brickman et al. (1978) demonstrated that both groups returned to baseline levels of happiness over time, contradicting their initial expectations about the lasting emotional impact of their experiences. Similarly, students often overestimate the emotional toll of receiving lower grades, only to adapt and move on more quickly than anticipated.

Brickman, P., Coates, D., & Janoff-Bulman, R. (1978). Lottery winners and accident victims: Is happiness relative?

Journal of Personality and Social Psychology, 36(8), 917– 927.

Diener, E., Lucas, R. E., & Scollon, C. N. (2006). Beyond the hedonic treadmill: Revising the adaptation theory of wellbeing. American Psychologist, 61(4), 305–314.

Gilbert, D. T., Pinel, E. C., Wilson, T. D., Blumberg, S. J., & Wheatley, T. P. (1998). Immune neglect: A source of durability bias in affective forecasting. Journal of Personality and Social Psychology, 75(3), 617– 638.

Hoerger, M., Chapman, B., & Duberstein, P. (2023). Coping strategies and immune neglect in affective forecasting: Direct evidence and key moderators. Judgment and Decision Making, 18(2), 123–139.

Suh, E. M., Diener, E., Oishi, S., & Triandis, H. C. (1998). The shifting basis of life satisfaction judgments across cultures: Emotions versus norms. Journal of Personality and Social Psychology, 74(2), 482–493.

Wilson, T. D., & Gilbert, D. T. (2005). Affective forecasting: Knowing what to want. Current Directions in Psychological Science, 14(3), 131–134.

Reproducibility: Gilbert et al. (1998) found consistent overestimations of emotional responses to both positive and negative events. Further research by Wilson et al. (2000) emphasized the role of “immune neglect,” where individuals fail to account for their psychological defenses that dampen the impact of emotional experiences. A study by Diener et al. (2006) confirmed that this bias is replicable across diverse cultural contexts, reinforcing its robustness (e.g., Hoerger et al., 2023).

Selected References

Business Example: In business, the impact bias can lead to flawed decision- making. For example, employees may overestimate the satisfaction derived from achieving monetary rewards, only to find their happiness levels plateau shortly thereafter (Suh et al., 1998). Similarly, marketers exploiting 327

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INTEROCEPTIVE BIAS The tendency for one's internal physiological state to affect decision-making.

Rooney and Ellie had been walking through the spacious halls of the museum for several hours.

"What an amazing museum!" exclaimed Ellie.

"There must be a new exhibition. It's so great that you dragged me out of the house!

It's weird though... I remember we came here last year, and it was so boring. It seems like everything here has changed so much since then."

Rooney laughed: "You probably forgot. Almost everything is the same as last year, except for the Impressionist exhibition. Last time, you decided to wear those new high-heeled shoes right before we left, and you disliked everything: the weather was terrible, there were crowds of people, and you thought the museum was no good. That's why I'm really glad you're wearing sneakers today.

It's fantastic, and now you can enjoy the art without any discomfort."

"I'm sure you're exaggerating, but there might be some truth to it," Ellie pondered. "Clothes and shoes really do affect your mood. So, shall we go check out more sculptures?

Anyway, thanks! It's a great museum.

From now on, I'll only wear the most comfortable shoes here. I promise," she said with a laugh.

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About: The interoceptive bias refers to distortions in how individuals perceive and interpret internal bodily sensations, such as heartbeat, hunger, or physical pain. This bias affects emotional regulation, decision-making, and overall wellbeing.

Craig (2002) highlighted that interoception—our ability to sense the physiological state of the body—is crucial for emotional and cognitive processes. However, interoceptive bias occurs when these perceptions are either exaggerated or minimized, leading to flawed judgments. For example, individuals with anxiety may misinterpret normal bodily sensations, such as a slightly elevated heart rate, as signs of a serious health issue. This bias is linked to conditions like anxiety, depression, and eating disorders, emphasizing its relevance in both clinical and everyday contexts.

specific products, such as soft drinks, even when water would suffice.

Trivia Example: Interoceptive bias can explain why some individuals misinterpret mild dehydration as hunger. Studies by Herbert et al. (2012) revealed that poor interoceptive awareness often leads to inappropriate responses to bodily needs, such as overeating when thirsty or ignoring early signs of illness, like fatigue or fever.

Selected References

Reproducibility: Research consistently supports the existence and impact of interoceptive bias (e.g., Cui et al., 2025). Dunn et al. (2010) demonstrated that individuals with heightened interoceptive awareness made better decisions in emotionally charged scenarios, such as gambling tasks.

Conversely, studies by Khalsa et al. (2008) found that individuals with interoceptive deficits are more prone to anxiety and poor emotional regulation. Replication efforts, including crosscultural studies, have confirmed the robustness of these findings, indicating that while interoception varies across individuals, interoceptive bias is a replicable phenomenon that interacts with psychological and physiological states.

Craig, A. D. (2002). How do you feel? Interoception: The sense of the physiological condition of the body. Nature Reviews Neuroscience, 3(8), 655–666.

Critchley, H. D., Wiens, S., Rotshtein, P., Ohman, A., & Dolan, R. J. (2004). Neural systems supporting interoceptive awareness. Nature Neuroscience, 7(2), 189–195.

Cui, H., Wang, J., & Li, C. (2025). Interoceptive Dysfunction in Psychiatric Disorders and Non-invasive Neuromodulation for Improving Interoception: H. Cui et al.: Interoceptive Dysfunction in Psychiatric Disorders and Non-invasive Neuromodulation. Neuroscience Bulletin, 1-13.

Dunn, B. D., Galton, H. C., Morgan, R., Evans, D., Oliver, C., Meyer, M., … & Dalgleish, T. (2010). Listening to your heart: How interoception shapes emotion experience and intuitive decision making. Psychological Science, 21(12), 1835–1844.

Herbert, B. M., Muth, E. R., Pollatos, O., & Herbert, C. (2012).

Interoception across modalities: On the relationship between cardiac awareness and the sensitivity for gastric functions. PLOS ONE, 7(5), e36646.

Khalsa, S. S., Rudrauf, D., & Tranel, D. (2008). Interoceptive awareness declines with age. Psychophysiology, 45(5), 666–674

Business Example: In professional environments, interoceptive bias can influence decision-making. Executives under stress may misinterpret physiological signals, such as a racing heart, as fear rather than excitement, leading to overly cautious behavior during negotiations or presentations (Critchley et al., 2004). In marketing, companies exploit this bias by encouraging consumers to associate bodily sensations (e.g., thirst) with the need for .

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OPTIMISM BIAS The tendency to be over-optimistic about the outcome of planned actions.

Ellie but clearly didn't want to talk about it.

"It doesn't look like nothing!" Ellie exclaimed.

"You could've lost an eye!" Realizing he couldn't avoid the conversation, Rooney spoke up, shuffling his feet. "You see, I went to Nicole's party yesterday."

"A party at Nicole's? Seriously? She lives in one of the most dangerous neighborhoods in the city. It's really risky, especially at night."

"I thought about that and decided to go while it was still light. I figured everything would be fine if I stuck to the busy streets. What could go wrong? I don't bother anyone! But on the way, I ran into some aggressive guys.

They tried to steal my bike."

"I see. But they didn't get your bike, right? It's here with you," Ellie noted, glancing at the parked bicycle nearby.

"They couldn't, but I had to fight," Rooney smiled, scratching his bandaged arm and injured eye. "I hope you learned something from this? You won't be going back to that area again, right? It's like asking for trouble. Do you know the crime statistics there?"

"Why not? It's a fine neighborhood, you just have to be smart about it. Go there early, and it'll be okay. I just made a mistake this time – went too late. Otherwise, it's totally safe to go there."

"I'm amazed at your optimism! It seems like you don’t learn from your experiences," Ellie said, patting Rooney on the shoulder.

Ellie bumped into Rooney at the pharmacy's entrance.

"What happened to you?" she asked. "Did you get into a fight? Let me see – you've got a black eye and something's wrong with your arm.

Tell me what happened."

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optimism can result in financial losses and operational inefficiencies.

About: The optimism bias is a cognitive distortion where individuals overestimate the likelihood of positive events occurring to them and underestimate the likelihood of negative outcomes. First systematically explored by Weinstein (1980), this bias is pervasive across various contexts, from health and finance to relationships. For example, individuals may believe they are less likely to experience illness, job loss, or accidents compared to others. This bias is often driven by a combination of selfserving motivations and a failure to accurately weigh statistical probabilities. While optimism bias can promote resilience and motivation, it also leads to poor decision- making and insufficient preparation for risks.

Reproducibility: The optimism bias is supported by extensive empirical research (e.g., Lyu et al., 2025).

Weinstein (1980) conducted foundational experiments demonstrating its prevalence across different demographics and scenarios.

Sharot et al. (2007) provided neurological evidence, showing that the bias is associated with reduced activity in the anterior cingulate cortex when individuals process negative information. Cross-cultural studies (Chowdhury et al., 2014) have confirmed that while the bias is universal, its intensity varies by culture and context. These findings emphasize the importance of mitigating the effects of optimism bias through education and structured risk management strategies.

Trivia Example: A notable example of optimism bias is evident in personal health decisions. For instance, studies

by Sharot (2011) found that people consistently underestimate their risk of contracting illnesses such as influenza, often neglecting preventive measures like vaccination. Similarly, drivers often believe they are less likely than others to be involved in car accidents, contributing to risky driving behaviors.

Selected References

Buehler, R., Griffin, D., & Ross, M. (1994). Exploring the “planning fallacy”: Why people underestimate their task completion times. Journal of Personality and Social Psychology, 67(3), 366–381.

Chowdhury, R., Sharot, T., Wolfe, T., Düzel, E., & Dolan, R. J. (2014). Optimistic update bias increases in older age.

Psychological Medicine, 44(9), 2003–2012.

Lyu, D., Jia, F., & Gai, X. (2025). Optimism bias, judgment of severity, and behavioral change during two stages of the pandemics in China. Scientific Reports, 15(1), 176.

Sharot, T. (2011). The optimism bias. Current Biology, 21(23), R941–R945.

Sharot, T., Riccardi, A. M., Raio, C. M., & Phelps, E. A. (2007).

Neural mechanisms mediating optimism bias. Nature, 450(7166), 102–105.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323.

Weinstein, N. D. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39(5), 806–820.

Business Example: In the corporate world, optimism bias can skew project planning and investment strategies.

Buehler et al. (1994) demonstrated that managers frequently underestimate project timelines and costs, leading to the “planning fallacy.” This bias can also affect entrepreneurial ventures, as business founders overestimate their chances of success, despite high rates of failure in the industry (Tversky & Kahneman, 1992). While optimism can fuel innovation, unchecked 331

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PRO-INNOVATION BIAS The belief that an innovation should be adopted by whole society without the need of its alteration.

"We have some awesome news!" Ellie declared proudly. "Dad installed solar panels on our roof. Now, our house will be the most advanced in the whole neighborhood.

We're going to be at the forefront of energy conservation. We're promoting 'green' technology so all our neighbors will switch to energy-saving methods too." ”Your house is already the most advanced in the neighborhood," Rooney shrugged. "Your dad was one of the first to get a Tesla, your brother drives an electric car, and I think you were among the first to start collecting and recycling rainwater for irrigation. But none of your neighbors have switched to electric cars or started collecting rainwater like you. It's cool, of course. I'm really happy for you, but I doubt it will impress the neighbors enough to make them switch to new energy-saving technologies."

"You're wrong, these are the technologies of the future! Eventually, everyone will be using them," Ellie countered confidently.

"I hope so. But I doubt it will happen very quickly."

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software development, companies may favor innovative tools like artificial intelligence-based analytics without fully understanding the implications for data security or ethical considerations (Johnson et al., 2021).

About: The pro-innovation bias refers to the tendency to overvalue the benefits of an innovation while downplaying its limitations or risks. This bias often emerges during the development, promotion, or adoption phases of new technologies, products, or ideas. Rogers (2003) first popularized the concept in the context of diffusion of innovations, highlighting that while innovations often offer improvements, their full implications, including potential drawbacks, are frequently overlooked. This bias can lead to premature adoption of innovations without adequate evaluation of long-term consequences or alternative solutions.

Reproducibility: Research has consistently supported the existence of pro- innovation bias across different domains. Studies by Rogers (2003) demonstrate the tendency of early adopters to emphasize the benefits of new technologies while neglecting potential risks. More recently, Ferreira et al.

(2020) examined the adoption of genetic editing technologies, finding a consistent overestimation of benefits despite ethical and regulatory concerns. The reproducibility of this bias has been robust, with cross-industry studies highlighting its prevalence in technology, healthcare, and environmental domains. Future research aims to develop frameworks for mitigating this bias, particularly during the innovation adoption phase.

Trivia Example: A classic example of pro-innovation bias is the initial enthusiasm for asbestos in the early 20th century. Hailed as a revolutionary material due to its heat resistance and versatility, asbestos was widely adopted in construction and manufacturing. However, the significant health risks, including its role in causing mesothelioma, were underestimated and took decades to be fully acknowledged (Mossman et al., 1990).

Selected References

Ferreira, A., von Schönfeld, K. C., Tan, W., & Papa, E. (2020).

Maladaptive planning and the pro-innovation bias: considering the case of automated vehicles. Urban Science, 4(3), 41.

Johnson, R., & Kaplan, B. (2021). Ethical risks in AI adoption: A framework for evaluation. Technology in Society, 64, 101523.

Mossman, B. T., Gee, J. B., & Craighead, J. E. (1990). Asbestosrelated diseases. New England Journal of Medicine, 320(26), 1721–1730.

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

Zhang, R., Xue, R., & Liu, L. (2020). Blockchain challenges and opportunities: A systematic review. Future Generation Computer Systems, 107, 841– 853.

Business Example: In the corporate world, pro-innovation bias can skew strategic decisions. For instance, the adoption of blockchain technology was initially championed as a transformative tool for industries ranging from finance to supply chains.

However, its high energy consumption and scalability issues were often minimized in early assessments, leading to significant challenges in implementation (Zhang et al., 2020). Similarly, in

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REACTANCE The urge to do the opposite of what someone wants you to do out of a need to resist a perceived attempt to constrain your freedom of choice.

"Good day," the camera store clerk greeted Rooney and Ellie with a radiant smile. "How can I help you today?"

Rooney handed him a camera bag. "I'd like to pay for this bag," he said.

"Of course. Do you have our loyalty card?"

"Yes, here it is," Rooney handed over his card, which the clerk scanned.

"Oh, I see you're a regular customer," the clerk remarked, then suddenly started a sales pitch. "I notice you're interested in Leicas.

We have a wide range of Leica cameras and accessories. Let me show them to you." He hurried to a display at the opposite wall.

"Can I help you with anything?"

"No, thank you," Rooney replied, visibly annoyed, taking Ellie's hand. "We'd better go."

"Wait! What about your bag?"

"I'll think about it," Rooney answered, leaving the store.

Once outside, Ellie asked, "What happened? You needed that bag!"

“I can't stand it when they tell me what I need," Rooney replied, still irked. "I'll just buy it online later. Let's go!"

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overt pressure, reduces reactance and enhances customer engagement.

About: Reactance is a psychological phenomenon wherein individuals experience a motivational pushback when they perceive their freedom of choice is being restricted or threatened. Coined

by Brehm (1966) in his theory of psychological reactance, this response manifests as resistance to persuasion, defiance, or the adoption of behaviors contrary to the imposed restrictions.

Reactance is often triggered in contexts where rules, advice, or restrictions are perceived as overly controlling, leading individuals to restore their autonomy by rejecting or opposing the directive.

Reproducibility: Experiments by Silvia (2006) showed that individuals are more likely to reject advice or recommendations perceived as controlling, even when they align with their interests. Further, Rains (2013) highlighted reactance in health communication, noting its consistent impact across demographic groups. Although cultural variations exist (e.g., De Las Cuevas and de Leon, 2024), with individualistic societies exhibiting stronger reactance (Kim et al., 2019), the phenomenon has been successfully replicated across several domains.

Trivia Example: A common example of reactance is observed during public health campaigns. When antismoking ads employ fear-based messaging, they often provoke reactance, especially among younger audiences. Rather than reducing smoking rates, these campaigns can lead to the reinforcement of smoking behaviors as individuals assert their autonomy against perceived control (Rains, 2013).

Selected References

Brehm, J. W. (1966). A theory of psychological reactance.

Academic Press.

De Las Cuevas, C., & de Leon, J. (2024). Implications of psychological reactance for clinical practice in psychiatry including a systematic review. Motivation Science.

Fransen, M. L., Smit, E. G., & Verlegh, P. W. J. (2015). Strategies and motives for resistance to persuasion: An integrative framework. Frontiers in Psychology, 6, 1201.

Kim, S., Peng, S., & Choi, S. M. (2019). Cultural differences in the effect of reactance on health communication. Journal of Health Communication, 24(6), 594–602.

Rains, S. A. (2013). The nature of psychological reactance revisited: A meta- analytic review. Human Communication Research, 39(1), 47–73.

Silvia, P. J. (2006). Reactance and the dynamics of disagreement: Multiple paths from threatened freedom to resistance to persuasion. European Journal of Social Psychology, 36(5), 673–685.

Business Example: In marketing, reactance can undermine product recommendations perceived as overly forceful.

For instance, aggressive pop-up ads urging customers to “Act Now!” can provoke reactance, deterring consumers from purchasing products (Fransen et al., 2015). Conversely, subtle framing of options, such as presenting choices without

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SALIENCE BIAS The tendency to focus on the most noticeable (salient) features of a person or concept.

"Listen, have you finished picking out clothes?

I've been waiting for you for two hours," Rooney said, clearly irritated.

"Oh, Rooney, hi," Ellie greeted him. "Weren't we supposed to meet at the café?" "Yes, but that was almost two hours ago," Rooney replied, discontented. "I shouldn't have to wait this long. Can we speed it up a bit?"

"Wait, how did you even find me? I didn’t say which part of the store I'd be in."

"That was actually easy! There's a big red dragon in front of this display. I knew you wouldn't pass by it. Plus, these are the brightest Tshirts in the store. I knew they’d catch your eye. Everywhere else in the store has very subdued colors. This is the only spot bursting with vibrant hues! I figured this was the first place to look for you."

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About: Salience bias refers to the tendency to focus disproportionately on information or elements that stand out while neglecting less conspicuous yet equally or more relevant factors. This cognitive bias is grounded in the human brain’s preference for stimuli that are visually, emotionally, or conceptually prominent (Taylor & Thompson, 1982). While salience can be advantageous in drawing attention to critical issues, it often leads to misjudgments by prioritizing eye-catching information over a balanced assessment. For example, dramatic news events, such as plane crashes, receive significant attention, despite air travel being statistically safer than driving.

Reproducibility: Research on salience bias is robust and replicable (e.g., Djerf-Pierre et al., 2025). Taylor and Thompson’s (1982) studies demonstrated its widespread influence in decision-making, with follow-up studies confirming its role across diverse contexts, including finance, healthcare, and politics. For instance, Krosnick et al. (1990) found that salient information about political candidates, such as scandals, often outweighs their policy positions in voters’ evaluations.

Similarly, salience bias in financial markets has been evidenced in traders’ disproportionate focus on highly visible data, such as headlinegrabbing earnings reports, often neglecting broader economic indicators (Barberis et al., 1998).

Trivia Example: A clear example of salience bias is how consumers often overestimate the dangers of shark attacks after viewing sensationalized media coverage, despite their rarity. This heightened perception of risk persists even though more common causes of harm, like car accidents, pose a far greater threat (Slovic et al., 2004).

Selected References

Barberis, N., Shleifer, A., & Vishny, R. W. (1998). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343.

Djerf-Pierre, M., Shehata, A., & Johansson, B. (2025). Media salience shifts and the public’s perceptions about reality: How fluctuations in news media attention influence the strength of citizens’ sociotropic beliefs. Mass Communication and Society, 28(3), 459-484.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.

Krosnick, J. A., & Kinder, D. R. (1990). Altering the foundations of support for the president through priming. American Political Science Review, 84(2), 497–512.

Slovic, P., Fischhoff, B., & Lichtenstein, S. (2004). Facts and fears: Understanding perceived risk. In Readings in Risk, 137– 152. Earthscan Publications.

Taylor, S. E., & Thompson, S. C. (1982). Stalking the elusive vividness effect. Psychological Review, 89(2), 155–181.

Business Example: In marketing, salience bias plays a crucial role.

Brands often highlight visually or emotionally salient features to capture consumer attention.

For instance, luxury car advertisements frequently showcase high-end features like leather interiors or advanced technology, diverting attention from practical aspects such as fuel efficiency or maintenance costs (Kahneman, 2011). This strategic emphasis influences purchasing decisions by shaping consumers’ perceptions of value.

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SECTION II SOCIAL

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PART 5 SOCIAL

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INTERACTION EFFECTS

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AUTHORITY BIAS The tendency to attribute greater accuracy to the opinion of an authority figure (unrelated to its content) and be more influenced by that opinion.

"Hey, want to catch a movie this weekend?" Ellie asked. "There's this new one with George Clooney. My brother saw it yesterday and really liked it."

"No, I'm not interested," Rooney replied bluntly.

"Why not?"

"I read a review by this blogger, @RKfilms, and they completely trashed it. Trust me, it's not worth it!"

"But it has an 86% rating on Rotten Tomatoes!"

Ellie countered.

"Even if it had 100%! If @RKfilms says the movie's rubbish, then it must be!"

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healthcare, patients frequently over-rely on their doctors’ authority, sometimes at the expense of exploring alternative or complementary treatments (Epstein and Street, 2011).

About: Authority bias refers to the tendency to attribute more weight and credibility to the opinions or actions of authority figures, often leading to uncritical acceptance of their directives. This bias is deeply rooted in social hierarchies and evolutionary psychology, where deference to authority could enhance survival and cohesion within groups (Milgram, 1963). However, in modern contexts, this predisposition often overrides rational evaluation, influencing decisions in domains such as medicine, education, finance, and workplace dynamics.

Authority bias can result in both positive and negative outcomes: while it fosters trust and efficiency in hierarchical systems, it may also lead to poor decision-making when individuals defer to authority without independent scrutiny.

Reproducibility: The prevalence of authority bias has been consistently demonstrated in behavioral science research (e.g., Li et al., 2025). Milgram’s (1963) seminal study has been replicated across decades and cultural contexts, confirming the universal influence of perceived authority. Subsequent studies, such as Burger (2009), showed similar levels of compliance, even with updated ethical standards. In medical contexts, research by Frosch et al. (2012) highlights patients’ reluctance to challenge physicians’ recommendations, even when the advice may not align with their preferences. Cross-cultural research by Bond and Smith (1996) suggests that authority bias is particularly pronounced in collectivist cultures, where deference to hierarchical structures is socially reinforced. These findings emphasize the global relevance and persistence of authority bias across varied domains and scenarios.

Trivia Example: The classic Milgram experiment vividly illustrates authority bias. Participants were instructed by a figure of authority—a researcher in a lab coat—to administer what they believed were electric shocks to another person. Despite clear signs of distress from the supposed recipient, most participants continued to obey the instructions, demonstrating the profound influence of perceived authority on moral reasoning (Milgram, 1963). Variations of this experiment have consistently replicated similar findings, underscoring the robustness of the phenomenon (Burger, 2009).

Selected References

Bond, R., & Smith, P. B. (1996). Culture and conformity: A metaanalysis of studies using Asch’s (1952b, 1956) line judgment task. Psychological Bulletin, 119(1), 111–137.

Burger, J. M. (2009). Replicating Milgram: Would people still obey today? American Psychologist, 64(1), 1–11.

Epstein, R. M., & Street, R. L. (2011). The values and value of patient-centered care. Annals of Family Medicine, 9(2), 100–103.

Frosch, D. L., May, S. G., Rendle, K. A. S., Tietbohl, C., & Elwyn, G. (2012). Authoritarian physicians and patients’ fear of being labeled “difficult.” Health Affairs, 31(5), 1030–1038.

Li, Y., Guo, X., Gao, J., Chen, G., Zhao, X., Zhang, J., ... & Wei, X. (2025, July). LLMs Trust Humans More, That’sa Problem!

Unveiling and Mitigating the Authority Bias in RetrievalAugmented Generation. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 28844-28858).

Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology, 67(4), 371–378.

Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.

Business Example: In the corporate world, authority bias can stifle innovation and critical thinking. For instance, employees may defer to senior executives’ opinions during meetings, even when they possess more accurate or innovative ideas. The 2008 financial crisis exemplifies this bias at scale, as many financial institutions adhered unquestioningly to the risky strategies endorsed by influential CEOs, exacerbating systemic failures (Thaler and Sunstein, 2008). In 345

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ACTOR-OBSERVER BIAS The tendency of people to attribute their own actions to external causes while attributing other people's behaviors to internal causes.

"Rooney, why are you so upset?" Ellie patted Rooney on the shoulder. "So your team didn't win Team of the Year award, what's the big deal? You'll get it next year! There's going to be a new robotics competition, and you'll be even better prepared."

"We were perfectly prepared this time! It's just bad luck, that's why it's so frustrating."

"Look, TEAM-A didn't win any prizes either, but they aren't upset about it."

"Yeah, but their projects were way worse than ours. They're genuinely weak. That's fair."

"Right, of course," said Ellie sarcastically. "TEAMA is a weak team, so it's their fault. And you're strong, but just unlucky!"

"Exactly," Rooney said, but then, looking up at Ellie, he burst out laughing along with her.

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parties make an effort to understand each other’s perspectives. Training programs on attribution biases often emphasize the importance of perspective-taking to mitigate these effects and enhance workplace harmony (Ross, 1977).

About: The actor-observer bias describes a cognitive asymmetry in how people explain behavior.

When individuals evaluate their actions, they often attribute them to external, situational factors. Conversely, when judging others’ actions, they are more likely to ascribe them to internal, dispositional traits. This discrepancy arises from differing perspectives: actors are more aware of the situational constraints influencing their actions, while observers lack access to this context and focus on the individual.

Rooted in Heider’s (1958) foundational attribution theory, the actor- observer bias has significant implications for interpersonal relationships, conflict resolution, and leadership dynamics. This bias is particularly pronounced in negative situations, where it serves to protect one’s self-concept while maintaining critical perspectives toward others.

Reproducibility: The seminal work of Jones and Nisbett (1971) provided the foundation, and subsequent studies have expanded on their findings across diverse cultural and contextual settings (e.g., Fiedler et al., 1995). Malle (2006) conducted a meta-analysis demonstrating the reliability of the bias across scenarios involving negative outcomes.

However, the strength of the bias varies depending on cultural background: collectivist cultures, which emphasize situational and relational explanations, display a reduced actorobserver bias compared to individualistic cultures (Choi et al., 1999). Furthermore, close relationships, such as those with friends or family, often attenuate the bias because actors and observers are more likely to share situational awareness (Regan and Totten, 1975).

Trivia Example: A relatable example of the actor-observer bias occurs in traffic situations. Drivers often justify their own speeding by citing urgent circumstances, such as running late for an appointment. However, when observing another driver speeding, they are more likely to interpret it as reckless behavior or lack of concern for safety. This everyday scenario highlights how differently individuals evaluate similar actions depending on their role (Jones and Nisbett, 1971).

Selected References

Choi, I., Nisbett, R. E., & Norenzayan, A. (1999). Causal attribution across cultures: Variation and universality. Psychological Bulletin, 125(1), 47–63.

Fiedler, K., Semin, G. R., Finkenauer, C., & Berkel, I. (1995). Actorobserver bias in close relationships: The role of selfknowledge and self-related language. Personality and Social Psychology Bulletin, 21(5), 525-538.

Heider, F. (1958). The psychology of interpersonal relations.

Wiley.

Jones, E. E., & Nisbett, R. E. (1971). The actor and the observer: Divergent perceptions of the causes of behavior. In E. E. Jones et al. (Eds.), Attribution: Perceiving the causes of behavior (pp. 79–94). General Learning Press.

Malle, B. F. (2006). The actor-observer asymmetry in attribution: A (surprising) meta-analysis. Psychological Bulletin, 132(6), 895–919.

Regan, D. T., & Totten, J. (1975). Empathy and attribution: Turning observers into actors. Journal of Personality and Social Psychology, 32(5), 850– 856.

Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 10, pp. 173–220). Academic Press.

Business Example: In organizational settings, the actor-observer bias frequently manifests in performance evaluations and workplace interactions. For instance, a team leader might attribute an employee’s missed deadlines to poor time management or lack of commitment, while the employee may explain it as a result of unrealistic expectations or resource constraints. These divergent attributions can lead to misunderstandings and conflicts unless both 347

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CHEERLEADER EFFECT The tendency for people to appear more attractive in a group than in isolation.

"What are you digging around on the computer for?" Rooney asked. He had been waiting for about forty minutes for Ellie to get ready to go to the gym with him for their workout.

"Are you going to be much longer? You still need to pack your gym bag."

"I'm just looking for a photo for my online profile, but I can't find anything suitable. You see, I need a profile photo for an online exhibition of my work. But I don't like any of them," Ellie continued scrolling through photos on her computer. "They're all either blurry or look too much like passport photos."

"Can't you upload the photo later?" Rooney wondered.

"No, it has to be on the profile by 4 pm today.

Those are the exhibition's rules." "I see. But can you change it later?"

"Yes, but I still need to upload something now."

"I get the problem," Rooney said. "You can't find anything suitable where you're alone.

What about photos where you're with other people? Like with your friends?"

"That's it!" Ellie found a photo where she was with her brother and two school friends, Lara and Mel. "I really like this photo; I look natural here."

"Well then, use that photo for now, and I'll take a new one for you tonight that doesn't look 'like a passport photo'. Deal?"

Ellie nodded in response.

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perceived positivity and attractiveness of the group to influence consumer behavior. In workplace environments, this bias may impact hiring decisions during panel interviews, where candidates presented as part of a cohesive group may be evaluated more favorably than those assessed individually.

About: The cheerleader effect refers to the phenomenon where individuals appear more attractive when seen in a group compared to when viewed alone.

First formally studied by Walker and Vul (2014), the effect is attributed to perceptual and cognitive biases. Group presentation leads to the averaging of facial features, which enhances perceived attractiveness, as individual imperfections become less noticeable. This cognitive process stems from how humans process visual information, with a preference for composite or averaged representations. The cheerleader effect has implications for social dynamics, marketing, and the psychology of attraction.

Reproducibility: Walker and Vul (2014) demonstrated the effect using controlled image manipulations, showing that participants consistently rated individuals in groups as more attractive than when the same individuals were viewed alone. Subsequent research has replicated these findings across different contexts (van Osch et al., 2015).

However, variability exists depending on group size and composition, as overly large groups may dilute individual distinctiveness. The effect is highly context-dependent (e.g., Messner et al., 2021).

Trivia Example: The cheerleader effect can be observed in popular media and social gatherings. For example, characters in ensemble casts of TV shows often appear more appealing collectively than individually. Similarly, people in group photos on social media tend to receive more positive feedback compared to solo images. This effect emphasizes the influence of group context on individual perceptions (Walker and Vul, 2014).

Selected References

Messner, C., Carnelli, M., & Höhener, P. S. (2021). Change in evaluation mode can cause a cheerleader effect. Frontiers in Psychology, 12, 607448. van Osch, Y., & Hospers, M. (2015). Averaging attractiveness: How perceived group attractiveness influences individual attractiveness ratings. Social Psychological and Personality Science, 6(4), 411–417.

Walker, D., & Vul, E. (2014). Hierarchical encoding makes individuals in a group seem more attractive.

Psychological Science, 25(1), 230–235.

Zajonc, R. B. (1968). Attitudinal effects of mere exposure. Journal of Personality and Social Psychology, 9(2), 1–27.

Business Example: Marketers frequently use the cheerleader effect to enhance the appeal of products or people. For instance, advertisements often depict groups of happy individuals using a product, leveraging the

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DEFENSIVE ATTRIBUTION HYPOTHESIS Attributing more blame to a harm-doer as the outcome becomes more severe or as personal or situational similarity to the harm-doer decreases.

It was a beautiful sunny Saturday morning. Ellie and Rooney were rollerblading through the park, chatting and joking around.

"How about skating backwards?" Rooney challenged, turning to face Ellie, his back to the path ahead. Barely five meters in, Ellie shouted, grabbing his hand: "Watch out!"

Rooney braked just in time. Looking ahead, he saw a 12-year-old boy on a scooter who had swerved onto the main alley and miraculously stopped inches from him.

"Are you blind? Can't you see where you're going?" Rooney yelled. "I could've crashed into you! You need to watch your speed!"

The boy, wordless, picked up his scooter and disappeared into the park.

"Did you see that?" Rooney asked Ellie. "Does he have a death wish or something?"

"Actually, you're also to blame," Ellie pointed out.

"How's that?"

"You were the one skating backwards and not seeing anything. And you scolded the kid! Maybe you should skate like everyone else – facing forward and watching where you're going!"

"Okay," Rooney conceded thoughtfully, "you're right. I shouldn't have yelled at him. My fault."

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for improving workplace communication and fostering a culture of accountability without blame.

About: The Defensive attribution hypothesis explains a cognitive bias where individuals attribute blame or responsibility for negative outcomes in a way that preserves their own sense of security or control. Shaver (1970) introduced this concept, positing that people judge situations based on their perceived similarity to the victim. When observers feel psychologically distant from the victim, they tend to blame the victim to create a sense of immunity to similar risks. In contrast, when the observer identifies closely with the victim, they are more likely to attribute the outcome to external factors, as this protects their belief in a just and manageable world.

Reproducibility: Research on defensive attribution demonstrates consistent patterns across various scenarios.

Shaver (1970) showed how judgments of responsibility shift based on similarity and outcome severity. Further studies in legal and organizational contexts have replicated these findings, reinforcing the hypothesis’s validity (Lerner and Miller, 1978; Walster, 1966).

However, cultural factors play a significant role.

Collectivist cultures emphasize situational attributions, while individualist societies lean toward dispositional explanations (Choi et al., 1999). These findings suggest that while robust, defensive attribution is shaped by cultural and contextual nuances (e.g., Billett and Qian, 2008).

Trivia Example: This phenomenon often surfaces in reactions to crime reports. For example, a person hearing about a burglary might attribute blame to the victim for leaving their doors unlocked if they consider themselves cautious in locking doors.

Conversely, someone living in a similar neighborhood might focus on the lack of police presence to distance themselves from the inevitability of the crime.

Selected References

Billett, M. T., & Qian, Y. (2008). Are overconfident CEOs born or made? Evidence of self-attribution bias from frequent acquirers. Management Science, 54(6), 1037-1051.

Choi, I., Nisbett, R. E., & Norenzayan, A. (1999). Causal attribution across cultures: Variation and universality. Psychological Bulletin, 125(1), 47–63.

Lerner, M. J., & Miller, D. T. (1978). Just world research and the attribution process: Looking back and ahead.

Psychological Bulletin, 85(5), 1030– 1051.

Shaver, K. G. (1970). Defensive attribution: Effects of severity and relevance on the responsibility assigned for an accident.

Journal of Personality and Social Psychology, 14(2), 101– 113.

Walster, E. (1966). Assignment of responsibility for an accident.

Journal of Personality and Social Psychology, 3(1), 73–79.

Business Example: In organizational settings, the defensive attribution hypothesis can manifest during workplace accidents. Employees distant from the role of an injured worker may attribute the mishap to negligence, while those in similar roles might blame inadequate safety measures or management. Understanding this bias is crucial

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EGOCENTRIC BIAS Recalling the past in a self-serving manner, e.g., remembering one's exam grades as being better than they were, or a caught fish as bigger than it really was.

"Can you believe it? I got knocked out early in the tennis tournament today, and guess by whom? Jacob! He barely knows how to play.

He can hardly hold a racket," Rooney said, clearly frustrated.

"You're wrong," Ellie countered. "Jacob has really improved over the last year! I saw him training last month when I came to pick you up, and he was playing incredibly well."

"I thought you were rooting for me!"

"Of course, I'm your biggest supporter. You're my best friend. But let's face reality! You need to train more. You've been neglecting your tennis practice lately!"

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About: Egocentric bias refers to the tendency to overemphasize one’s own role, perspective, or contributions in various situations while underestimating the roles or perspectives of others. This cognitive bias stems from the innate difficulty humans face in decentering from their own experiences. Pronin et al. (2007) argue that egocentric bias is a fundamental aspect of human cognition, leading to skewed perceptions in collaborative work, interpersonal conflicts, and memory. This bias often results in overestimating personal input or the degree to which one’s thoughts and feelings are shared by others.

Reproducibility: Research on egocentric bias has shown consistent findings across disciplines (e.g., O’Connor et al., 2024). Ross and Sicoly (1979) demonstrated that individuals routinely overestimate their own contributions in shared tasks. Moreover, Epley et al. (2004) found that egocentric tendencies persist even when participants are explicitly asked to consider others’ perspectives. While cultural factors influence the expression of egocentric bias, it remains a universal phenomenon. Western cultures, which emphasize individualism, might exhibit stronger egocentric tendencies compared to collectivist societies, where group harmony is prioritized (Heine et al., 1999).

Trivia Example: A common example of egocentric bias is evident in group projects. Most individuals tend to believe they contributed more effort than their peers, irrespective of the actual distribution of tasks. For instance, in a college group assignment, multiple members might independently claim they did the majority of the work.

Selected References

Epley, N., Keysar, B., Van Boven, L., & Gilovich, T. (2004).

Perspective taking as egocentric anchoring and adjustment. Journal of Personality and Social Psychology, 87(3), 327–339.

Heine, S. J., Kitayama, S., & Lehman, D. R. (1999). Cultural differences in self- enhancement: Evidence from Japan and Canada. Journal of Personality and Social Psychology, 72(6), 1268–1283.

O'Connor, R. J., Lucas, A. P., & Riggs, K. J. (2024). Rethinking egocentric bias: A computer mouse-tracking study of adult belief processing. Journal of Experimental Psychology: General, 153(2), 307.

Pronin, E., Gilovich, T., & Ross, L. (2007). Objectivity in the eye of the beholder: Divergent perceptions of bias in self versus others. Psychological Review, 111(3), 781–799.

Ross, M., & Sicoly, F. (1979). Egocentric biases in availability and attribution. Journal of Personality and Social Psychology, 37(3), 322–336.

Tomasello, M., Carpenter, M., Call, J., Behne, T., & Moll, H. (2005).

Understanding and sharing intentions: The origins of cultural cognition. Behavioral and Brain Sciences, 28(5), 675–691.

Business Example: Egocentric bias can manifest in workplace dynamics, particularly during performance reviews. Employees might overestimate their individual contributions to team successes while underappreciating their colleagues’ input, leading to potential conflict. Managers may also inadvertently downplay the influence of their subordinates’ efforts on achieving organizational goals. Recognizing this bias is critical for fostering fairness and collaboration in team environments (Tomasello et al., 2005).

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EXTRINSIC INCENTIVES BIAS An exception to the fundamental attribution error, where people view others as having been influenced by extrinsic incentives (e.g., a high salary), while viewing themselves as having intrinsic reasons (e.g., doing something for the personal gratification).

"Did you enjoy the exhibition?" Rooney asked.

"I'm still digesting it all. It's hard to say," replied Ellie thoughtfully.

"I think it was a brilliant idea to create statues from plastic, to draw attention to ocean pollution. That sculptor, Jack Iris, did a great job, in my opinion."

"I'm not sure. It all seemed a bit insincere to me.

He never had any environmental pieces before. It feels like he's just jumping on the bandwagon because it's trendy now."

"I didn't really see any hype about it. And at the exhibition opening, Jack spoke about conservation with such conviction. I didn't sense any dishonesty." "You might be right.

I need to think about it more," Ellie said.

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opportunities for professional growth.

Misjudging employee motivations can lead to ineffective management strategies and poor organizational outcomes.

About: Extrinsic incentives bias refers to the tendency to overemphasize the role of external rewards, such as money or recognition, in motivating others while underestimating the impact of intrinsic motivators, such as personal satisfaction, curiosity, or a sense of purpose. This bias stems from the misalignment in how people perceive their own motivations versus those of others.

Kruger et al. (2005) demonstrated that individuals often assume others are primarily driven by extrinsic factors, whereas they themselves are influenced by intrinsic motivations. This disconnect can lead to flawed assumptions about how to inspire or manage others effectively in various contexts.

Reproducibility: Empirical research supports the existence of extrinsic incentives bias. Kruger et al. (2004) conducted experiments showing that participants underestimated the importance of intrinsic motivations in others’ decision-making processes. Additionally, Gagné and Deci (2005) emphasized the significance of intrinsic motivators in self-determination theory, finding that extrinsic motivators often undermine intrinsic ones when poorly implemented.

However, cross-cultural differences highlight variability in the strength and expression of this bias, with collectivist societies placing greater emphasis on intrinsic communal goals compared to individualistic cultures.

Trivia Example: An illustrative example of this bias is seen in educational settings. Teachers or policymakers may believe students are motivated solely by grades or rewards, ignoring the intrinsic joy of learning. This perspective can result in policies that emphasize performance metrics at the expense of fostering creativity or critical thinking.

Selected References

Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and selfdetermination in human behavior. Springer Science & Business Media.

Gagné, M., & Deci, E. L. (2005). Self-determination theory and work motivation. Journal of Organizational Behavior, 26(4), 331–362.

Kruger, J., Wirtz, D., Van Boven, L., & Altermatt, T. W. (2004). The effort heuristic. Journal of Experimental Social Psychology, 40(1), 91–98.

Pink, D. H. (2011). Drive: The surprising truth about what motivates us.Riverhead Books.

Wrzesniewski, A., McCauley, C., Rozin, P., & Schwartz, B. (1997).

Jobs, careers, and callings: People’s relations to their work. Journal of Research in Personality, 31(1), 21–33.

Business Example: In the workplace, managers frequently overestimate the effectiveness of monetary rewards as motivators while neglecting the importance of recognition, autonomy, and purpose (Gagné and Deci, 2005). For instance, a company might increase salaries or bonuses to improve employee satisfaction but fail to address deeper motivators, such as meaningful work or

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FALSE CONSENSUS EFFECT The tendency to overestimate how much other people agree with us.

"Hey, since we're out fishing, do you want to drive to the next village for some pickles?"

Rooney asked.

"I can't stand pickles!" Ellie responded, wrinkling her nose. "Why go all the way there for them? You can buy pickles in any store!"

"Really? You don't eat pickles? That's surprising; I thought everyone liked them," Rooney said, astonished. "And besides, you can't find these kind of pickles in stores. Are you sure you don't want to change your mind? It could be a fun adventure. We could even rent a boat!"

"I'm absolutely certain! I'm not going anywhere for pickles!"

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is not accurately gauged, leading to reputational and financial losses (Marks and Miller, 1987).

About: The false consensus effect is a pervasive cognitive bias where individuals overestimate the degree to which their opinions, beliefs, and behaviors are shared by others. Identified by Ross, Greene, and House (1977), this bias arises from egocentric reasoning and a lack of exposure to alternative perspectives. It is reinforced by the human tendency to associate with like-minded individuals, creating echo chambers that amplify the belief that personal views are universal. This phenomenon impacts interpersonal communication, group dynamics, and decisionmaking processes, often leading to overconfidence and poor judgment in both personal and professional settings.

Reproducibility: The false consensus effect has been extensively studied and replicated across diverse scenarios (e.g., Choi et al., 2024). Ross et al. (1977) demonstrated its impact in social judgments, while Marks and Miller (1987) conducted a comprehensive review of studies affirming its prevalence. Mullen et al. (1985) conducted a metaanalysis showing that the bias is amplified when individuals assess ambiguous or subjective topics, as they tend to generalize from personal experiences. Cross-cultural research has revealed interesting variations, with collectivist societies displaying a reduced tendency toward false consensus due to heightened awareness of group norms (Watson, 1982).

Trivia Example: A common instance of the false consensus effect occurs in environmental attitudes. For example, a person who prioritizes recycling might assume that others share the same commitment, despite statistical evidence indicating varying levels of participation in sustainable practices. This overestimation can lead to frustration or confusion when others do not meet these expectations, further perpetuating the bias.

Selected References

Choi, J., Hong, Y., & Kim, B. (2024). People will agree what I think: Investigating LLM's False Consensus Effect. arXiv preprint arXiv:2407.12007.

Marks, G., & Miller, N. (1987). Ten years of research on the falseconsensus effect: An empirical and theoretical review.

Psychological Bulletin, 102(1), 72–90.

Mullen, B., Atkins, J. L., Champion, D. S., Edwards, C., Hardy, D., & Story, J. E. (1985). The false consensus effect: A metaanalysis of 115 hypothesis tests. Journal of Experimental Social Psychology, 21(3), 262–283.

Ross, L., Greene, D., & House, P. (1977). The “false consensus effect”: An egocentric bias in social perception and attribution processes. Journal of Experimental Social Psychology, 13(3), 279–301.

Svenson, O. (1981). Are we all less risky and more skillful than our fellow drivers? Acta Psychologica, 47(2), 143–148.

Watson, D. (1982). The actor and the observer: How are their perceptions of causality divergent? Psychological Bulletin, 92(3), 682–700.

Business Example: In corporate settings, the false consensus effect often influences managerial decisions. A leader implementing a new policy might overestimate employee support, assuming their team shares their enthusiasm without seeking feedback. This misjudgment can result in resistance, reduced morale, and project failures. For instance, a tech company rolling out a controversial software update might face backlash if customer feedback 357

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FUNDAMENTAL ATTRIBUTION ERROR

.

The tendency for people to over-emphasize personality-based explanations for behaviors observed in others while under- emphasizing the role and power of situational influences "Hey, Rooney, sorry for calling so late," Ellie said, "Did I wake you?" "No, I wasn't asleep.

What's up?"

"Do you have any balloons at home?"

"Yeah, I do."

"Can I borrow some?"

"Sure, but why do you need them?"

"Well, my brother just got back, and his wife is arriving tomorrow for her birthday. He planned to decorate the house with balloons, but I used all of ours for a theater production. Now he's freaking out, spent two hours ranting about his balloons. It's a nightmare. He just lost it over some balloons!"

"Well, why call him a psycho right away? Didn't he just fly in from Cambodia? That's a long flight; he must be exhausted. Maybe that's why he's in a bad mood."

"So, about the balloons? I could come over and pick them up now, and I’ll buy new ones tomorrow when the shops open to replace them. His wife arrives at 5 a.m., and all the shops will still be closed."

"Okay, I get it. But I'll come over to your place; it's too late for you to be running around. I'll just need a coffee in return!"

"Deal!"

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About: The fundamental attribution error (FAE) is a widespread cognitive bias where individuals overemphasize personal traits and underestimate situational factors when interpreting others’ behavior (Ross, 1977). This tendency stems from a preference for attributing actions to stable, internal characteristics rather than transient, external conditions. For example, if a colleague fails to meet a deadline, one might assume they are disorganized rather than considering they might be overwhelmed by external circumstances such as family emergencies or unclear project goals. This bias significantly impacts interpersonal relationships, decisionmaking, and organizational dynamics, often leading to unfair judgments or stereotyping (Gilbert and Malone, 1995).

incorrect performance reviews.

Trivia Example: In a groundbreaking study by Jones and Harris (1967), participants were presented with essays supporting or opposing Fidel Castro. Even when informed that the stance was assigned rather than chosen, participants attributed the writers’ views to their personal beliefs. This highlighted how individuals often neglect external constraints when interpreting others’ behaviors, a hallmark of FAE.

Selected References

Reproducibility: FAE is one of the most studied and validated psychological biases, demonstrating robust reproducibility across diverse contexts (e.g., Luong and Butler, 2023). A notable study by Storms (1973) illustrated that changing perspectives—such as reviewing an interaction on video—can reduce FAE, as individuals become more attuned to situational factors.

Furthermore, cross-cultural research by Choi et al. (1999) found that individualistic societies, like the United States, exhibit stronger FAE compared to collectivist cultures, such as Japan, where situational influences are more frequently acknowledged. These findings stress the bias’s prevalence and its susceptibility to situational and cultural moderation.

Choi, I., Nisbett, R. E., & Norenzayan, A. (1999). Causal attribution across cultures: Variation and universality. Psychological Bulletin, 125(1), 47–63.

Gilbert, D. T., & Malone, P. S. (1995). The correspondence bias.

Psychological Bulletin, 117(1), 21–38.

Harvey, P., Madison, K., Martinko, M. J., Crook, T. R., & Crook, T. A. (2014). Attribution theory in the organizational sciences: A case of unrealized potential. Journal of Organizational Behavior, 35(4), 441–452.

Jones, E. E., & Harris, V. A. (1967). The attribution of attitudes.

Journal of Experimental Social Psychology, 3(1), 1–24.

Luong, R., & Butler, K. (2023). Informal psychology education and the fundamental attribution error: Testing the effectiveness of accessible online passages. Current Psychology, 42(16), 14012-14024.

Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology (Vol. 10, pp. 173–220). Academic Press.

Storms, M. D. (1973). Videotape and the attribution process: Reversing actors’ and observers’ points of view. Journal of Personality and Social Psychology, 27(2), 165–175.

Business Example: In the workplace, FAE frequently influences employee appraisals. For instance, a manager might label an employee as “incompetent” for missing a presentation deadline while failing to account for external factors such as last-minute assignment changes or resource limitations (Harvey et al., 2014). This misjudgment can lead to strained relationships, lower morale, and 359

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FALSE UNIQUENESS BIAS The tendency of people to see their projects and themselves as more singular than they actually are.

"Why are we dragging ourselves to this yoga class?" Ellie grumbled. "I bet the class will be empty at 8 AM on a Sunday! I doubt there are any other sports fans crazy enough to torture themselves like this."

"On the contrary, Ellie," Rooney hefted her sports bag onto his shoulder, "I barely managed to get us a spot. The 6 AM and 7 AM classes are always packed, and this one had a threemonth waiting list. So, no complaining, let's hurry up before we're late!"

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About: The false uniqueness bias is a cognitive distortion where individuals overestimate the rarity of their positive traits or behaviors compared to others (Goethals et al., 1991). This bias leads people to believe that their abilities, values, or opinions are unique, fostering an inflated sense of selfperception. For instance, an employee might believe their innovative ideas are exceptionally rare within their organization, even if others possess similar qualities. This bias contrasts with the false consensus effect, where people overestimate the extent to which others share their views or behaviors. False uniqueness bias often stems from a need to maintain self-esteem and differentiate oneself from peers (Suls et al., 1988).

positioning products as exclusive, prompting consumers to purchase goods to affirm their distinctiveness.

Trivia Example: In a study by Suls et al. (1988), participants assessed their abilities in various domains, such as generosity and intelligence, relative to others.

Findings revealed that participants systematically undervalued the prevalence of positive traits in others, demonstrating the pervasive nature of the false uniqueness bias.

Selected References

Reproducibility: An eralyexperiment by Alicke et al. (1985) demonstrated the bias in participants’ overestimation of their moral behaviors compared to their peers. Subsequent research, such as Van Boven et al. (2003), found crosscultural variations, with individualistic societies exhibiting stronger tendencies toward false uniqueness than collectivist cultures, where social harmony often tempers individual selfenhancement. The bias has also been replicated in business settings (e.g., Aguinis and Gabriel, 2022) Aguinis, H., & Gabriel, K. P. (2022). International business studies: Are we really so uniquely complex?. Journal of International Business Studies, 53(9), 2023-2036.

Alicke, M. D., & Govorun, O. (2005). The better-than-average effect. In M. D. Alicke, D. A. Dunning, & J. Krueger (Eds.), The self in social judgment (pp. 85–106). Psychology Press.

Goethals, G. R., Messick, D. M., & Allison, S. T. (1991). The uniqueness bias: Studies of constructive social comparison. Journal of Experimental Social Psychology, 27(3), 258–275.

Suls, J., Lemos, K., & Stewart, H. L. (2002). Self-esteem, construal, and comparisons with the self, friends, and peers. Journal of Personality and Social Psychology, 82(2), 252–261.

Van Boven, L., White, K., & Huber, M. (2003). Egocentrism, false consensus, and false uniqueness in judgments of traits and behaviors. Journal of Personality and Social Psychology, 85(5), 881–892.

Business Example: The false uniqueness bias can hinder collaboration in workplaces. For example, a manager who overestimates the uniqueness of their leadership style might undervalue team input, leading to reduced innovation and employee dissatisfaction (Goethals et al., 1991).

Additionally, marketers exploit this bias by

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HALO EFFECT The tendency for an individual's positive or negative trait to "spill over" from one area of their personality to another in others' perceptions of them.

"Can you believe it? My sneakers ripped again during training today," Rooney said, clearly annoyed. "That's the second pair this month!"

"Well, don't buy sneakers from that brand anymore – try a different one," Ellie suggested.

"It's not about the brand! Top tennis players endorse this brand!" Rooney insisted confidently.

"I don’t know, maybe those sneakers require special care. Or maybe you're doing something wrong? But anyway, I didn't think you’d fall for advertising like that.

Just because your idol endorses a product doesn't mean it's good. You know this, right? Brands collaborate with stars to leverage their positive reputation to boost sales."

"You're right," Rooney nodded. "I'll try something different. Maybe I am indeed a victim of advertising…"

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About: The halo effect refers to the cognitive bias where an individual’s overall impression of a person, product, or organization influences judgments about their specific attributes.

Introduced by Thorndike (1920), this bias often leads people to assume that a positive trait in one domain extends to other unrelated areas. For instance, a physically attractive person might be perceived as more competent, intelligent, or friendly, even without evidence supporting these assumptions (Nisbett and Wilson, 1977). This phenomenon highlights the human tendency to rely on overarching impressions rather than objective evaluation.

Reproducibility: The halo effect is a welldocumented and replicable phenomenon, with robust evidence spanning decades (e.g., Kim et al., 2025).

Thorndike’s (1920) original experiments demonstrated that military officers’ overall evaluations of soldiers influenced ratings in specific attributes like leadership and physical appearance. Nisbett and Wilson (1977) provided further empirical evidence, showing that an instructor’s perceived warmth altered students’ ratings of unrelated traits. Cross- cultural studies, such as those by Kashima et al. (2004), reveal that the halo effect persists globally, although its manifestation can vary based on cultural norms and values.

Trivia Example: An iconic example of the halo effect is the perception of celebrities endorsing products. Consumers may associate the charisma and success of a celebrity with the quality of the product, despite no direct correlation between the two (Kahneman, 2011). This effect is also evident in education, where students perceived as likable often receive higher evaluations, even in unrelated areas such as intelligence or discipline (Ambady and Rosenthal, 1993).

Selected References

Ambady, N., & Rosenthal, R. (1993). Half a minute: Predicting teacher evaluations from thin slices of nonverbal behavior and physical attractiveness. Journal of Personality and Social Psychology, 64(3), 431–441.

Iyer, G., & Soberman, D. A. (2000). Markets for product modification information. Marketing Science, 19(3), 203– 225.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.

Kashima, Y., Siegal, M., Tanaka, K., & Isaka, M. (2004). Universal biases in self- perception: Evidence from the US, Australia, and Japan. Journal of Cross-Cultural Psychology, 35(5), 563–583.

Kim, K., Ryu, J., Jeon, H., & Suh, B. (2025, July). Blinded by Context: Unveiling the Halo Effect of MLLM in AI Hiring.

In Findings of the Association for Computational Linguistics: ACL 2025 (pp. 26067-26113).

Nisbett, R. E., & Wilson, T. D. (1977). The halo effect: Evidence for unconscious alteration of judgments. Journal of Personality and Social Psychology, 35(4), 250–256.

Rosenzweig, P. (2007). The halo effect… and the eight other business delusions that deceive managers. Public Affairs.

Thorndike, E. L. (1920). A constant error in psychological ratings.

Journal of Applied Psychology, 4(1), 25–29.

Business Example: The halo effect significantly influences consumer behavior and corporate branding. Companies like Apple benefit from their reputation for innovation, leading customers to perceive all Apple products as superior, regardless of individual quality (Iyer and Soberman, 2000). Similarly, employees who excel in one area may be prematurely promoted based on the assumption that their skills are universally transferable, potentially leading to organizational inefficiencies (Rosenzweig, 2007).

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ILLUSION OF ASYMMETRIC INSIGHT

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People perceive their knowledge of their peers to surpass their peers' knowledge of them.

"Hey," Rooney recognized Ellie's voice on the phone, "How was your Saturday? What did you get up to?"

"Oh, just the usual - did some cleaning, went shopping, played with my brother.

Now I'm about to cook dinner. Mom's gone on another business trip."

"Come on, you cleaned? Voluntarily? I'll never believe that! You're probably just lounging around playing video games!"

Rooney coughed in surprise, accidentally dropping his computer mouse on the floor.

"Alright, fine – I didn't clean everywhere, just tidied up the kitchen a bit, and I was just about to play a game while my brother's watching cartoons. What about you?"

"I went for a run this morning."

"That's unlikely. You probably slept in until noon and are now watching some movie while munching on cake!"

Ellie choked and dropped her fork, which she was using to eat an apple pie: "Wow, you've got me all figured out! Okay, I admit, I didn't get around to running today and yes, I am eating apple pie right now, but just a tiny piece! I promise, I'll definitely go for a run tomorrow!"

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understanding of consumer needs, leading to misaligned offerings. For example, high-profile product failures often arise when executives ignore consumer feedback, relying instead on perceived insight into market trends (Kahneman and Klein, 2009).

About: The illusion of asymmetric insight is a cognitive bias where individuals believe they understand others better than others understand them. This phenomenon stems from overconfidence in one’s introspective capabilities and the tendency to assume privileged access to others’ motivations and internal states. Pronin et al.

(2001) suggest that people rely heavily on observable cues and stereotypes to infer others’ traits and behaviors while simultaneously believing their own motivations and intentions are more complex and difficult to decode. This results in a biased perspective where individuals overestimate their ability to perceive others while underestimating how transparent their own thoughts and feelings might be.

Reproducibility: The illusion of asymmetric insight has been extensively studied and replicated across diverse contexts (e.g., Steglich-Petersen and Skipper, 2019). Pronin et al. (2004) conducted controlled experiments demonstrating that participants consistently believed they could predict others’ preferences and motivations more accurately than others could predict theirs. This bias is also evident across cultures, although its intensity varies based on norms around self-perception and relational dynamics (Heine and Lehman, 1997). Furthermore, studies in organizational behavior confirm that hierarchical dynamics exacerbate the bias, with leaders particularly prone to overestimating their insight into employee needs and motivations.

Trivia Example: This bias is often evident in social dynamics, such as when a person in a friendship claims to “know the other person better than they know themselves.” This assumption can lead to misunderstandings, especially when one party imposes their interpretation of the other’s behavior without considering alternative perspectives. It also manifests in educational settings, where teachers may believe they understand a student’s learning challenges better than the student does, potentially leading to ineffective interventions (Pronin et al., 2001; Pronin et al., 2004).

Selected References

Heine, S. J., & Lehman, D. R. (1997). Culture, self-discrepancies, and self- satisfaction. Personality and Social Psychology Bulletin, 23(9), 913–925.

Kahneman, D., & Klein, G. (2009). Conditions for intuitive expertise: A failure to disagree. American Psychologist, 64(6), 515–526.

Pronin, E., Kruger, J., Savtisky, K., & Ross, L. (2001). You don't know me, but I know you: The illusion of asymmetric insight. Journal of Personality and Social Psychology, 81(4), 639.

Pronin, E., Gilovich, T., & Ross, L. (2004). Objectivity in the eye of the beholder: Divergent perceptions of bias in self versus others. Psychological Review, 111(3), 781–799.

Ross, L., & Ward, A. (1996). Naive realism in everyday life: Implications for social conflict and misunderstanding. In E. Reed, E. Turiel, & T. Brown (Eds.), Values and knowledge (pp. 103–135). Lawrence Erlbaum Associates.

Steglich-Petersen, A., & Skipper, M. (2019). Explaining the illusion of asymmetric insight. Review of Philosophy and Psychology, 10(4), 769-786.

Business Example: In business, the illusion of asymmetric insight can hinder collaboration and decision-making.

Managers may assume they fully understand the motivations and challenges of their team members while dismissing feedback or suggestions from subordinates. Similarly, companies designing products or marketing strategies might assume they have a superior 365

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ILLUSION OF TRANSPARENCY People overestimate others' ability to know them, and they also overestimate their ability to know others.

"Listen, do you mind if I skip the party tonight?"

Ellie asked. "Why's that?"

"Courtney will be there. She really gets on my nerves."

"I get it," Rooney replied, "But how exactly?"

"She's always offended by everything and expects others to comfort her. Last time, I spent half the evening with her on the stairs. I asked her, 'What’s wrong?' and she said 'Nothing,' while crying. I thought maybe she needed some time alone to calm down, so I tried to leave, but then she was like, 'Where are you going? Can't you see how upset I am?' I tried explaining that maybe she needed some space, but she said, 'Can't you see I’m feeling terrible and shouldn’t be left alone?'"

"What a mess," Rooney said, after hearing Ellie out, "You don't have to sit with Courtney and try to figure out how she feels. You don't need to do that. She's an adult and can handle herself. I promise, if you come, I'll keep Courtney off your back."

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understood by employees, leading to missed expectations and reduced productivity.

Similarly, during negotiations, individuals may overestimate how clearly their position or emotional stance is perceived by the opposing party, which can result in strategic missteps (Van Zant and Kray, 2014). Understanding this bias can improve clarity in communication and prevent overconfidence in interpersonal exchanges.

About: The illusion of transparency is a cognitive bias where individuals overestimate how apparent their internal thoughts, emotions, or intentions are to others. Rooted in egocentrism, this bias arises because individuals are highly attuned to their own internal states and mistakenly assume that others share the same level of awareness (Gilovich et al., 1998). This disconnect often leads to overconfidence in how effectively one’s emotions or intentions are communicated. For example, nervousness during a presentation or dishonesty in a negotiation might feel overwhelmingly obvious to the person experiencing it, even though observers are often oblivious to such subtleties.

Reproducibility: Gilovich et al. (1998) demonstrated the bias in settings where participants believed their lies were more easily detected by observers than was actually the case. Savitsky and Gilovich (2003) extended these findings to public speaking scenarios, showing that speakers consistently overestimated how noticeable their anxiety appeared to audiences. Cross-cultural studies have confirmed that the intensity of the illusion may vary by context and culture (Savitsky et al., 2001).

Trivia Example: An illustrative case of the illusion of transparency is found in public speaking.

Speakers frequently believe their nervousness— manifested in trembling hands or a racing heartbeat—is blatantly obvious to the audience.

However, research demonstrates that audiences are typically unaware of these cues and judge speakers based more on content and overall demeanor (Savitsky and Gilovich, 2003). This misperception can exacerbate anxiety, creating a feedback loop that further diminishes performance.

Selected References

Gilovich, T., Medvec, V. H., & Savitsky, K. (1998). The illusion of transparency: Biased assessments of others’ ability to read our emotional states. Journal of Personality and Social Psychology, 75(2), 332–346.

Savitsky, K., & Gilovich, T. (2003). The illusion of transparency and the alleviation of speech anxiety. Journal of Experimental Social Psychology, 39(6), 618–625.

Savitsky, K., Epley, N., & Gilovich, T. (2001). Do others judge us as harshly as we think? Overestimating the impact of our failures, shortcomings, and mishaps. Journal of Personality and Social Psychology, 81(1), 44–56.

Van Zant, A. B., & Kray, L. J. (2014). I can see both sides: The illusion of transparency and integrative negotiation outcomes. Organizational Behavior and Human Decision Processes, 124(2), 124–138.

Business Example: In workplace settings, the illusion of transparency can lead to ineffective communication. A manager, for instance, may assume that their ambiguous instructions are

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ILLUSORY SUPERIORITY Overestimating one's desirable qualities, and underestimating undesirable qualities, relative to other people.

"Wow, I didn't expect such a crowd," Rooney remarked, as he and Ellie approached the cinema where a massive queue wrapped around the building several times.

Rooney continued in amazement, "I don't get it.

The announcement said this special screening of 'Star Wars' was for die-hard fans who know the franchise and the books it's based on inside out. There's supposed to be a selection quiz before entry. Do all these people really know 'Star Wars' that well to pass the quiz?"

"It's not about whether they actually know 'Star Wars' or not, it's about what they think they know," Ellie replied. "Most people overestimate their abilities, thinking they're above average. Like how most people believe they're better than average drivers, but in reality, they're not. It's the same here – many people believe they know everything about 'Star Wars'."

Rooney looked uncertain. "I wonder if it's worth waiting in this line?"

"Since we're here, let's give it a shot. I believe in you!" Ellie said encouragingly.

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have demonstrated the robustness of illusory superiority (e.g., Corbu et al., 2025). Alicke et al.

(1995) found consistent evidence of individuals rating themselves higher than average across diverse traits. However, some cultural variations exist; collectivist cultures, such as Japan, exhibit weaker manifestations of this bias compared to individualistic cultures like the United States (Heine and Lehman, 1997). Additionally, the bias is moderated by domain-specific expertise.

Experts in a given field are less prone to illusory superiority within their domain, though they may exhibit it in unrelated areas (Kruger and Dunning, 1999). These findings suggest the phenomenon is replicable but context-sensitive, highlighting the interplay of individual and cultural factors.

About: Illusory superiority, often referred to as the “better-than-average effect,” is a cognitive bias in which individuals overestimate their own qualities, abilities, and characteristics relative to others. This bias is pervasive, especially in areas such as intelligence, driving skills, and moral behavior (Alicke and Govorun, 2005). For instance, most individuals believe they are better-than-average drivers despite the statistical improbability of such a majority. This overestimation is linked to self- enhancement motivations, where individuals seek to maintain a positive self-image, often at the expense of objectivity.

Trivia Example: One of the most cited examples of illusory superiority comes from a study by Svenson (1981), in which 93% of U.S. drivers rated themselves as above average in terms of driving safety. Such overconfidence is not confined to driving but extends to various domains, including academics, where students frequently overestimate their performance on exams (Dunning et al., 2004).

Selected References

Alicke, M. D., & Govorun, O. (2005). The better-than-average effect. The Self in Social Judgment, 85-106.

Alicke, M. D., Klotz, M. L., Breitenbecher, D. L., Yurak, T. J., & Vredenburg, D. S. (1995). Personal contact, individuation, and the better-than-average effect. Journal of Personality and Social Psychology, 68(5), 804–825.

Camerer, C., & Lovallo, D. (1999). Overconfidence and excess entry: An experimental approach. American Economic Review, 89(1), 306–318.

Corbu, N., Halagiera, D., Jin, S., Stanyer, J., Strömbäck, J., Matthes, J., ... & Aalberg, T. (2025). Illusory superiority about misinformation detection and its relationship to knowledge and fact-checking intentions: Evidence from 18 countries. Mass Communication and Society, 1-20.

Dunning, D., Johnson, K., Ehrlinger, J., & Kruger, J. (2004). Why people fail to recognize their own incompetence. Current Directions in Psychological Science, 12(3), 83–87.

Heine, S. J., & Lehman, D. R. (1997). The cultural construction of self- enhancement: An examination of group-serving biases. Journal of Personality and Social Psychology, 72(6), 1268–1283.

Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121–1134.

Moore, D. A., & Healy, P. J. (2008). The trouble with overconfidence. Psychological Review, 115(2), 502–517.

Svenson, O. (1981). Are we all less risky and more skillful than our fellow drivers? Acta Psychologica, 47(2), 143–148.

Business Example: In corporate settings, illusory superiority can lead to overconfident decision-making, especially among managers and leaders. For example, executives might overestimate their ability to predict market trends or make strategic decisions, leading to costly errors (Moore and Healy, 2008). Similarly, entrepreneurs often underestimate the risks associated with launching a business, believing their ventures are more likely to succeed than statistical averages suggest (Camerer and Lovallo, 1999).

Reproducibility: Numerous studies across cultures and contexts 369

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ILLUSION OF EXTERNAL AGENCY When people believe that an outside force, agent, or influence is guiding their actions.

"Hey, Ellie," Rooney greeted her warmly, "Feels like ages since I've seen you!"

"Yeah, sorry, I've been caught up rehearsing for a play. The premiere's next week, so it's been really busy," Ellie explained.

"I see. How are the rehearsals going?"

"We had the dress rehearsal today. The director said it went well and even complimented me, but I don't know..."

"Why's that?" Rooney asked curiously.

"He always tries to boost my morale, even when I'm not happy with my own performance."

"Nonsense! I'm sure next week's performance will be fantastic, not just because the director encourages you, but because you've worked so hard on your role!"

Rooney said confidently.

"I hope so," Ellie shrugged, "Anyway, I'm planning to wear my 'lucky bracelet' for good measure."

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client indecisiveness, often overlook their own decision-making flaws or team inefficiencies.

This bias can hinder organizational learning and lead to repetitive mistakes (Kahneman, 2011).

About: The illusion of external agency occurs when individuals attribute their own actions, thoughts, or emotions to external forces or entities. This bias often manifests in scenarios involving supernatural beliefs, conspiracy theories, or even daily decision-making, where individuals underestimate their own agency in creating outcomes. It has been linked to cognitive dissonance reduction, as people may find it easier to externalize blame or responsibility rather than confront their own role in an event (Wegner, 2002). For example, people might attribute a successful exam outcome to luck or divine intervention rather than their own preparation.

Replicability: Wegner et al. (2004) demonstrated that individuals could be led to believe they had less control over actions they consciously performed when misled by external cues. Similarly, research on learned helplessness supports the notion that individuals attribute lack of control to external factors, even when such control exists (Abramson et al., 1978). However, cultural differences influence the prevalence of this bias (e.g., Loehr, 2022). Collectivist societies might externalize success to group or societal factors more often than individuals in individualistic cultures (Markus and Kitayama, 1991).

Trivia Example: A classic instance is seen in spiritual or paranormal experiences.

For example, individuals who claim to witness poltergeist activity often interpret unexplained sounds or movements as external agency, despite the possibility of natural explanations like wind or faulty construction (Irwin, 2009). Such attributions satisfy a cognitive need for explanations, particularly in ambiguous situations.

Selected References

Abramson, L. Y., Seligman, M. E., & Teasdale, J. D. (1978). Learned helplessness in humans: Critique and reformulation.

Journal of Abnormal Psychology, 87(1), 49–74.

Irwin, H. J. (2009). The psychology of paranormal belief: A researcher’s handbook. University of Hertfordshire Press.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus, and Giroux.

Loehr, J. D. (2022). The sense of agency in joint action: An integrative review. Psychonomic Bulletin & Review, 29(4), 1089-1117.

Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation.

Psychological Review, 98(2), 224–253.

Wegner, D. M. (2002). The illusion of conscious will. MIT Press.

Wegner, D. M., Sparrow, B., & Winerman, L. (2004).

Vicarious agency: experiencing control over the movements of others. Journal of Personality and Social Psychology, 86(6), 838–848.

Business Example: In organizational settings, the illusion of external agency can impede accountability.

Employees attributing project failures to external factors, such as market conditions or

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JUST-WORLD HYPOTHESIS The belief that the world is fundamentally just, causing people to rationalize an otherwise inexplicable injustice as deserved by the victim(s).

"Hey, Ellie, where are you headed? Let me help you with those bags," Rooney offered, taking the packages Ellie was carrying.

"Didn't you hear? April broke her leg. I'm on my way to visit her in the hospital," Ellie explained.

"Wait, is this the same April who spilled coffee on your painting right before the last exhibition? And the same April who harassed you for three weeks until you painted something for her for another exhibition?" Rooney asked.

"Firstly, yes, the very same April. Secondly, she didn’t do those things on purpose!"

"I think you're being too kind to her. She's just a terrible person, and if she broke her leg, I think it's just karma for the way she treated you," Rooney remarked.

"How can you say that?" Ellie retorted, taking back the bags. "She's in the hospital, and you're talking about karma!"

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demonstrated this bias in experiments where observers attributed unjust outcomes to victims’ behavior. More recent research has shown cultural differences in the extent of this bias, with individualistic societies exhibiting stronger justworld beliefs than collectivist ones (Bègue, 2002).

While replicable, its manifestation is influenced by context, individual differences, and cultural values (e.g., Zhang and Zhang, 2025).

About: The just-world hypothesis posits that people have an inherent need to believe that the world is fair and that individuals generally get what they deserve. This belief can influence judgments and behaviors, leading to victim-blaming or the minimization of systemic inequities. For instance, observers may rationalize negative outcomes by attributing them to the victim’s actions or characteristics, reinforcing the idea that bad things only happen to those who deserve them (Lerner and Simmons, 1966). This bias is often subconscious and serves to protect individuals from the discomfort of perceiving an unpredictable and unjust world.

Selected References

Bègue, L. (2002). Belief in a just world and the ideologies of inequality. European Journal of Social Psychology, 32(2), 105–113.

Furnham, A. (2003). Belief in a just world: Research progress over the past decade. Personality and Individual Differences, 34(5), 795–817.

Hafer, C. L., & Bègue, L. (2005). Experimental research on justworld theory: Problems, developments, and future challenges. Psychological Bulletin, 131(1), 128–167.

Lerner, M. J., & Simmons, C. H. (1966). Observer’s reaction to the “innocent victim”: Compassion or rejection? Journal of Personality and Social Psychology, 4(2), 203–210.

Zhang, X., & Zhang, Y. (2025). Belief in a just world or belief in just others? a study on the object of belief in a just world. BMC psychology, 13(1), 564.

Trivia Example: A well-known illustration of the just-world hypothesis is public responses to crime victims.

For example, individuals may blame victims of theft for “not being careful enough” rather than considering the broader socio-economic factors that contribute to criminal behavior (Hafer and Bègue, 2005). Such attributions provide a sense of moral order, albeit at the expense of empathy.

Business Example: In organizational contexts, the just-world hypothesis can hinder diversity and inclusion efforts.

For instance, underperforming employees from marginalized backgrounds may be unfairly judged as inherently less competent, ignoring the systemic barriers they face.

Similarly, leaders might downplay the impact of workplace inequalities, assuming that all employees have equal opportunities to succeed (Furnham, 2003).

Replicability: Numerous studies have validated the just-world hypothesis. Lerner and Simmons (1966) 373

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MORAL LUCK The tendency to blame or praise individuals for actions that were largely determined by factors over which they had no control.

"Listen, do you know anyone good at math or programming? I'm putting together a team for a programming competition and we're one person short," Rooney said, hoping Ellie could help. "One of our guys got sick, and we can't find a replacement."

"I'm not sure," Ellie shrugged. "Let me think.

Wait, maybe Daniel? He's good at programming."

"Not him!" Rooney waved his hands dismissively. "That guy is a walking disaster. Did I tell you about when he went with me to the international business competition?"

"No, what happened?"

"What happened? First, as soon as he got on the bus, the bus got a flat tire. Then, they put him in the same hotel room as me, and the first thing he did was break the toilet flush tank. Then, the water in our room got cut off because he tried to fix the tank himself.

And then, he ironed his shirt and knocked out the power on the whole floor. By the time we fixed everything with two stunned technicians, it was 3 AM. And when I finally went to bed, I found out Daniel snores like a freight train. Naturally, we lost the next day. No, anyone but him."

"You're being weird – those are just prejudices.

Those events weren’t Daniel’s fault. Just bad luck," Ellie said.

"I don't know – but one thing I do know for sure is that bad luck only seems to follow him and whoever is with him. I'll find someone else!"

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strategy results in financial losses, they are likely to be labeled as reckless or incompetent. This dichotomy reveals how external factors, such as market fluctuations or unforeseen crises, heavily influence judgments of success or failure, often overriding considerations of intent or expertise (Bazerman and Moore, 2012).

About: Moral luck refers to the phenomenon where an individual’s actions are judged morally not only based on their intentions but also on the outcomes of those actions, even when those outcomes are beyond the individual’s control (Nagel, 1979). This bias highlights a tension between the ethical principle of fairness and the reality of human moral judgment. For example, someone who negligently drives drunk and arrives home safely may be perceived as less culpable than another individual who engages in the same behavior but causes a fatal accident. In both cases, the intentions and actions are identical, yet moral judgments differ due to the role of chance, underscoring the influence of uncontrollable factors on evaluations of responsibility.

Replicability: Empirical research provides evidence for the pervasiveness of moral luck across various domains (e.g., Carlson et al., 2025). Cushman (2008) conducted controlled experiments where participants judged identical actions with differing outcomes and found consistent differences in moral evaluations. Further studies have demonstrated the cultural variability of moral luck, with collectivist societies exhibiting stronger tendencies to judge outcomes over intentions compared to individualist cultures (Weber et al., 2004). These findings suggest that while the phenomenon is replicable, its expression may depend on cultural norms and contexts.

Trivia Example: The concept of moral luck is vividly illustrated in historical and legal contexts. For instance, in war crimes trials, soldiers acting under identical orders may receive starkly different judgments depending on the observable outcomes of their actions, such as civilian casualties. Similarly, in corporate scandals, executives who narrowly avoid economic downturns despite engaging in risky or unethical behaviors are often lauded as strategic thinkers, while those who fail face moral condemnation, regardless of identical decision-making processes (Williams, 1981).

Selected References

Bazerman, M. H., & Moore, D. A. (2012). Judgment in managerial decision making (8th ed.). Wiley.

Carlson, E., Johansson, J., & Nyman, A. (2025). Higher-Order Control: An Argument for Moral Luck. Australasian Journal of Philosophy, 1-11.

Cushman, F. (2008). Crime and punishment: Distinguishing the roles of causal and intentional analyses in moral judgment. Cognition, 108(2), 353–380.

Nagel, T. (1979). Moral luck. In Mortal Questions (pp. 24–38).

Cambridge University Press.

Weber, J., Kopelman, S., & Messick, D. M. (2004). A conceptual review of decision-making in social dilemmas: Applying a logic of appropriateness. Personality and Social Psychology Review, 8(3), 281–307.

Williams, B. (1981). Moral luck. Proceedings of the Aristotelian Society, Supplementary Volumes, 50, 115–135.

Business Example: In the business world, moral luck often manifests in evaluations of leadership and decisionmaking. A CEO who makes aggressive financial decisions that yield massive profits may be celebrated as visionary. However, if the same 375

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NAÏVE CYNICISM Expecting more egocentric bias in others than in oneself.

"Rooney, it's great you're here, I need some help," Ellie said as she saw Rooney, "could you please help me move these boxes?"

"Sure, what's all this?" Rooney asked, eyeing the boxes curiously.

"I'm gathering some items for charity. Rob asked me to put together a few boxes for the homeless," Ellie explained while arranging the boxes.

"I don't get why you're helping this Rob guy," Rooney expressed in surprise, "you do realize he's doing charity work not to help others, but just to show off, right? He doesn't care about the homeless!"

"There you go again, seeing ulterior motives everywhere," Ellie sighed, "Rob is doing this from the goodness of his heart! So, are you going to help or not?"

"I'll help, but you should really keep an eye on Rob," Rooney grumbled, lifting a box.

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organizational change as purely self-serving, underestimating legitimate concerns about job security or workload. This dynamic can erode trust and collaboration within teams, highlighting the need for transparent communication.

About: Naïve cynicism refers to the tendency to believe that others are more self- serving or biased in their judgments and actions than they actually are, even when evidence suggests otherwise (Kruger and Gilovich, 1999). This bias can lead to the assumption that others’ opinions or decisions are primarily driven by selfish motives, while one’s own judgments are perceived as objective and fair. Naïve cynicism is rooted in an asymmetry in how individuals evaluate themselves versus others, often leading to miscommunication and distrust in interpersonal and professional relationships.

Replicability: Research consistently validates the existence of naïve cynicism. Kruger and Gilovich (1999) demonstrated the bias through experimental studies, showing that participants consistently underestimated the altruistic motives of others.

Research by Ross and Ward (1996) revealed that individuals overestimate the role of self- interest in others’ behavior, even when provided with evidence to the contrary. These findings have been replicated in various domains, from legal judgments to healthcare decision-making, confirming the robustness of the phenomenon while highlighting its implications for organizational and societal interactions.

Trivia Example: A famous example of naïve cynicism is seen in political discourse, where individuals frequently attribute opposing viewpoints to ulterior motives or self-interest. For instance, a voter may assume that supporters of an opposing political party are solely driven by personal gain, even when their positions align with altruistic values or societal benefit. This bias exacerbates polarization by fostering a belief that disagreement stems from self-interest rather than genuine differences in ideology.

Selected References

Kruger, J., & Gilovich, T. (1999). “Naïve cynicism” in everyday theories of responsibility assessment: On biased assumptions of bias. Journal of Personality and Social Psychology, 76(5), 743–753.

Ross, L., & Ward, A. (1996). Naive realism in everyday life: Implications for social conflict and misunderstanding. In E. S. Reed, E. Turiel, & T. Brown (Eds.), Values and knowledge (pp. 103–135). Lawrence Erlbaum Associates.

Van Lange, P. A., & Kuhlman, D. M. (1994). Social value orientations and impressions of others: A theoretical and empirical review. European Review of Social Psychology, 5(1), 33–59.

Tsay, C. J., Shu, L. L., & Bazerman, M. H. (2011). Naivete and cynicism in negotiations and other competitive contexts. The Academy of Management Annals, 5(1), 495518.

Yamagishi, T., & Kiyonari, T. (2000). The group heuristic in social dilemmas. Psychological Review, 107(4), 844–860.

Business Example: In the workplace, naïve cynicism often manifests in performance evaluations or negotiations (e.g., Tsay et al, 2011). Employees might assume that management decisions, such as budget cuts, are primarily aimed at boosting executive bonuses, ignoring broader organizational constraints or strategic considerations. Conversely, leaders might view employee resistance to

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NAÏVE REALISM Belief that we see reality as it really is – objectively and without bias; that the facts are plain for all to see; that rational people will agree with us; and that those who don't are either uninformed, lazy, irrational, or biased. ”What’s going on?" Ellie asked, looking at Rooney's morose expression.

"Just that I planned to hit the beach today, but no one wanted to come along. Everyone's super busy..."

"Maybe they really are busy?"

"Yeah right, they just don't want to go," Rooney muttered under his breath.

Ellie smiled, "Did you even check the weather forecast? There was a storm warning issued!"

"So what? It's actually perfect weather for surfing."

"Did you ever consider that others might perceive risk differently? What's 'perfect surfing weather' for you is dangerously stormy weather for them."

Rooney pondered for a moment.

"You're right," he finally said after a long silence.

"I hadn't thought of that." "Let's go to a café – it's better than heading to the beach in a storm!"

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misunderstanding often leads to decreased morale and inefficiencies, highlighting the importance of fostering open dialogue.

About: Naïve realism is the cognitive bias in which individuals believe their perceptions and interpretations of the world reflect reality objectively, assuming that others who disagree are either uninformed, irrational, or biased (Ross and Ward, 1996). This bias fosters overconfidence in one’s perspective and can exacerbate interpersonal and societal conflicts. It is closely tied to the belief that one’s perceptions are unbiased and rational, whereas others’ views are tainted by subjectivity. This phenomenon highlights the inherent challenges in reconciling opposing viewpoints, as it creates barriers to understanding and compromise.

Replicability: The concept of naïve realism has been extensively validated across experimental and real-world contexts. Ross and Ward (1996) demonstrated its pervasiveness in various social and political domains, where individuals were prone to dismiss opposing viewpoints as irrational. Recent studies have explored its implications in global conflicts, showing how it deepens divisions by undermining empathy and constructive dialogue (Pronin et al., 2004). The robust replication of naïve realism in diverse cultural and situational settings highlights its robustness. Mitigating its effects requires targeted interventions such as perspectivetaking exercises and education (e.g., Mazullo and Raimondi, 2025).

Trivia Example: One illustrative example of naïve realism is seen in sports fandom. Fans of rival teams often believe that referees unfairly favor the opposing team, assuming their judgments to be biased.

Studies by Hastorf and Cantril (1954) on perceptions of a football game revealed that fans of competing teams perceived the same events, such as fouls, differently based on their allegiance, emphasizing the subjective nature of reality shaped by personal biases.

Selected References

Hastorf, A. H., & Cantril, H. (1954). They saw a game: A case study.

Journal of Abnormal and Social Psychology, 49(1), 129– 134.

Mazzullo, G., & Raimondi, A. (2025). Naïve Realism, Seemings, and the Nature of Visual Experiences. American Philosophical Quarterly, 62(3), 233-247.

Pronin, E., Gilovich, T., & Ross, L. (2004). Objectivity in the eye of the beholder: Divergent perceptions of bias in self versus others. Psychological Review, 111(3), 781–799.

Ross, L., & Ward, A. (1996). Naive realism in everyday life: Implications for social conflict and misunderstanding. In E. S. Reed, E. Turiel, & T. Brown (Eds.), Values and knowledge (pp. 103–135). Lawrence Erlbaum Associates.

Sherman, D. K., & Cohen, G. L. (2006). The psychology of selfdefense: Self- affirmation theory. Advances in Experimental Social Psychology, 38, 183–242.

Business Example: Naïve realism frequently arises in organizational change management. Employees may perceive proposed changes as unnecessary or flawed, believing their understanding of the company’s processes is more accurate than that of senior management. Similarly, leaders may dismiss employees’ concerns as resistance to progress rather than valid feedback. This mutual

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BEN FRANKLIN EFFECT A person who has done someone a favor is more likely to do that person another favor than they would be if they had received a favor from that person.

"Where did you get those cookies from?" Rooney asked. "Remember our agreement? No sugar."

"Of course, I remember," Ellie replied. "These aren't for me; they're for Dad's guests tonight. My brother's wife, Courtney, baked them. I asked her for help since I've been swamped. I still have dinner to prepare for the evening guests!"

"Courtney? Baked them?" Rooney feigned surprise. "But you two can't stand each other! Why would she help you?"

"Stop it, Courtney's not that bad. We've actually become friends recently. I asked for her help with some shopping the other day, and she lent a hand. And today, she baked these cookies."

"Become friends? Wow, that's unexpected!

Alright, how can I help you?"

"Could you wash the vegetables, please? We need to start preparing dinner."

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increasing the likelihood of future purchases.

Similarly, leaders who request employees’ input on projects often find that these employees become more engaged, justifying their effort by believing in the leader’s vision or the project’s value.

About: The Ben Franklin Effect is a psychological phenomenon where people who do someone a favor are more likely to do another favor for that person in the future, even if they initially had no positive feelings toward them. Rooted in cognitive dissonance theory, this bias arises because individuals seek to resolve the inconsistency between their actions and their attitudes. To reduce discomfort, they convince themselves that they must like the person they helped, thus justifying their behavior (Jecker and Landy, 1969). The effect is named after Benjamin Franklin, who recounted an incident in his autobiography where he requested a favor from a political rival. By borrowing a rare book and subsequently thanking him, Franklin found that his rival’s attitude softened, transforming an adversary into a friend.

Replicability: Jecker and Landy (1969) demonstrated that participants who were asked by the experimenter to return money (as a personal favor) rated the experimenter more favorably than those who were asked to return the money by a secretary or not asked at all. Later studies, such as those by Swann et al. (1990), confirmed the effect, showing that favor-giving strengthens interpersonal bonds.

However, cultural differences can influence its magnitude (e.g., Finger, 2006). In collectivist societies, where helping behavior is a norm, the effect may be less pronounced because favors are often attributed to societal expectations rather than personal preference.

Trivia Example: The Ben Franklin Effect is often observed in social situations where small acts of cooperation build rapport. For instance, during school group projects, students who help their peers with minor tasks often feel closer to those individuals later, attributing their willingness to assist to a budding friendship. This process reinforces the bonds formed through seemingly insignificant interactions.

Selected References

Jecker, J. D., & Landy, D. (1969). Liking a person as a function of doing them a favor. Human Relations, 22(4), 371–378.

Franklin, B. (1906). The autobiography of Benjamin Franklin. P. F. Collier & Son. Swann, W. B., Jr., Stein-Seroussi, A., & Giesler, R. B. (1990). Why people self-verify. Journal of Personality and Social Psychology, 59(3), 500–513.

Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.

Finger, S. (2006). Benjamin Franklin and the neurosciences. Functional neurology, 21(2), 67.

Nisbett, R. E., & Ross, L. (1980). Human inference: Strategies and shortcomings of social judgment. Prentice-Hall.

Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation.

Psychological Review, 98(2), 224–253

Business Example: In business, the effect is utilized to foster stronger customer relationships and employee engagement. Customer loyalty programs often include requests for small actions, such as leaving a review or filling out a survey. By completing these tasks, customers perceive themselves as more aligned with the brand, 381

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BIAS BLIND SPOT The tendency to see oneself as less biased than other people, or to be able to identify more cognitive biases in others than in oneself.

"The best phone is definitely an iPhone," Rooney declared confidently. "I don't understand how people can use Androids!"

"Many people at my dad's work use Androids, and they're perfectly fine," Ellie countered.

"That's probably just because Google partially sponsors your dad's workplace equipment.

So, most people there use Androids, even though iPhones are better!"

"Wait a minute," Ellie said, her voice dripping with sarcasm. "So, you're suggesting that my dad's colleagues are biased because Google sponsors them, but you're not biased at all?"

"What do you mean?"

"Well, Apple sponsors your robotics club!"

"That's ridiculous," Rooney retorted, a bit offended. "That has nothing to do with my choice of smartphone!" "Sure, of course!"

Ellie laughed.

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their assumptions.

About: The bias blind spot is a cognitive bias wherein individuals recognize the susceptibility of others to biases but fail to identify similar biases in themselves (Pronin et al., 2002). This phenomenon arises from the introspection illusion, which leads individuals to trust their own reasoning as objective and free from bias, while they attribute others’ reasoning to subjective influences. People erroneously believe that they are capable of evaluating situations rationally and independently, yet perceive others as less capable due to bias. This bias has significant implications for interpersonal relationships, decision-making, and conflict resolution, as it creates an illusion of superiority in judgment.

Replicability: Pronin et al. (2002) demonstrated that participants consistently rated themselves as less biased compared to their peers, even when presented with evidence of their biases in tasks like anchoring or overconfidence. Cross- cultural studies further corroborate this finding, indicating that the bias is not limited to specific populations or contexts (e.g., Scopelliti et al., 2015). However, its intensity may vary depending on factors like cognitive ability, openness to feedback, and the complexity of the decision at hand (e.g., Kelly, 2024). Interventions, such as self-reflective exercises and training in metacognition, have shown potential in reducing this bias. For instance, structured feedback sessions have been effective in prompting individuals to acknowledge their own biases, enhancing decision-making in organizational and personal contexts.

Trivia Example: A classic example of the bias blind spot occurs in discussions of ethical dilemmas. In a classroom setting, students may criticize historical figures for moral failings, viewing their decisions as a result of bias or ignorance, while failing to recognize how their own perspectives are shaped by contemporary cultural norms and personal experiences.

Selected References

Pronin, E., Lin, D. Y., & Ross, L. (2002). The bias blind spot: Perceptions of bias in self versus others. Personality and Social Psychology Bulletin, 28(3), 369–381.

Scopelliti, I., Min, H. S., McCormick, E., Kassam, K. S., & Morewedge, C. K. (2015). Bias blind spot: Structure, measurement, and consequences. Management Science, 61(10), 2468–2486.

Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.

Kelly, T. (2024). Bias, norms, introspection, and the bias blind spot 1. Philosophy and Phenomenological Research, 108(1), 81-105.

Nisbett, R. E., & Ross, L. (1980). Human inference: Strategies and shortcomings of social judgment. Prentice-Hall.

Pronin, E. (2007). Perception and misperception of bias in human judgment. Trends in Cognitive Sciences, 11(1), 37–43.

Wilson, T. D., & Brekke, N. (1994). Mental contamination and mental correction: Unwanted influences on judgments and evaluations. Psychological Bulletin, 116(1), 117–142.

Business Example: In corporate settings, the bias blind spot can manifest when team leaders assume their strategies are data-driven and objective, dismissing dissenting opinions from colleagues as biased or uninformed. This bias can stifle innovation and collaboration, as individuals are less likely to reflect on their own decisionmaking processes. Organizations addressing this bias often implement structured decisionmaking frameworks, encouraging teams to consider multiple perspectives and challenge 383

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COMPASSION FADE The predisposition to behave more compassionately towards a small number of identifiable victims than to a large number of anonymous ones.

"Hey, Ellie, how's everything going?" Rooney asked.

"Not great," Ellie was upset. "No one wanted to donate for the African children. I don't know what to do. It seems like nobody cares that children in Africa are dying from hunger."

"It's not that people don't care. It's just that 'African children' is an abstract concept for many. People do care about the fate of a specific child, but the more people who are in need, the less compassion they feel.

Does it make sense?"

"I see," Ellie said. "Will you help me organize a new fundraising campaign? I hadn't considered that people don't understand what I'm talking about."

"Of course, I'll help! We need to find specific children in need and tell their stories to people. The result will be completely different – you'll see!"

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while maximizing impact.

About: Compassion fade describes a psychological bias in which individuals’ empathy and motivation to help diminish as the number of people in need increases. This counterintuitive phenomenon suggests that as crises grow in scale, people become less emotionally engaged, a behavior attributed to psychological numbing and perceived helplessness (Slovic, 2007). The identifiable victim effect— a tendency to feel more compassion for a single, identifiable individual than for a group—is often cited as a related mechanism (Small et al., 2007). As a result, large-scale humanitarian crises or disasters may receive insufficient aid despite their severity.

Replicability: The replicability of compassion fade has been well-documented in both laboratory and realworld settings. Slovic (2007) demonstrated that participants were more inclined to donate when presented with the story of one child compared to statistical information about widespread suffering. Subsequent experiments corroborated these findings, showing a decline in emotional engagement and financial contributions as the number of victims increased (Dickert et al., 2011).

Cameron and Payne (2011) found cross-cultural evidence of this bias, suggesting that psychological mechanisms like cognitive overload and the perceived inefficacy of individual action contribute universally to compassion fade. While interventions like focusing on collective agency have shown promise, addressing the inherent limitations of human empathy remains challenging.

Trivia Example: A striking example of compassion fade occurred during the Syrian refugee crisis in 2015. A photo of Aylan Kurdi, a young child who drowned attempting to reach safety, garnered worldwide attention and spurred donations. In contrast, the broader crisis, involving millions of refugees, often failed to elicit the same emotional and financial response. This disparity highlights how people are more moved by the plight of one individual than by abstract statistics or larger groups.

Selected References

Cameron, C. D., & Payne, B. K. (2011). Escaping affect: How motivated emotion regulation creates insensitivity to mass suffering. Journal of Personality and Social Psychology, 100(1), 1–15.

Dickert, S., Sagara, N., & Slovic, P. (2011). Affective motivations to help others: A two-stage model of donation decisions.

Journal of Behavioral Decision Making, 24(4), 361–376.

Slovic, P. (2007). If I look at the mass I will never act: Psychic numbing and genocide. Judgment and Decision Making, 2(2), 79–95.

Small, D. A., Loewenstein, G., & Slovic, P. (2007). Sympathy and callousness: The impact of deliberative thought on donations to identifiable and statistical victims.

Organizational Behavior and Human Decision Processes, 102(2), 143–153.

Västfjäll, D., Slovic, P., & Mayorga, M. (2014). Compassion fade: Affect and charity are greatest for a single child in need.

PLOS ONE, 9(6), e100115.

Business Example: Nonprofit organizations and humanitarian campaigns often combat compassion fade by focusing on individual stories. For instance, World Vision’s “sponsor a child” campaigns personalize large-scale issues like hunger or poverty, making them relatable and actionable.

Businesses using corporate social responsibility initiatives often face similar challenges, as they must balance emotional engagement with factual representation to maintain credibility 385

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CURSE OF KNOWLEDGE When better-informed people find it extremely difficult to think about problems from the perspective of lesser-informed people.

Saturday, you know."

"Listen, I've been trying to solve this physics problem all night. Can you explain what 'antimatter' is?"

"Antimatter? Sure! You see, besides normal matter, which everything is made of, there's also antimatter. Its existence is due to the existence of symmetric particleantiparticle pairs. For example, electronpositron, proton-antiproton, and so on.

When a particle and its antiparticle collide, they annihilate each other – the particles mutually destroy each other, releasing a significant amount of energy. Does that make sense?"

"Annihilate-what? Can you explain the same thing, but in normal, human language?"

"Sorry," Rooney said, "I got a bit carried away with the terms. You see, at the moment of the Big Bang, when the universe was just born, an equal amount of matter and antimatter appeared..." He paused, thought for a moment, and then said, "How about this, I'll freshen up, have breakfast, and come over. I'll explain everything to you in normal 'human' language. I promise! You should rest in the meantime."

"Okay, thanks! I'll be waiting for you!" Ellie said and headed to the kitchen to make coffee.

"Rooney, hello!" Rooney immediately recognized Ellie's voice over the phone.

"Hi," Rooney glanced at the clock - it was half past five in the morning. "Why are you up so early? Is something wrong? It's 386

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healthcare, often struggle with making information accessible to non- experts.

About: The curse of knowledge describes a cognitive bias where individuals, once they know something, find it challenging to imagine not knowing it.

This bias can distort how experts communicate with novices, often leading to an overestimation of the audience’s knowledge (Camerer et al., 1989). The bias is prevalent in diverse domains, including education, business, and technology, where experts may struggle to break down complex ideas for laypersons. The inability to “unlearn” information or adopt a beginner’s perspective often results in ineffective communication and frustration.

Replicability: Hinds (1999) demonstrated that experts systematically overestimate novices’ ability to understand tasks, regardless of complexity. Birch and Bloom (2007) extended this research by showing that even young children exhibit a rudimentary form of this bias, suggesting that it arises early in cognitive development. Recent experiments using real-world scenarios, such as technical communication and instructional design, further confirm the bias’s robustness (Rozenblit and Keil, 2002). Efforts to mitigate this bias, such as training individuals in perspectivetaking and using feedback loops, have yielded mixed results, highlighting the entrenched nature of this cognitive distortion.

Trivia Example: An illustrative example is the “tapping experiment” conducted by Newton (1990), in which “tappers” who tapped out a well-known song rhythmically overestimated the likelihood that listeners would identify it. Tappers believed that 50% of the audience would recognize the song, but the actual success rate was only 2.5%.

This stark difference highlights how knowledge biases perception of simplicity and clarity.

Selected References

Birch, S. A. J., & Bloom, P. (2007). The curse of knowledge in reasoning about false beliefs. Psychological Science, 18(5), 382–386.

Camerer, C., Loewenstein, G., & Weber, M. (1989). The curse of knowledge in economic settings: An experimental analysis. Journal of Political Economy, 97(5), 1232–1254.

Hinds, P. J. (1999). The curse of expertise: The effects of expertise and debiasing methods on predictions of novice performance. Journal of Experimental Psychology: Applied, 5(2), 205–221.

Newton, E. (1990). The curse of knowledge: A bias in perspectivetaking. Unpublished doctoral dissertation, Stanford University.

Rozenblit, L., & Keil, F. (2002). The misunderstood limits of folk science: An illusion of explanatory depth. Cognitive Science, 26(5), 521–562.

Business Example: The curse of knowledge frequently manifests in corporate communication. For instance, technical jargon often confuses customers unfamiliar with the industry. Companies like Apple, renowned for simplifying complex technology for the average user, actively work against this bias by employing user- centric language and intuitive design. However, firms in more technical fields, such as finance or

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COURTESY BIAS The tendency to give an opinion that is more socially correct than one's true opinion, so as to avoid offending anyone.

Rooney and Ellie were sitting in a café, discussing a movie they had seen the night before.

"Here's your coffee and water," the waitress said, placing a cup of coffee in front of Rooney.

However, the glass of water slipped from her hand and fell to the floor next to their table, splashing Rooney. Shards of glass scattered across the floor, some even landing on the table.

A smiling manager appeared as if out of nowhere.

"We'll clean this up right away," he said. "The employee who served you will be replaced.

Let's move you to another table."

"Thank you," Rooney replied, dabbing at his trousers with a napkin. "But there's no need to punish anyone. Everything is fine.

It was probably my own awkward hand movement that caused it… We're comfortable here, right, Ellie?"

"Definitely. There is nothing wrong with the lady who was looking after us," Ellie nodded.

"Are you sure?" the manager asked.

"Absolutely," Rooney reassured him. "It's just water, after all."

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anonymous feedback mechanisms and foster cultures that value candor, emphasizing that constructive criticism drives growth and innovation (Edmondson, 1999).

About: Courtesy bias refers to the tendency of individuals to withhold negative opinions or provide overly positive feedback to avoid offending others, maintaining social harmony or preserving relationships (Fisher, 1993). It is particularly prevalent in collectivist cultures, such as those in East Asia, where social harmony is highly valued, but it also appears in individualist societies, albeit to a lesser extent.

Courtesy bias skews decision-making processes by presenting a falsely positive view of opinions or outcomes. For example, in feedback or evaluation scenarios, individuals may feel obligated to inflate their assessments to align with perceived social expectations, often at the expense of honesty and constructive dialogue (Heine et al., 2002).

Replicability: The courtesy bias has been observed in diverse contexts, from customer satisfaction surveys to workplace evaluations (Heine et al., 2002). Fisher and Tellis (1998) demonstrated that patients in healthcare settings often rated their experiences positively, especially during direct interactions with providers. Similarly, studies across cultures highlight that collectivist societies exhibit a stronger tendency toward courtesy bias, linked to values of group harmony and indirect communication styles. Interventions, including anonymous feedback tools and culturally tailored survey methods, have shown varying success in mitigating the bias but remain context-dependent. Laboratory experiments and field studies reinforce its robustness, though its intensity fluctuates based on cultural norms and situational dynamics.

Trivia Example: A striking manifestation of courtesy bias can be observed in restaurant reviews. Diners, when faced with servers inquiring about their meal, often express satisfaction even if the food or service failed to meet their expectations. This stems from an innate discomfort with confrontation or the desire to avoid awkward interactions (Fisher and Tellis, 1998).

Selected References

Edmondson, A. C. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383.

Fisher, R. J. (1993). Social desirability bias and the validity of indirect questioning. Journal of Consumer Research, 20(2), 303–315.

Fisher, R. J., & Tellis, G. J. (1998). Removing social desirability bias with indirect questioning: Is the cure worse than the disease? Advances in Consumer Research, 25, 563–567.

Heine, S. J., Lehman, D. R., Peng, K., & Greenholtz, J. (2002).

What’s wrong with cross-cultural comparisons of subjective Likert scales?: The reference-group effect.

Journal of Personality and Social Psychology, 82(6), 903– 918.

Business Example: In professional environments, courtesy bias undermines performance reviews and feedback systems. Employees, particularly subordinates, may hesitate to critique managers or colleagues honestly, fearing retaliation or conflict. For instance, an overly generous performance review might result in stagnation as genuine areas for improvement are obscured. To combat this, organizations such as Netflix employ 389

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HOSTILE ATTRIBUTION BIAS The tendency to interpret others' behaviors as having hostile intent, even when the behavior is ambiguous or benign.

"I see you've become friends with Rob," Rooney remarked. "What were you two whispering and laughing about? He was probably making jokes about me."

"Listen," Ellie frowned, "this isn't funny anymore. You see some sort of malice in everything. First, yes, we're friends, and second, he just told me a joke. It had nothing to do with you. And third, stop acting like a child!"

"Alright, alright. I'm sorry. I was wrong."

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through emotional intelligence training and conflict resolution workshops can foster a more harmonious and productive workplace culture (Yang and Salmivalli, 2013).

About: Hostile attribution bias is the tendency to interpret ambiguous or neutral behaviors of others as intentionally hostile or aggressive (Dodge, 1980). This bias often emerges in conflictladen or emotionally charged interactions, contributing to misunderstandings and escalating interpersonal disputes. Rooted in cognitive distortions, it is particularly prevalent among individuals with heightened sensitivity to rejection or those who have experienced trauma or adversity during childhood (Crick and Dodge, 1996). For instance, if someone bumps into an individual in a crowded hallway, a person exhibiting hostile attribution bias may assume the act was deliberate rather than accidental, triggering a defensive or aggressive reaction.

Replicability: Dodge (1980) demonstrated the histile attribution bias prevalence among children with behavioral issues, revealing that they are more likely to perceive hostility in neutral situations.

Subsequent research has replicated these findings in adult populations, particularly in high-stress environments such as law enforcement or competitive sports (Epps and Kendall, 1995). Interventions like cognitivebehavioral therapy have shown promise in reducing the bias, emphasizing the role of reframing exercises in mitigating misinterpretations of intent (Yeager et al., 2013).

Trivia Example: Hostile attribution bias is frequently depicted in media. For example, in courtroom dramas, characters often misinterpret neutral statements or behaviors as aggressive cross-examinations, further escalating tensions. This portrayal highlights the bias’s role in interpersonal conflict, where individuals perceive malice even in benign contexts (Dodge, 1980).

Selected References

Crick, N. R., & Dodge, K. A. (1996). Social information-processing mechanisms in reactive and proactive aggression. Child Development, 67(3), 993– 1002.

Dodge, K. A. (1980). Social cognition and children’s aggressive behavior. Child Development, 51(1), 162–170.

Epps, J., & Kendall, P. C. (1995). Hostile attributional bias in adults: Cognitive underpinnings and links to aggression. Cognitive Therapy and Research, 19(2), 159– 178.

Yang, A., & Salmivalli, C. (2013). Different forms of bullying and victimization: Bully-victims versus bullies and victims. European Journal of Developmental Psychology, 10(6), 723–738.

Yeager, D. S., Miu, A. S., Powers, J., & Dweck, C. S. (2013). Implicit theories of personality and attributions of hostile intent: A meta-analysis, an experiment, and a longitudinal intervention. Child Development, 84(5), 1651–1667.

Business Example: In workplace settings, hostile attribution bias can hinder teamwork and collaboration. A manager who misinterprets an employee’s request for clarification as insubordination may respond with unwarranted hostility, damaging morale and trust. Addressing such biases

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IDENTIFIABLE VICTIM EFFECT The tendency to respond more strongly to a single identified person at risk than to a large group of people at risk.

"What are you hiding here for?" Ellie asked. "The party's in full swing, and you're sitting in the kitchen."

"I don't want to talk to Daniel," Rooney mumbled. "And why's that?"

"They caught him cheating on the last math test." "I see, but what does that have to do with you?"

"The thing is, I spent almost a month helping him prepare for that test. And can you believe it? They didn't expel him; they just made him retake it. They should've kicked him out!"

"Don't worry," Ellie said, patting Rooney on the shoulder. "Some percentage of students always cheat on exams."

"I'm not talking about 'some percentage' of students, I'm talking about a specific person."

"I understand," Ellie said. "Come on, let's get out of here. It's not worth spending the whole evening in the kitchen."

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engage consumers emotionally and increase charitable giving or purchases linked to social causes. This has been observed in the success of charity-driven product campaigns, where donations are tied to purchasing specific products, such as the “Product Red” campaign for HIV/AIDS awareness, which effectively utilized identifiable victims to boost sales and awareness (Berman and Kim, 2010).

About: The identifiable victim effect refers to the psychological phenomenon in which people are more likely to help a single, identifiable victim rather than a large group of anonymous victims, even when the aggregate suffering is greater in the latter case (Small et al., 2007). This bias stems from emotional responses to specific, humanized individuals, which often elicit a stronger empathetic reaction than statistical or abstract representations of larger groups. When a victim is given a name, face, or personal story, people are more inclined to act, often driven by the perceived moral imperative to help someone they can relate to personally (Kogut and Ritov, 2005). The identifiable victim effect is commonly observed in charitable donations, where appeals featuring a single individual are more successful than those that focus on the broader need.

Replicability: Research has shown that individuals donate more money to causes when the appeal focuses on a specific person, compared to when the appeal is framed in terms of a larger group or statistical need (Kogut and Ritov, 2005).

However, the effect’s replicability can depend on factors like the perceived closeness or similarity of the victim to the potential donor. Studies have also explored its ethical implications, questioning whether focusing on individual victims can overshadow broader systemic issues (Cialdini et al., 1997).

Trivia Example: In the context of media coverage, stories featuring individual victims of disasters or crimes often receive more attention and emotional support than those focusing on the broader context. For instance, news reports about a missing child or a heroic individual in a disaster usually result in larger donations or public support than stories about the same disaster affecting hundreds of people, showcasing how the identifiable victim effect shapes public response.

Selected References

Berman, J. Z., & Kim, J. (2010). Do good deeds make you feel good?

The impact of perceived prosocial behavior on consumer responses. Journal of Consumer Research, 37(4), 551-559.

Cialdini, R. B., Brown, S. L., Lewis, B. P., Luce, C., & Neuberg, S. L. (1997). Reinterpreting the empathy–altruism relationship: When one into one equals oneness. Journal of Personality and Social Psychology, 73(3), 481–494 Kogut, T., & Ritov, I. (2005). The “identifiable victim” effect: An identified group, or just a single individual? Journal of Behavioral Decision Making, 18(3), 157-167.

Small, D. A., Loewenstein, G., & Slovic, P. (2007). Sympathy and callousness: The impact of deliberative thought on donations to identifiable and statistical victims.

Organizational Behavior and Human Decision Processes, 102(2), 143-153.

Business Example: In marketing and corporate social responsibility (CSR), the identifiable victim effect can be used strategically. A company may showcase individual stories of those affected by a cause (e.g., a child suffering from a disease) in order to 393

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PYGMALION EFFECT The phenomenon whereby higher expectations lead to an increase in performance.

"Congratulations," Ellie beamed with pride for Rooney. "You played fantastically today!"

"Thanks," he said, a hint of surprise in his voice.

"I never expected to win the cup - it's all thanks to my new coach, Matt, you, and everyone who believed in me. So many people told me before the tournament that I could win! I just couldn't let you all down.

Matt trained me almost every day for the past six months. I owe him a lot. The main thing is, all of you inspired me to go the extra mile. And here's the result! Thank you, Ellie!"

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encouragement and belief from a leader can directly influence performance outcomes. By cultivating a culture of high expectations and positive reinforcement, companies can foster greater engagement and achievement among their staff.

About: The Pygmalion effect refers to the phenomenon where higher expectations lead to an increase in performance. It is named after the myth of Pygmalion, a sculptor who fell in love with a statue he had carved, which then came to life. The effect occurs when an individual’s performance is influenced by the expectations others have of them. This effect has been demonstrated in various settings, from education to business. It highlights the power of belief and expectations in shaping behavior (Rosenthal and Jacobson, 1968). In the early study by Rosenthal and Jacobson, teachers were told that certain students were “late bloomers” expected to show significant academic improvement. These students, who were randomly selected, showed higher academic growth by the end of the year, demonstrating how the teachers’ expectations shaped their students’ performance. The Pygmalion effect reveals how social and organizational contexts can shape individuals’ outcomes and offers insight into the selffulfilling nature of expectations.

Replicability: Research has shown that when individuals are aware that others have high expectations of them, they are more likely to perform better.

However, replicating the Pygmalion effect can depend on the context and the strength of the expectations communicated (e.g., Veestraeten et al., 2021). Expectations are more likely to influence performance in environments where individuals believe that they are being closely monitored and evaluated (Brophy, 1983). The effect’s replicability has been examined in several domains, including educational settings, where the impact of teacher expectations on student achievement has been widely studied (Jussim and Harber, 2005). However, some studies suggest that the magnitude of the effect can vary depending on factors such as personality traits, the type of task, and the strength of the leader’s belief in the individual (e.g., Latham and Locke, 2007).

Trivia Example: Coaches who believe in the potential of certain athletes, even if the athletes themselves have yet to display exceptional talent, tend to provide those athletes with more opportunities and feedback, which boosts their performance. For instance, studies in basketball teams have shown that coaches’ beliefs in players’ abilities can lead to greater effort and improved performance, effectively creating a self-fulfilling prophecy (Latham and Locke, 2007).

Selected References

Brophy, J. E. (1983). Research on the self-fulfilling prophecy and teacher expectations. Journal of Educational Psychology, 75(5), 631–661.

Brophy, J. E., & Good, T. L. (1986). Teacher behavior and student achievement. In M. C. Wittrock (Ed.), Handbook of research on teaching (3rd ed., pp. 328–375). Macmillan.

Jussim, L., & Harber, K. D. (2005). Teacher expectations and selffulfilling prophecies: Addressing the shortcomings of the meta-analytic evidence. Personality and Social Psychology Review, 9(2), 131-155.

Latham, G. P., & Locke, E. A. (2007). New developments in and directions for goal-setting research. European Psychologist, 12(4), 290–300.

Rosenthal, R., & Jacobson, L. (1968). Pygmalion in the classroom: Teacher expectation and pupils’ intellectual development. Holt, Rinehart, & Winston.

Veestraeten, M., Johnson, S. K., Leroy, H., Sy, T., & Sels, L. (2021).

Exploring the bounds of Pygmalion effects: Congruence of implicit followership theories drives and binds leader performance expectations and follower work engagement. Journal of leadership & organizational studies, 28(2), 137-153.

Business Example: In business, the Pygmalion effect has significant implications for leadership and management.

Managers who set high expectations for their employees and express belief in their abilities tend to see increased productivity and job satisfaction among their team members (Brophy and Good, 1986). This can be particularly effective in settings like sales teams, where 395

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SOCIAL DESIRABILITY BIAS The tendency to respond to questions in a manner that will be viewed favorably by others.

"How are you doing?" Rooney asked. "Oh, you know, alright," Ellie replied.

"I can tell something's up. What happened?"

"It's nothing. Just that for my internship, I had to conduct a series of interviews on a sensitive social issue. I chose to focus on drinking and driving, but it didn't go well."

"Why not?"

"I interviewed 20 people, but all of them claimed they'd never driven under the influence.

How am I supposed to create this series when I have no real material? It's obvious that at least some of them were lying."

"People will never admit to driving while intoxicated themselves. Why don't you change your question? Instead of asking about their own behavior, why not ask how many drivers, in their opinion, drive drunk?"

"You're right, I hadn't thought of that," Ellie said.

"But I probably won't have enough time to gather new material now."

"Nonsense, I'll help you! Let's draft a new list of questions and quickly survey more drivers."

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product or service to avoid feeling impolite. This creates a distortion in the feedback data that organizations rely on to make decisions regarding improvements, policies, and product development. Companies like Gallup and others that conduct employee engagement surveys often utilize methods to control for social desirability bias, such as anonymous surveys or carefully phrased questions, to mitigate its impact (King et al., 2004).

About: Social desirability bias refers to the tendency of individuals to respond in a manner that will be viewed favorably by others, often distorting their true beliefs or behaviors. This bias arises from the desire to conform to social norms or expectations and to present oneself in a positive light. It is commonly observed in self-report surveys, interviews, and questionnaires, where respondents may overstate their moral behaviors or accomplishments and underreport socially undesirable actions. For example, in surveys about alcohol consumption or smoking, people often downplay their use to align with societal norms that discourage such behaviors (Tourangeau and Yan, 2007). Social desirability bias can lead to inaccurate data in fields such as public opinion research, health surveys, and market research. The impact of this bias is heightened when the subject matter involves topics that are considered sensitive or socially charged, such as political opinions, income levels, or personal relationships. Over time, this tendency can result in skewed perceptions of behaviors or opinions across populations.

Replicability: The social desirability bias is consistently observed in research across various settings and populations. Replication studies confirm its presence in self-reported data and highlight the challenges it poses to data accuracy (Van de Mortel, 2008). However, the extent of the bias may vary depending on the topic under discussion, the method of data collection, and the individual’s level of social concern. For example, several studies found that individuals with higher social self-consciousness were more likely to exhibit social desirability bias. Additionally, recent research indicates that face-to-face interviews tend to elicit more pronounced social desirability bias compared to anonymous surveys. Despite efforts to control for this bias, such as through the use of indirect questioning or randomized response techniques, achieving measurement accuracy remains a challenge (e.g., Bursztyn et al., 2025).

Trivia Example: When voters are asked about their preferred candidate, they may be more inclined to report a preference for a candidate they believe is socially accepted, even if they privately hold different views. This phenomenon can lead to a misrepresentation of public opinion, particularly in tightly contested races where individuals fear social judgment for supporting a less popular candidate (Blair et al., 2017).

Selected References

Blair, J., Blair, M., & Heavner, M. (2017). Social desirability bias in surveys: A review. Public Opinion Quarterly, 81(1), 49-62.

Bursztyn, L., Haaland, I. K., Röver, N., & Roth, C. (2025). The Social Desirability Atlas (No. w33920). National Bureau of Economic Research.

King, E. B., & King, D. M. (2004). Social desirability bias in selfreport surveys: A review of the literature. Journal of Applied Social Psychology, 34(10), 1855-1883.

Tourangeau, R., & Yan, T. (2007). Sensitive questions in surveys.

Psychological Bulletin, 133(5), 859-883.

Van de Mortel, T. F. (2008). Faking it: Social desirability bias in self-report research. Australian Journal of Advanced Nursing, 25(1), 40-48.

Business Example: In business, social desirability bias is a critical factor when conducting employee satisfaction surveys or customer feedback questionnaires.

Employees might underreport negative sentiments about management or workplace conditions for fear of retaliation, while customers might exaggerate their satisfaction with a 397

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SHARED INFORMATION BIAS The tendency for group members to spend more time and energy discussing information that all members are already familiar with and less time and energy discussing information that only some members are aware of.

"How was rehearsal?" Rooney asked.

"There was no rehearsal," Ellie shook her head.

"Instead, we spent an entire hour debating whether we want to move to a new rehearsal space." "What's wrong with the old one?"

"Nothing really. But there are rumors that they're planning to demolish the building where we rehearse to build a new supermarket."

"I'm a bit confused then. Shouldn't the first step be to find out if the building is actually being demolished?" Rooney questioned.

"I agree with you, but you know how people love to discuss what everyone else knows. So, we ended up talking about the rumors.

Probably, only our director knows the actual situation. But he wasn't there today.

Heard he's sick."

"Just don't get upset before you know for sure.

We should find out the real story first and then decide."

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obvious data, such as emerging market niches or competitor weaknesses, go unmentioned. Such biases can lead to missed opportunities for innovation or poorly informed decisions. In response, companies have been increasingly adopting “pre-mortem” analysis, which encourages the team to actively consider unique or dissenting opinions before decisions are finalized (Klein, 2007).

About: Shared information bias, or the “common knowledge effect,” occurs when group members prioritize discussing information known to all, rather than unique insights held by individuals.

This leads to distorted discussions where shared ideas are reinforced at the expense of diverse perspectives that could improve decisionmaking. The bias is common in settings like board meetings, jury deliberations, and project teams, where familiar information dominates while novel insights are overlooked (Stasser and Titus, 1985). This limits creativity and critical thinking, particularly in high-stakes environments. Research shows that groups tend to ignore unshared information, resulting in suboptimal outcomes (Wittenbaum et al., 2004).

Mitigating this bias requires intentionally structuring discussions to encourage unique contributions and promote diverse viewpoints.

Replicability: Studies have demonstrated that when teams are asked to discuss complex problems, they disproportionately discuss common knowledge and ignore unique information, even if it would lead to better outcomes. Wittenbaum et al.

(2004) conducted a study where groups of participants were tasked with solving problems, and they found that while groups were more likely to recall shared information, they often ignored unshared facts that could have helped them achieve better results. Research has shown that the bias can be mitigated with strategies such as structured discussions, anonymity in sharing information, or deliberate encouragement to present unshared information (Bohnet et al., 2008).

Trivia Example: Research has shown that jurors are more likely to discuss and emphasize facts that are known by all, while minimizing the consideration of unique information provided by individual jurors (Stasser et al., 1989). This dynamic can lead to poorer verdicts, as critical, less-known information that may alter the course of the trial gets overlooked in favor of more familiar, shared knowledge.

Selected References

Bohnet, I., Frey, B. S., & Huck, S. (2001). More order with less law: On contract enforcement, trust, and crowding. American Political Science Review, 95(1), 131–144.

Klein, G. (2004). The power of intuition: How to use your gut feelings to make better decisions at work. Doubleday.

Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48(6), 1467–1478.

Stasser, G., Vaughan, S. I., & Wittenbaum, G. M. (1989).

Information exchange and influence in groups. European Journal of Social Psychology, 19(5), 287–300.

Wittenbaum, G. M., Stasser, G., & McDoom, L. (2004). The influence of information sampling on group decisionmaking. Organizational Behavior and Human Decision Processes, 93(2), 169–180.

Business Example: In business settings, shared information bias often emerges in project team meetings or brainstorming sessions, where participants may spend excessive time discussing ideas or facts everyone is already aware of. For instance, in a marketing team meeting, members might spend time rehashing common trends in consumer behavior, while valuable insights from less 399

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SINGULARITY EFFECT The tendency to place a disproportionate weight on the last information encountered when making a decision.

In the center of the park, near the fountain, an elderly woman was sitting, knitting gray socks. Spread out on the ground beside her was a small mat, on which lay several pairs of knitted socks and a hat for collecting money.

However, few passersby seemed interested in the socks.

Rooney approached the old woman and carefully placed $10 in her hat.

"What did you do?" Ellie looked at Rooney in surprise. "It's the first time I've seen you help the poor." "'The poor' is an abstract concept. But I know this old lady."

"I don't understand. What does it matter whether you know her or not?" "There's a big difference. She lives on the next street," Rooney replied calmly. "I know you like various charity funds, but I don’t really trust them. Besides, that's not the main point. You see, funds are almost always large organizations working with groups of people. But this is a specific person, and someone I know. I always try to help this old lady."

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Apple during the peak of the iPhone’s dominance, may fail to innovate in other areas.

As a result, these businesses may be vulnerable to market disruptions or technological advancements that reduce the singular product’s market share. In such cases, decision-makers may neglect other products or the need for diversification, thinking that one major success will continue to drive growth. In contrast, companies that avoid the singularity effect take a more holistic approach to business strategy, investing in multiple areas of development and remaining agile in response to market shifts (Christensen, 1997).

About: The singularity effect is a cognitive bias where people fixate on a single significant event or factor, overestimating its importance while ignoring relevant context. This often occurs when individuals or groups become preoccupied with an exceptional success, failure, or discovery, failing to see the broader complexity. In technology, for example, excitement over a breakthrough AI model can eclipse awareness of its limitations. The effect influences both individual and group decisions, as dramatic or visible events are prioritized over less publicized but relevant details. It is especially prevalent in media coverage, where singular events like scandals or financial crashes receive outsized attention, skewing public perception. Mitigating this bias requires a more nuanced, contextual analysis that accounts for multiple contributing factors (e.g., Majumder et al., 2024).

Replicability: Behavioral economics research shows that people often fixate on extreme events—like stock market crashes or natural disasters—while underestimating gradual trends (Tversky and Kahneman, 1982). Replication studies across fields such as technology forecasting and crisis management confirm that dramatic events disproportionately shape risk and outcome judgments. However, this bias can be mitigated through critical thinking, exposure to multiple perspectives, and training to consider broader contexts (Tversky and Kahneman, 1981). While robust, the singularity effect’s impact varies with cognitive skills and the strategies used to counter it.

Trivia Example: Often, a singular catastrophic event, such as the 2008 financial crash, is attributed to a single cause, such as subprime mortgage lending or the collapse of a major financial institution.

However, this oversimplification ignores the broader set of systemic, global factors that contributed to the crisis. This focus on one event overshadows more complex, long-term issues such as global financial imbalances and regulatory failures, which are crucial for understanding the root causes of such economic downturns. When consumers and policymakers are exposed only to sensationalized stories, they may misperceive the real causes of economic instability, leading to ineffective responses.

Selected References

Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard Business Review Press.

Majumder, R., Tai, Y. L., Ziano, I., & Feldman, G. (2024). Revisiting the impact of singularity on the Identified Victim Effect: Replication and extension of Kogut and Ritov (2005a) Study 2. Judgment and Decision Making, 19, e26.

Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453-458.

Tversky, A. & Kahneman, D. (1982). Judgment under uncertainty: Heuristics and biases. In Rationality in Action: Contemporary approaches, edited by P.K. Moser, Cambridge University Press.

Business Example: In business, the singularity effect is evident when firms overvalue a single product, service, or breakthrough at the expense of a more balanced strategy. For example, companies that become overly reliant on one successful product, such as 401

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SYSTEM JUSTIFICATION The tendency to defend and bolster the status quo. Existing social, economic, and political arrangements tend to be preferred, and alternatives disparaged sometimes even at the expense of individual and collective self-interest.

"Thanks for picking me up," said Ellie. She had spent the entire day at a homeless shelter, assisting the volunteers. "Feeling tired?"

Rooney inquired.

"It was eye-opening," Ellie replied thoughtfully.

"I had some really insightful conversations with the people there. It's interesting to see how some of them view the social and economic system."

"In what way?" Rooney asked, intrigued.

"Well, despite their challenging circumstances, many of them seemed to have a sort of acceptance of the status quo. They believe that the current system, with all its flaws, is somehow justified. It's like they think those who are better off must have worked harder or deserved it more."

"It's a complex issue," Rooney added. "But your involvement there is really making a difference, Ellie."

"I hope so," Ellie said, smiling softly.

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About: System justification bias is the cognitive tendency to defend and rationalize existing social, economic, and political systems, even when they are biased or harmful. People often view the status quo as fair and legitimate, despite evidence of inequality or dysfunction. This can lead individuals—including those in marginalized groups—to support policies that disadvantage them, as a way to reduce cognitive dissonance and accept their societal roles (Jost et al., 2004).

The bias appears across contexts, from politics to workplaces, where those in power often justify inequalities that serve their interests. Its strength is shaped by factors such as personal benefit, cultural values, and social identity dynamics (Kay and Jost, 2003).

Business Example: In business, system justification bias appears in corporate structures that reinforce existing hierarchies, even when they create inefficiencies or employee dissatisfaction. Large companies often justify traditional top-down management as the “natural” or most efficient model, despite evidence to the contrary. Innovative firms like Valve Corporation have adopted flat hierarchies and decentralized decision-making, resulting in greater productivity and satisfaction. Still, many firms cling to conventional models, viewing them as “tried and tested,” which prevents exploration of more adaptive, collaborative approaches (e.g., Biedron et al., 2024).

Replicability: Studies show people that often defend the status quo—even unjust systems—as a way to reduce cognitive dissonance and preserve psychological comfort. Jost et al. (2004) found that individuals, including marginalized groups, may endorse ideologies that uphold systemic inequality. The effect’s impact can be reduced by exposure to counter-ideologies and narratives that question the legitimacy of existing systems (Kay and Jost, 2003).

Trivia Example: One striking example of system justification can be seen in the United States during the civil rights movement of the 1960s. Even though a significant portion of the population was suffering under segregationist policies, many individuals, particularly those in positions of power or who were benefiting from the status quo, justified racial inequalities by claiming that the social order was naturally structured in this way. These justifications helped perpetuate oppressive systems by convincing both the oppressors and the oppressed that the prevailing social order was legitimate. While the civil rights movement succeeded in changing laws and practices, elements of system justification persist today in societal attitudes toward wealth inequality, racial discrimination, and political systems, where marginalized groups may accept the status quo as part of an inevitable or “natural” system (Jost et al., 2004).

Selected References

Biedron, H. W., Reimer, N. K., & Balcetis, E. (2024). A systematic review of motivated system justification among youth. Frontiers in Social Psychology, 2, 1440094.

Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25(6), 881–919.

Kay, A. C., & Jost, J. T. (2003). Complementary justice: Effects of “poor but happy” and “poor but honest” stereotype exemplars on system justification and implicit activation of the justice motive. Journal of Personality and Social Psychology, 85(5), 823–837.

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SELF-SERVING BIAS The tendency to claim more responsibility for successes than failures. It may also manifest itself as a tendency for people to evaluate ambiguous information in a way beneficial to their interests.

"Hope I don't end up on Miles' team again," Rooney muttered, feeling anxious about the upcoming tennis competition and the imminent team allocations.

"Why's that?" Ellie asked, her curiosity piqued.

"Didn't you guys win the last two tournaments together?"

"Well, it's complicated," Rooney sighed. "Miles is tough to work with. When we win, he credits it all to his 'superior' skills and intense practice sessions. But when we lose, he blames everyone else but himself— me, the coach, even the referees. It's exhausting. He just refuses to acknowledge his mistakes or take any responsibility for our losses."

"Don't stress too much about it," Ellie reassured him with a smile. "With a bit of luck, you'll get a different partner this time."

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improvement (Miller and Ross, 1975). In terms of employee performance, companies may also encounter issues where employees attribute their successes to personal talent while blaming failures on colleagues or external factors, preventing collaboration and fostering an environment of finger-pointing. To counteract this, organizations need to encourage a culture of accountability and provide mechanisms for honest feedback that helps employees reflect on both their successes and mistakes (e.g., Coutts et al., 2024).

About: Self-serving bias refers to the cognitive tendency of individuals to attribute positive events to their own character or actions, while attributing negative events to external factors. This bias helps protect self-esteem and maintains a favorable view of oneself, even in the face of failure. For example, when an employee receives praise for a successful project, they might attribute it to their skills and hard work, but if the project fails, they might blame external factors such as inadequate resources or an unsupportive team.

Replicability: Studies show that individuals tend to attribute positive outcomes to internal factors (e.g., their abilities or efforts) and negative outcomes to external factors (e.g., luck or circumstances). This bias is robust across cultures but varies in intensity (e.g., Coutts et al., 2024); collectivist cultures, which value group harmony, display it less strongly than individualistic cultures that emphasize personal achievement (e.g., Heine, et al., 1999). The bias is especially pronounced in high-stakes or emotionally charged situations where identity is tied to performance. It can be reduced through interventions like feedback training or fostering a growth mindset, which encourage individuals to view successes and failures more objectively (Dweck, 2006).

Trivia Example: This phenomenon is common in various domains, including academic settings, sports, and business environments (e.g., Mezulis et al., 2004). Research has shown that self-serving bias not only influences how individuals explain their own outcomes but also affects how they perceive others. For instance, people are more likely to attribute the success of others to external factors (e.g., luck or circumstances) rather than acknowledging the role of personal effort or ability (Zuckerman, 1979). While this bias can lead to a more positive self-image, it can also distort reality, preventing individuals from learning from mistakes or accurately assessing their performance.

Business Example: Self-serving bias can play a significant role in managerial decisions. For example, leaders who oversee a successful product launch may attribute the success to their strategic vision and leadership, reinforcing their self-image as competent decision-makers. However, if the product fails in the market, these same leaders may shift the blame to market conditions, a lack of consumer understanding, or external competitors, instead of considering flaws in their decision-making or planning. This pattern can hinder learning within organizations, as leaders may not take full responsibility for failures, missing valuable opportunities for growth and

Selected References

Coutts, A., Gerhards, L., & Murad, Z. (2024). What to blame? Selfserving attribution bias with multi-dimensional uncertainty. The Economic Journal, 134(661), 1835-1874.

Dweck, C. S. (2006). Mindset: The new psychology of success.

Random House.

Heine, S. J., Lehman, D. R., Markus, H. R., & Kitayama, S. (1999). Is there a universal need for positive self-regard?

Psychological Review, 106(4), 766–794.

Miller, D. T., & Ross, M. (1975). Self-serving biases in the attribution of causality: Fact or fiction? Psychological Bulletin, 82(2), 213–225.

Mezulis, A. H., Abramson, L. Y., Hyde, J. S., & Hankin, B. L. (2004).

Is there a universal positivity bias in attributions? A meta-analytic review of individual, developmental, and cultural differences in the self-serving attributional bias. Psychological Bulletin, 130(5), 711–747.

Zuckerman, M. (1979). Attribution of success and failure revisited: Or the motivational bias is alive and well in attribution theory. Journal of Personality, 47(2), 245–287.

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SEXUAL OVER/UNDERPERCEPTION BIAS The tendency to overinterpret signals from the opposite sex as indicating sexual interest, or underinterpret them as non- sexual.

"I'm so fed up with David's pranks!" Ellie exclaimed. "Can you believe he dropped my mouse into jelly again? I had to throw it away."

"Sounds to me like David has a bit of a crush on you," Rooney winked at Ellie. "Don't exaggerate. People show their romantic interests in more mature ways."

"Don't underestimate it. It's obvious he's going out of his way to get your attention."

"Stop making things up, please. Now, I guess I'll have to start locking my mouse in my desk drawer."

"I'm not sure that'll stop him. Next thing you know, he'll find a way to smear something all over your monitor. Just wait and see."

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romantic interest from a male colleague out of concern for misinterpretation. These biases are shaped by social norms and gender stereotypes, underscoring the need for organizations to implement training and awareness programs. By establishing clear boundaries and expectations, businesses can reduce misperceptions and foster healthier professional dynamics (Glick and Fiske, 1996).

About: Sexual over/underperception bias refers to the cognitive tendency to overestimate or underestimate sexual interest and intentions based on social cues or interactions. People often misinterpret others’ behaviors or intentions, leading them to perceive sexual interest where none exists (overperception) or fail to recognize signals of sexual interest (underperception). This bias is often influenced by various social, psychological, and situational factors.

Replicability: Sexual over/underperception bias is observed across diverse populations and contexts. Though the bias is present across cultures, its intensity varies with cultural attitudes toward gender and sexuality (e.g., Miller and Tice, 2001; O’Neil and Green, 1997). Studies in non-Western settings, including Japan and the Middle East (Kashiwabara et al., 2012), confirm its crosscultural validity. Individual differences—such as personality, social intelligence, and past experiences—also affect how frequently the bias appears. Interventions like communication training and raising awareness can help mitigate its effects.

Trivia Example: Individuals may misinterpret friendly or neutral gestures as flirtation, leading them to overestimate someone’s sexual interest in them, while others may fail to recognize clear signs of sexual attraction due to personal insecurities or social conditioning (Lammers et al., 2011).

Research has shown that men are more likely to overperceive sexual interest from women, while women tend to underperceive sexual interest from men, particularly in ambiguous situations (Abbey, 2002). This phenomenon has implications in various contexts, including dating, sexual harassment, and workplace dynamics. Overperception bias can lead to unwanted advances or misunderstandings, while underperception can lead to missed opportunities or failure to recognize genuine interest. The influence of gender, context, and individual differences all play crucial roles in how people interpret sexual cues.

Selected References

Abbey, A. (2002). Alcohol-related sexual assault: A common problem among college students. Journal of Studies on Alcohol, Supplement, 14, 118–128.

Glick, P., & Fiske, S. T. (1996). The ambivalent sexism inventory: Differentiating hostile and benevolent sexism. Journal of Personality and Social Psychology, 70(3), 491-512.

Kashiwabara, K., Tanaka, M., & Yamagishi, T. (2012). Sexual overperception bias in Japan: The role of culture in interpreting sexual cues. Social Psychological and Personality Science, 3(2), 219-224.

Lammers, J., Stoker, J. I., Jordan, J., Pollmann, M., & Stapel, D. A. (2011). Power increases infidelity among men and women. Psychological Science, 22(9), 1191–1197.

Miller, S. L., & Tice, D. M. (2001). The psychological consequences of sexism: Male-to-female gender differences in the perception of sexual harassment. Psychology of Women Quarterly, 25(3), 149-156.

O’Neil, J. M., & Green, K. (1997). The roles of gender and genderrelated biases in sexual harassment perceptions: A review. Psychology of Women Quarterly, 21(2), 277-288.

Business Example: In the workplace, sexual over/underperception bias can lead to misunderstandings, especially when boundaries between colleagues are unclear. A male employee might misread a female colleague’s friendliness as sexual interest, resulting in inappropriate behavior, while a female employee may overlook genuine

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TRAIT ASCRIPTION BIAS The tendency for people to view themselves as relatively variable in terms of personality, behavior, and mood while viewing others as much more predictable.

So, did you ask your dad about the internship in San Francisco?" Rooney inquired.

"No way, he'd never let me go," Ellie replied sadly. "I just flunked physics. I can imagine what he'd say: 'Until you improve your physics grades, no trips for you!'. He thinks he knows me inside out, but honestly, he doesn't understand me at all."

"I think you're being a bit harsh on your dad. He's pretty cool. It seems like you think you've got him figured out, but in reality, he understands you more than you realize!"

"Alright, you're right – I'll ask him today. Maybe I'll get lucky."

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especially evident in hiring, where candidates are judged by surface traits or stereotypes. In leadership assessments, it can reinforce organizational homogeneity by favoring “ideal” traits like decisiveness, while overlooking diverse talents. As a result, organizations may miss out on skilled individuals who don’t fit conventional leadership molds (Schneider, 2004).

About: Trait ascription bias refers to the cognitive tendency to ascribe specific traits to others based on limited or incomplete information, often while failing to apply the same standards to oneself. This bias is grounded in the fundamental attribution error, where individuals are inclined to overestimate the importance of dispositional factors in others’ behavior while underestimating situational influences. For example, a person might label a colleague as lazy for arriving late to work, but when they themselves arrive late, they attribute it to external factors, such as traffic or personal problems.

Replicability: Early work by Ross (1977) and Miller and Ross (1975) highlights how individuals often explain their own behavior situationally while attributing others’ actions to stable dispositions.

Pronin and Ross (2006) extend this by showing that people perceive their future selves more like others, suggesting trait ascription bias even within self-perception. Heine et al. (2002) further complicate cross-cultural comparisons by demonstrating how reference-group effects distort trait evaluations, reinforcing the need for culturally sensitive replication. Together, these studies provide evidence for replicating aspiration bias effects, though researchers must account for cultural, temporal, and contextual moderators to ensure validity.

Trivia Example: This bias can be particularly prominent in situations involving group dynamics, where people perceive members of other groups (e.g., different organizations or cultural groups) as having stereotypical traits, but do not see these traits in themselves or their own groups (e.g., Pronin and Ross, 2006). The trait ascription bias can also be affected by emotional states, previous experiences, and the need for cognitive consistency. Research has demonstrated that this bias can shape perceptions of personality traits in both social and professional contexts, influencing workplace interactions, hiring decisions, and social relationships (Miller and Ross, 1975).

Selected References

Heine, S. J., Lehman, D. R., Peng, K., & Greenholtz, J. (2002).

What’s wrong with cross-cultural comparisons of subjective Likert scales?: The reference-group effect. Journal of Personality and Social Psychology, 82(6), 903–918.

Miller, D. T., & Ross, M. (1975). Self-serving biases in the attribution of causality: Fact or fiction? Psychological Bulletin, 82(2), 213-225. https://doi.org/10.1037/h0076486 Pronin, E., & Ross, L. (2006). Temporal differences in trait selfascription: when the self is seen as an other. Journal of personality and social psychology, 90(2), 197.

Ross, L. (1977). The intuitive psychologist and his shortcomings: Distortions in the attribution process. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 10, pp. 173–220). Academic Press.

Schneider, D. J. (2004). The psychology of stereotyping. Guilford Press.

Business Example: Trait ascription bias often affects employee evaluations and hiring decisions. For example, managers may attribute leadership ability to extroverted employees based on assertiveness, overlooking situational factors like subject familiarity. Conversely, introverted employees may be seen as less competent, despite excelling in roles requiring deep focus. This bias is 409

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ULTIMATE ATTRIBUTION ERROR A group-level bias similar to the fundamental attribution error, where actions by a member of an out-group are attributed more to the person's character than to situational factors, compared with actions by one's in-group.

"Why are you hiding out in the greenhouse?"

Rooney asked Ellie as he came to join her for their trip to the gym.

"Oh, I'm so glad you're here," Ellie replied. "I'm hiding from my mom's friend Mary-Ann. She's staying with us until the end of the week."

"Why are you hiding from her?"

"It's dreadful, you can't imagine the awful prejudices she has." "Like what?"

"For instance, she claimed that people who need to rely on food banks do so not because of their low income or lack of options, but because they're all lazy. Can you believe it?"

"I get why you'd want to avoid her, but you don't need to hide in the greenhouse. You might not change her mind, but I think you should still tell her she's wrong."

"You're right. Just give me a moment to get ready, and we'll head to the gym. I'll definitely talk to Mary-Ann this evening."

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downturns or supply chain issues. However, if a rival team underperforms, the same manager might attribute it to internal flaws—such as laziness or poor leadership. This bias reinforces in-group favoritism and can lead to unfair evaluations, strained interdepartmental relationships, and missed opportunities for organizational learning. Recognizing and correcting for this bias is essential for equitable performance management and fostering a collaborative workplace culture.

About: The ultimate attribution error (UAE) refers to the tendency to attribute negative behaviors of outgroup members to internal flaws, while explaining the same behaviors in ingroup members as caused by external factors. As an extension of the fundamental attribution error, UAE commonly arises in intergroup contexts, where people favor their own group over others.

For example, a rival team member’s failure may be seen as incompetence, while the same failure by a teammate is blamed on bad luck. This bias reinforces stereotypes, fuels prejudice and escalates conflict by promoting an “us versus them” mindset. UAE is prevalent in politics, sports, and workplaces, where it impedes collaboration and supports social hierarchies by justifying discrimination and preserving the status quo.

Replicability: Research consistently shows that people attribute negative behaviors of outgroup members to internal traits, while excusing similar behaviors in ingroup members (e.g., Priedols et al., 2022). Studies across diverse cultures confirm the UAE as a widespread phenomenon, though its expression varies with context and intergroup tension. It tends to intensify during periods of political unrest or racial conflict and has been shown to influence hiring, negotiation, and conflict resolution in diverse organizations. While robust, the UAE’s impact depends on factors such as group identity salience and the nature of the interaction (Hewstone, 1990; Pettigrew, 1979).

Trivia Example: An example of the ultimate attribution error appears in media coverage of crime. When individuals from marginalized racial or ethnic groups commit offenses, reports often emphasize character flaws or cultural deficits, attributing the crime to inherent traits. In contrast, similar acts by majority group members are typically explained through situational factors like stress or mental illness. This pattern reflects the core of the UAE—blaming outgroup members while excusing ingroup members—and reinforces racial and social stereotypes. Research shows this bias is widespread in media reporting, with minority offenders’ backgrounds scrutinized more heavily than those of majority offenders (Dixon and Linz, 2000).

Selected References

Dixon, T. L., & Linz, D. (2000). Overrepresentation and underrepresentation of African Americans and Latinos as lawbreakers on television news. Journal of Communication, 50(2), 131–154.

Dover, T. L., Major, B., & Kaiser, C. R. (2012). Shifting blame: The consequences of attributing inequality to discrimination or lack of effort. Personality and Social Psychology Bulletin, 38(3), 289-301.

Hewstone, M. (1990). The “ultimate attribution error”? A review of the literature on intergroup causal attribution.

European Journal of Social Psychology, 20(4), 311-335.

Pettigrew, T. F. (1979). The ultimate attribution error: Extending Allport’s cognitive analysis of prejudice. Personality and Social Psychology Bulletin, 5(4), 461-476.

Priedols, M., Dimdins, G., Gaina, V., Leja, V., & Austers, I. (2022).

Political trust and the ultimate attribution error in explaining successful and failed policy initiatives. SAGE Open, 12(2).

Business Example: The ultimate attribution error often surfaces in business when managers evaluate employee performance across different teams. For example, if a sales manager sees that their own team missed a quarterly target, they might attribute it to external factors like market 411

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WORSE-THAN-AVERAGE EFFECT A cognitive bias whereby individuals rate their own ability as below average, despite evidence to the contrary.

"Why did you decide not to participate in the exhibition? You've been preparing for half a year!" Rooney asked.

"Do you want me to embarrass myself? I'm not planning on making a fool of myself," Ellie declared.

"Why would you be embarrassed?"

"Because my skills, compared to the other participants, are below average. I have nothing to show. With my level, it's better to just stay home."

"Look," Rooney said confidently, "stop making things up. Don’t be afraid, your work is fantastic. If you back out now, you'll regret it later. Come on, get ready, I'll help you take your work to the gallery!"

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new responsibilities—even when well-qualified (e.g., Whillans et al., 2020).

About: The worse-than-average effect (WTAE) is a cognitive bias where individuals perceive themselves as performing worse than others in specific domains, such as health, intelligence, or job performance. Despite objective evidence of competence, people may overestimate their shortcomings—for example, believing they are less fit or less capable at work than peers, even with positive feedback. This self-critical bias contrasts with the better-than-average effect, where individuals overrate their abilities. WTAE is most pronounced when clear comparison standards are lacking, leading to self-doubt and subjective evaluations. It can negatively impact self-esteem, increase procrastination, and deter people from pursuing challenges (e.g., Hoorens, 1993).

Replicability: The effect has shown consistent replicability across experimental and applied contexts.

Hoorens (1993) documented the robustness of this bias within the broader framework of social comparison, noting that it tends to emerge when individuals lack confidence or perceive the task as highly challenging. Pyszczynski et al. (1985) further demonstrated that individuals selectively seek information that supports selfprotective conclusions, which can reinforce underestimation in performance contexts. More recently, Whillans et al. (2020) proposed a conceptual framework highlighting the motivational and developmental benefits of worse-than-average beliefs, offering a nuanced understanding of when and for whom the effect may be adaptive. Together, these findings affirm the replicability of the effect while also pointing to important boundary conditions and individual differences.

Trivia Example: In a general knowledge competitions such as a trivia quiz, participants may assume that their peers possess superior knowledge in specialized categories like classical music or science, despite having comparable levels of expertise. This bias contrasts with the better-than-average effect and is often observed when tasks are perceived as complex, leading individuals to discount their own competence.

Understanding this phenomenon is important in educational, organizational, and social contexts, as it can influence motivation, self-efficacy, and decisionmaking.

Selected References

Hoorens, V. (1993). The better-than-average effect in social comparison. European Review of Social Psychology, 4(1), 113-139.

Pyszczynski, T., Greenberg, J., & LaPrelle, J. L. (1985). Social comparison after success and failure: Biased search for information consistent with a self-serving conclusion. Journal of Experimental Social Psychology, 21(2), 195–211.

Whillans, A. V., Jordan, A. H., & Chen, F. S. (2020). The upside to feeling worse than average (WTA): A conceptual framework to understand when, how, and for whom WTA beliefs have long-term benefits. Frontiers in Psychology, 11, 642.

Business Example: WTAE emerges when employees underestimate their performance, even after receiving positive feedback. This is common in competitive fields like tech, finance, and academia, where individuals often hold themselves to unrealistic standards. Studies found that employees high in perfectionism or self-criticism were more likely to experience the WTAE. This bias can lead to undervaluing one’s work, increased stress, burnout, and reluctance to pursue promotions or 413

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COLLECTIVE EFFECTS

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AVAILABILITY CASCADE A self-reinforcing process in which a collective belief gains more plausibility through its increasing repetition in public discourse (or "repeat something long enough and it will become true"). with the lions?"

"The dark spooky house? I'm not going there.

That place is haunted, and a witch lives there. They say she killed her whole family.

When we were kids, we called it 'the house of chimeras.' No, let me walk you, but I'm not going in there."

"Really? Are you scared?"

"I'm not scared," Rooney bristled, "I just don't want to go. Everyone says awitch lives there." ”Wow, I didn't think you believed in such gossip.

Where do these medieval ideas come from? Someone probably blurted it out, scared by the look of the house, and it spiralled from there! I remember some irresponsible journalist wrote an article about a 'haunted house' about a year ago.

What witch? An old lady named Josephine lives there, she's 86 and completely harmless. She hasn't killed anyone. It's all nonsense... Just because she lives alone and is different, doesn't make her a witch.

The house was passed down from her grandfather. And it's not black – it's just made of dark gray bricks."

"And why do you need her?" Rooney asked skeptically.

"Have you seen her garden and greenhouse? She knows a lot about plants. She has some of the best orchids in the country. This orchid," Ellie pointed to the small sprout in the pot, "just won't grow. I want to show it to Josephine and ask for advice. Don't be silly. Let's go."

"Okay - let's go - I trust you," Rooney said, hoisting the bag onto his shoulder.

"Let's go," Ellie said, smiling. "I baked the cake – I bet we will probably be treated to tea."

"Hi, Rooney - good that you came. Can you help me? Take this bag and this orchid, and come with me," Ellie pointed to a sports bag and a pot with a tiny orchid sprout. She herself was holding a small-sized cake.

"Alright," Rooney said, "but where are we going?"

"To the next street – you know the big house 416

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behavior, especially with product fads. For example, the rapid rise of fidget spinners was driven by media coverage, viral social media, and influencer endorsements. As the product was repeatedly seen and discussed, its perceived value grew, triggering the social proof heuristic— people assumed popularity signaled worth.

Despite no major innovation, the sheer volume of exposure inflated its appeal, leading to widespread adoption. Eventually, as interest faded, the cascade reversed, demonstrating how information repetition can distort consumer perception and drive short-lived trends.

About: The availability cascade refers to a selfreinforcing cycle where a belief or idea gains more credibility and spreads more widely simply because it is repeatedly mentioned or widely discussed (e.g., Tversky and Kahneman, 1974). As more individuals or media outlets begin to present a particular idea, its perceived validity increases, making it seem more accurate or truthful to the general public. This bias operates on the availability heuristic, where the frequency or salience of information influences our perception of its truth. As an idea becomes more available in public discourse, its visibility boosts confidence in its accuracy, even if the evidence supporting it is limited or false. For example, sensationalized news reports about certain risks, such as the spread of diseases or criminal activity, can escalate fear and lead to a distorted view of their actual prevalence. Over time, this cascade effect can shape collective opinions, beliefs, and even policy decisions, regardless of the underlying factual accuracy. The phenomenon plays a significant role in shaping public opinion, particularly in the context of politics, health scares, and social issues (e.g., Shiller, 2000).

Replicability: The availability cascade draws on wellestablished psychological mechanisms that have demonstrated strong replicability across studies.

Tversky and Kahneman’s (1974) foundational work on the availability heuristic provides the cognitive basis for understanding how easily recalled information can disproportionately influence judgment. Kunda (1990) further supports this by showing how motivated reasoning shapes the interpretation and acceptance of information, especially when it aligns with existing beliefs. Lichtenstein and Slovic (2006) illustrate how preferences are constructed in real time, often shaped by salient narratives rather than objective data. Shiller’s (2000) analysis of financial markets exemplifies how repeated media narratives can fuel economic bubbles—an applied form of the cascade. Finally, Wilson and Gilbert (2005) highlight how affective forecasting errors can amplify the emotional salience of repeated messages.

Trivia Example: The availability cascade can be observed in the context of public knowledge quizzes. When a particular answer—such as “Einstein” in response to a question about a famous physicist—is repeatedly mentioned or endorsed by participants, its perceived correctness increases, regardless of its factual accuracy. This repetition amplifies the answer’s cognitive availability, leading others to adopt it without independent verification. Over time, the initial suggestion gains momentum and becomes widely accepted within the group, not because of its validity but due to its frequent exposure. This phenomenon exemplifies how repeated information can shape collective beliefs and judgments, a core mechanism of the availability cascade.

Selected References

Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480-498.

Lichtenstein, S., & Slovic, P. (2006). The construction of preference. Cambridge University Press.

Shiller, R. J. (2000). Irrational exuberance. Princeton University Press.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Wilson, T. D., & Gilbert, D. T. (2005). Affective forecasting: Knowing what to want. Current Directions in Psychological Science, 14(3), 131-134.

Business Example: The availability cascade appears in consumer 417

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BANDWAGON EFFECT The tendency to do (or believe) things because many other people do (or believe) the same. Related to groupthink and herd behavior.

“I think I look good.”

“But you never wear dresses. And heels? That’s new.”

“Everyone’s wearing them. I went shopping with friends yesterday—we all got dresses.”

“And the shoes?”

“Not everyone has these. They’re Louboutins. I saved for two years. They’re in all the magazines. A bit tight, but worth it.”

“And the glasses? You don’t need glasses.”

“They’re fashion glasses. No prescription—just stylish. They make me look smarter.”

Rooney sighed. “So basically, you saw others wearing it and followed along.”

Ellie frowned. “What’s wrong with that?”

“Nothing… except it’s not you. You look uncomfortable.”

Ellie tried to walk, wobbled, and fell.

“See? You can’t even walk in them. And you’re applying for a web design internship.

Everyone there wears sneakers.”

“So what do I do now?”

“Go change. Just be yourself.”

Minutes later, Ellie came back in jeans, sneakers, and a blue jacket.

“Perfect,” Rooney smiled. “Don’t forget your portfolio.”

That evening, Ellie called. “They picked me! You were right. You have to be yourself… I returned everything.”

“Everything?”

“Except the shoes. They’ll stretch. I’m sure.”

“Ellie… they’re too small.”

"So what? All the models wear them!"

“What’s this?” Rooney looked at Ellie in surprise “What’s wrong?” she asked, checking herself over.

“You’re going to the interview like that?”

“Yeah, why not?”

“In a dress and heels?”

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and Huawei, whose success also reflects consumers’ desire to align with groups that value cutting-edge tech. The bandwagon effect thus plays a central role in shaping tech markets and brand loyalty.

About: The bandwagon effect is a cognitive bias where individuals adopt behaviors or beliefs simply because they see others doing the same. As a form of conformity bias, it drives people to align with the majority—even without fully understanding or agreeing with the choice. The term originates from early 20th-century politics, where riding a bandwagon signaled popular support. This effect is amplified by social proof and is common in areas like politics, consumer trends, and social movements. It can spread inaccurate information as people conform to what seems socially accepted, especially in uncertain situations. The bias reflects a fundamental human need for acceptance, often overriding independent judgment.

Replicability: The bandwagon effect has been widely replicated across contexts such as voting, consumer choice, and group decision-making. Bikhchandani, et al.

(1992) provided a theoretical framework through the concept of informational cascades, showing how early adopters can disproportionately influence group decisions. Cialdini (2009) reinforced this with empirical evidence on social proof. Experimental studies (e.g., Salganik, et al., 2006) confirmed that popularity can emerge independently of quality, validating the effect in artificial cultural markets. Market-focused research (e.g., Dubé et al., 2010; Goldenberg et al., 2001) further demonstrated how network effects and emotional cues contribute to product adoption patterns consistent with bandwagon dynamics. Bindra et al. (2022) synthesized decades of research, affirming the robustness of the effect.

Trivia Example: A clear example of the bandwagon effect is the rise of social media trends like the “Ice Bucket Challenge.” Initially launched to raise funds for ALS research, the challenge went viral on platforms like Facebook (currently, Meta) and Twitter (currently, X) in the mid-2010s. As celebrities and public figures joined in, participation skyrocketed—not always due to strong support for the cause, but because it became the social “thing to do.” The widespread sharing created a cascade of imitation, illustrating how the bandwagon effect can drive mass behavior more through popularity than personal conviction.

Selected References

Bindra, S., Sharma, D., Parameswar, N., Dhir, S., & Paul, J. (2022).

Bandwagon effect revisited: A systematic review to develop future research agenda. Journal of Business Research, 143, 305-317.

Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 100(5), 992–1026.

Cialdini, R. B. (2009). Influence: The psychology of persuasion.

Harper Business.

Dube, L., Hitsch, G. J., & Chintagunta, P. K. (2010). Tipping and concentration in markets with indirect network effects.

Marketing Science, 29(2), 216-234.

Goldenberg, J., Lehmann, D. R., & Mazursky, D. (2001). The idea itself and the circumstances of its emergence as predictors of new product success. Management Science, 47(1), 69–84.

Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006). Experimental study of inequality and unpredictability in an artificial cultural market. Science, 311(5762), 854-856.

Simonson, I., & Tversky, A. (1992). Choice in context: Tradeoff contrast and extremity bias. Journal of Marketing Research, 29(3), 281-295.

Business Example: The bandwagon effect is commonly seen in consumer behavior, especially in the adoption of new technologies. A key example is the rise of the iPhone. After its 2007 launch, early adopters helped build its reputation as a must-have device.

As more people bought iPhones, others followed suit—often driven by a desire not to be left behind. This created a cascade, where popularity fueled further adoption. The trend extended to other smartphone brands like Samsung, Google, 419

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GROUP ATTRIBUTION ERROR The biased belief that the characteristics or beliefs of some group members are representative of the entire group.

"Are you planning to celebrate your birthday?"

Rooney asked. He knew Ellie's birthday was coming up in a week.

"Of course, I am," Ellie nodded, "I thought about inviting a few people over: you, Kristen, George." "Not him, though!" "Why not?"

"First, if you invite him, he'll bring all his brothers along. Second, he's crazy, and so is his whole family."

"Where did you get that from?"

"Recently, at Linda's party, he nearly set her apartment on fire. Can you believe that he tried to start a bonfire right in Linda's hallway during the party? Haven't you heard?"

"Firstly, you weren't there, so you don't know exactly what happened. Spreading rumors is unworthy. Someone made up nonsense, and you believed it. Secondly, even if it's true, why do you assume George's entire family would behave like that?"

"I've heard it from many people," Rooney said confidently.

"Even more reason – see, you're just passing on hearsay about George and his family. You heard it, but that doesn't make it a fact.

You're accusing people without any proof!"

"Fact or not, I've warned you!"

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on group-based attributions, it can lead to ineffective management decisions. For example, if a marketing team is blamed for a failed campaign due to one member’s poor performance, the entire team may be seen as lacking, even though the majority of the team members performed well. This type of bias in business contexts often stifles innovation and creates a culture of distrust within organizations.

By addressing this bias through diverse team interactions and leadership strategies that emphasize individual strengths, companies can encourage more accurate perceptions and make more informed, fair decisions (e.g., Sinclair and Kunda, 2000).

About: The group attribution error is the tendency to infer that an individual’s behavior reflects the characteristics of their entire group, overlooking within-group diversity. This bias leads to overgeneralizations, such as assuming one political party member’s actions represent the whole party. Mullen et al. (1985) found that people generalize more when they have limited knowledge of the group, especially with perceived outgroups like political factions, racial groups, or corporate teams. This bias reinforces stereotypes and social divisions. Yzerbyt et al.

(1995) linked it to the outgroup homogeneity effect, where outgroup members are seen as more alike than they actually are.

Replicability: The group attribution error has been consistently replicated across social and organizational contexts. This robust bias influences group dynamics and interpersonal judgments, though its strength varies with factors like group identity, contact frequency, and perceived threat.

Studies show that direct, positive interactions with outgroup members reduce the bias. Yzerbyt et al. (1995) noted the effect is strongest when group identities are rigid and personal contact is limited. The error’s replicability highlights the need to promote intergroup understanding and reduce bias in both corporate and societal decision-making.

Trivia Example: An example of the group attribution error is seen in public reactions to corporate scandals. When a high-profile executive, such as a CEO, behaves unethically, the public often assumes the entire company shares those values. This occurred with Uber in the late 2010s, where executive misconduct led to broader assumptions about company culture. Media coverage tends to amplify this bias by portraying individual actions as representative of the whole organization or industry. Mullen et al. (1985) found that people often misattribute individual behaviors to entire groups, overlooking internal diversity. This oversimplification fosters mistrust and obscures the complexity of organizational dynamics.

Selected References

Mullen, B., Johnson, C., & Kunkel, A. (1985). The group attribution error: A meta- analytic review. Personality and Social Psychology Bulletin, 11(3), 361-372.

Ross, L., & Nisbett, R. E. (1991). The person and the situation: Perspectives of social psychology. McGraw-Hill.

Sinclair, L., & Kunda, Z. (2000). Motivated stereotyping of women: She’s fine if she praised me but incompetent if she criticized me. Personality and Social Psychology Bulletin, 26(11), 1329–1342.

Yzerbyt, V. Y., Leyens, J.-P., & Schadron, G. (1995). Stereotypes and group behavior. European Review of Social Psychology, 6(1), 1-40.

Business Example: In a corporate setting, if one member of a team consistently underperforms, managers might wrongly assume that the entire department shares similar deficiencies. This can affect hiring, promotions, and team structure decisions, as managers generalize one person’s behavior to a whole group. Studies show that when people rely 421

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GROUPTHINK The practice of thinking or making decisions as a group in a way that discourages creativity or individual responsibility. photos in the dark without one is a hassle!"

"Interesting. Sure, no problem. Come in," Rooney replied. "But what's with the costume?"

"It's a forget-me-not costume. What do you think? Do you like my petal crown? I spent almost a week making it!"

"It's not the costume itself that worries me.

Don't you think it's a bit much to go outside in a light, short, sleeveless dress?

It's not warm out, and the wind is strong!

You need warmer clothes, not just a tripod."

"I thought about that," Ellie looked herself over from head to toe. "But you see, my friends and I agreed to all dress up as flowers. We'll watch the fireworks first and then have a flower-themed party."

"Brilliant!" Rooney said sarcastically. "A floral party for New Year's. Dressing up as flowers! Great! Why am I not surprised? It wouldn't be complete without your 'girls', obviously. I've never heard anything more ridiculous!"

"It's not ridiculous at all!" Ellie was offended.

"Here's the deal, take the tripod, but I'm not letting you go without warm clothes! You might not care because your 'girls' are more important, but I'm sure your parents will thank me later. Wait here. I'll ask my mom for her light down jacket. It's green, so it won't clash with your 'forget-me-not' theme. You'll be a forget- me-not on a green stem," with those words, Rooney disappeared down the corridor.

”Hey! I thought you were going to watch the New Year's fireworks with your friends," Rooney said in surprise, seeing Ellie at the door.

"Yeah, I am. Can I borrow your tripod? I want to take photos with my camera, but I can't find my tripod. And you know, taking 422

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and-mortar model. This reluctance reflected groupthink: executives were hesitant to challenge the existing strategy, and a shared belief in the viability of physical rentals led to complacency.

The company’s cohesion discouraged dissent, ultimately resulting in missed opportunities and business collapse (e.g., Hirschman, 2016).

About: Groupthink is a psychological phenomenon where a group reaches consensus without critically evaluating alternatives, prioritizing harmony over sound decision-making. In the early work by Irving Janis (1972), groupthink arises in cohesive in-groups, especially under strong leadership or high-stakes conditions. It suppresses dissent and promotes conformity, often leading to poor judgments and overlooked alternatives. Janis cited events like the Bay of Pigs invasion as classic examples, where dissenting views were ignored, resulting in disastrous outcomes. Groupthink can affect teams and organizations alike, as social pressure discourages individuals from speaking out, reinforcing flawed decisions and potentially leading to either paralysis or rash actions.

Replicability: The replicability of groupthink research has been a subject of ongoing scholarly interest, s. Janis’s seminal works (1972, 1982) laid the groundwork for understanding groupthink as a psychological phenomenon influencing policy decisions, providing detailed case studies that have been widely cited and critiqued. Studies like Mullen and Johnson (1993) extended this foundation through a meta-analytic review, offering quantitative support for the theory’s core propositions and highlighting conditions under which groupthink is more likely to occur. Esser (1998) further evaluated the robustness of groupthink research over a 25-year period, while more recent literature (e.g. Hirschman’s (2016) offered alternative mechanisms of dissent and conformity within organizations. Collectively, these works demonstrate the importance of methodological transparency and theoretical refinement in ensuring the replicability and continued relevance of groupthink research.

Trivia Example: A well-known example of groupthink is the 1986 Space Shuttle Challenger disaster. Despite warnings from some engineers about the risks of launching in cold weather, NASA management proceeded with the launch. Groupthink contributed to this tragedy, as the desire to stay on schedule and achieve success led to the suppression of dissent and the dismissal of critical safety concerns. Esser (1998) emphasized how group cohesion in high-pressure situations can compel members to conform rather than speak out. The Challenger case highlights the dangers of prioritizing consensus over critical evaluation and demonstrates the need for environments that welcome dissenting views, especially in high-stakes decisions.

Selected References

Esser, J. K. (1998). Alive and well after 25 years: A review of groupthink research. Organizational Behavior and Human Decision Processes, 73(2-3), 116-141.

Hirschman, A. O. (2016). Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States. Harvard University Press.

Janis, I. L. (1972). Victims of Groupthink: A Psychological Study of Policy Decisions and Fiascoes. Houghton Mifflin.

Janis, I. L. (1982). Groupthink: Psychological Studies of Policy Decisions and Fiascoes. Houghton Mifflin.

Mullen, B., & Johnson, C. (1993). Groupthink: A review of the theory. Psychological Bulletin, 113(1), 21-38.

Business Example: Groupthink can severely hinder innovation, as seen in Blockbuster’s failure to adapt to the rise of digital streaming. In the early 2000s, despite awareness of growing interest in services like Netflix, CEO John Antioco and his leadership team resisted change, prioritizing their brick423

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HERDING Individuals in a group can act collectively without centralized direction.

"Listen," Rooney said, eyeing Ellie's purchases, "why do you need 15 iPhone cases? Even if you change them every day of the week, you still won't be able to use them all.

There are only 7 days in a week."

"You don't understand," Ellie declared confidently, "first of all, there was a sale on these cases; secondly, I need all of them; and thirdly – there was a huge queue! It was a struggle to get them!"

"So basically, everyone was rushing to get cases, and you followed suit. You know, one case would have been enough for you."

"You don't understand anything about cases or fashion. I'm going to use them all!"

"We'll see…"

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1990s, investors poured money into internetrelated companies, often without understanding their business models or profitability. As more people invested, prices soared, attracting even more investors who feared missing out. This collective behavior inflated valuations far beyond fundamentals, eventually leading to a market crash. The herding dynamic here was driven by social proof and fear of regret, rather than rational analysis.

Replicability: Alevy et al. (2014) found herding behavior to be common in experimental markets, where individuals follow others’ choices despite having private information that could yield better outcomes. This tendency is also seen in realworld markets, such as during the 2008 financial crisis, where investors followed trends without independent analysis (e.g., Shiller, 2016). Herding can be reduced by offering more information or incentives for independent decision-making (e.g., Solnick and Hemenway, 1998). These patterns across domains show that herding is a robust phenomenon, though its strength varies depending on social influence, available information, and individuals’ confidence in their own judgment (Bikhchandani et al., 1992).

Selected References

About: Herding bias occurs when individuals make decisions based on others’ actions rather than their own analysis, often in uncertain situations.

People assume others possess better information and follow their lead instead of conducting independent research. This bias is common in financial markets, consumer trends, and political behavior. For example, during speculative bubbles, like the dot-com boom, investors purchased overvalued stocks simply because others were doing the same. Herding can result in collective inefficiencies and bubbles, as people prioritize group behavior or fear of missing out over critical thinking. Research shows the bias is stronger in low-cohesion groups or when individuals lack confidence. Though it may offer psychological security, herding often leads to poor group decisions that individuals might avoid if acting alone. It is closely linked to social influence, conformity, and informational cascades (e.g., Bikhchandani et al., 1992).

Trivia Example: Imagine you are walking down a busy street looking for a place to eat. You pass two restaurants side by side—one is nearly full, and the other is empty. Even without knowing anything about the food or service, you are more likely to choose the crowded one. This is a classic example of herding behavior: people assume that if others are choosing a particular option, it must be the better one. The decision is influenced more by the actions of others than by personal evaluation, often leading to a self-reinforcing cycle of popularity.

Alevy, J. E., List, J. A., & Soldner, M. (2014). The effect of information on herding behavior in experimental markets. Economic Inquiry, 52(1), 138-150.

Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 100(5), 992-1026.

Shiller, R. J. (2016). Irrational exuberance (3rd ed.). Princeton University Press.

Solnick, S. J., & Hemenway, D. (1998). The importance of relative income: The case of lottery winners. Journal of Economic Behavior & Organization, 34(1), 69-80.

Veblen, T. (1899). The Theory of the Leisure Class. Macmillan.

Business Example: In financial markets, herding is frequently observed during stock market bubbles. For instance, during the dot-com boom of the late

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INGROUP BIAS The tendency for people to give preferential treatment to others they perceive to be members of their own groups.

“I'm trying to decide who to pick for my tennis team. We have a training camp coming up, and this time it's going to be a team competition. I need to form a team of four people.”

“What's the problem then?” Ellie inquired, her interest piqued.

“Well, I’ve already found two players, and obviously, I’ll be playing on my own team.

But we need a fourth player. Usually, I play with Emily, but she went hiking in the mountains over the weekend and broke her arm. Now, it’s uncertain when she’ll be back for training.”

“Why don’t you just pick the strongest player available who doesn’t have a team yet?”

“The strongest? I guess that would be Chen. But he’s not an option.”

“Why not?”

“I don’t know. We usually play on opposing teams. Plus, he’s a Novak Djokovic fan, and I’m Roger Federer fan.”

“You’re serious?” Ellie exclaimed, clearly frustrated. “Listen to yourself! So, you're saying you won’t pick a good player just because he usually plays against you and supports a different tennis player? What does that even matter? Firstly, you're typically assigned to teams randomly; and secondly, why should it matter who someone roots for? That’s just ridiculous!”

“You’re right,” Rooney conceded. “It’s silly. I’ll give him a call.”

“What are you thinking about?” Ellie asked.

Rooney had been sitting on the bench for several minutes, lost in thought and nodding absently whenever Ellie spoke to him.

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About: Ingroup bias, also known as ingroup favoritism, refers to the tendency to favor members of one’s own group over those in other groups. This bias is deeply rooted in social identity theory, which posits that people derive part of their identity and self-esteem from the groups they belong to (e.g., Tajfel and Turner, 1979). Ingroup bias manifests in various ways, such as preferential treatment, positive evaluations, and higher levels of trust for ingroup members. Research shows that this bias is not limited to arbitrary groups like sports teams or work groups but extends to demographic categories such as race, nationality, and political affiliation. One of the most significant implications of ingroup bias is its contribution to social division, reinforcing stereotypes, and fostering intergroup conflict.

For instance, ingroup bias can play a pivotal role in the polarization of political parties, where individuals show preferential treatment for their political group while dismissing the views or abilities of the opposing group. The persistence of ingroup bias suggests that it is a powerful social mechanism that influences behavior, even in the absence of direct competition or animosity between groups. As such, ingroup bias is a key factor in understanding prejudice, discrimination, and the dynamics of group behavior.

Business Example: In the workplace, ingroup bias appears in team dynamics and managerial decisions. Managers often favor employees from their own department or those who share similar backgrounds. Ilies, Judge, and Wagner (2006) found that ingroup members received more mentoring and positive evaluations—even with equivalent performance. This bias can limit diversity, hinder innovation, and foster exclusion, negatively impacting collaboration and organizational culture.

Replicability: Ingroup bias is highly replicable across contexts.

Tajfel’s (1970) minimal group experiments showed favoritism even in randomly assigned groups. Mullen et al. (1992) confirmed this in a meta-analysis spanning both real and artificial groups. Organizational research (e.g., Brewer, 1999) continues to observe this bias in hiring, evaluations, and teamwork. While its intensity may vary by culture or context (e.g., Kershaw, 2021), ingroup bias consistently emerges—even without tangible stakes—and is especially strong when group identity feels threatened.

Selected References

Brewer, M. B. (1999). The psychology of prejudice: Ingroup love and outgroup hate? Journal of Social Issues, 55(3), 429– 444.

Kershaw, C., Rast III, D. E., Hogg, M. A., & van Knippenberg, D. (2021). Battling ingroup bias with effective intergroup leadership. British Journal of Social Psychology, 60(3), 765–785 Mullen, B., Brown, R., & Smith, C. (1992). Ingroup bias as a function of salience, relevance, and status: An integration. European Journal of Social Psychology, 22(2), 103–122.

Tajfel, H. (1970). Experiments in intergroup discrimination. Scientific American, 223(5), 96–102.

Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G. Austin & S. Worchel (Eds.), The social psychology of intergroup relations (pp.

33–47). Monterey, CA: Brooks/Cole.

Trivia Example: One example of ingroup bias is the US–Canada rivalry in international ice hockey. During the 2010 Winter Olympics gold medal game, Canadian fans viewed their team’s win as a national triumph, while US fans blamed isolated errors despite similar performance stats. Both groups interpreted events in ways that reflected positively on their own team, showing how group loyalty distorts judgment and sustains ingroup bias.

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OUTGROUP HOMOGENEITY BIAS Individuals see members of their own group as being more varied than members of other groups. empty chip packets were strewn across the floor. The kitchen sink was piled high with dirty dishes.

Ellie, carrying a tray of dirty glasses, stopped and sighed: "You see, Mom's gone for a week, and Dad's brothers and their sons came over. As a result, they've been watching TV and playing video games all day, and I have to clean up this pigsty. They went paintballing this morning and won't be back until the evening."

"Why don't they clean up after themselves? They should be made to wash their own mess," Rooney glanced at the dirty kitchen.

"Yeah right! Like they'd clean! I know you guys, all men are the same. Women would never let it get like this!"

"Hey, don't generalize! What's this talk about 'all men are the same, and women are different'... That's nonsense! There are plenty of messy women too."

"You're right," Ellie said guiltily. "Sorry, I just blurted it out without thinking. I'm just tired of all this," she looked around, "there I go again, spending half a day cleaning up."

"Here's what we'll do," Rooney said, taking the tray from Ellie. "I'll help you now, but afterwards, we're going to a café and then to the movies. In the evening, I'll talk to your cousins. You're not cleaning up after them anymore. They can do it themselves."

"Thank you, Rooney," Ellie said, sitting down on a chair.

"Wow, what a mess!" Rooney looked around, astonished by the chaos at Ellie's house.

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during mergers and acquisitions. Employees from the acquiring firm may stereotype staff from the target company as uniform in behavior or mindset, assuming they are resistant to change or lack innovation. Such assumptions, based solely on group identity, can impede post-merger integration and collaboration. These stereotypes cause friction, as the target company’s employees are frequently perceived as “the other.”

Addressing this bias requires organizations to highlight individual differences, encourage intergroup dialogue, and actively challenge overgeneralizations (e.g., Park and Rothbart, 1982).

About: Outgroup homogeneity bias is the tendency to see members of an outgroup as more alike than they are, while viewing one’s own ingroup as diverse. This bias arises from cognitive simplification—grouping others to make social environments easier to navigate. People often apply stereotypes to outgroups, assuming uniformity in traits and behaviors, while recognizing variation within their own group.

Hamilton and Gifford (1976) showed that individuals more readily attributed negative behaviors to minority group members and overlooked their diversity, while evaluating ingroup behavior more positively. This bias appears in contexts like race, politics, and hiring, where it shapes attitudes, reinforces prejudice, and influences decisions such as voting and consumer behavior.

Replicability: Hamilton and Gifford (1976) found that participants attributed more negative behaviors to a minority group and saw that group as less behaviorally diverse. Subsequent replications confirmed similar effects across racial, ethnic, and political domains (Dunham et al., 2011). In workplace contexts, Vandello and Cohen (1999) showed that outgroup candidates were often assumed to lack traits valued by the ingroup, even when such traits varied. Whether in lab studies or real-world scenarios, the persistence of this bias demonstrates its influence on intergroup dynamics.

Trivia Example: One example of outgroup homogeneity bias is how people tend to view fans of rival sports teams. For instance, a fan of a football team may perceive all supporters of the opposing team as overly aggressive or obnoxious, attributing negative stereotypes to them without considering the differences within the group. In contrast, when reflecting on their own team’s fan base, they may acknowledge a wide range of personalities, behaviors, and attitudes. This bias helps to explain why sports rivalries can often escalate into hostile encounters, as individuals focus on perceived uniformity within the outgroup while overlooking the diversity and individuality within their own group. This perception leads to polarized thinking, where a fan of one team may exaggerate the “otherness” of their rivals, which reinforces divisiveness and antagonism between groups.

Selected References

Dunham, Y., Baron, A. S., & Carey, S. (2011). The development of implicit intergroup attitudes. Child Development, 82(3), 793–811.

Hamilton, D. L., & Gifford, R. K. (1976). Illusory correlation in interpersonal perception: A cognitive basis of stereotypic judgments. Journal of Experimental Social Psychology, 12(4), 392–407.

Park, B., & Rothbart, M. (1982). Perception of out-group homogeneity and levels of social categorization: Memory for the subordinate attributes of in-group and out-group members. Journal of Personality and Social Psychology, 42(6), 1051.

Vandello, J. A., & Cohen, D. (1999). Patterns of conflict: Intergroup relations in the Southern United States. Journal of Personality and Social Psychology, 77(2), 327-341.

Business Example: Outgroup homogeneity bias often surfaces 429

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SOCIAL COMPARISON BIAS The tendency, when making decisions, to favor potential candidates who don't compete with one's own particular strengths.

"Amanda was really good today," Rooney said. "I don't know much about theater, but I enjoyed it. Thanks for dragging me to that play. I've never been to an amateur theater before. I liked it."

"I don't know what there was to like. And why does everyone fuss over Amanda? 'Amanda this, Amanda that.' She's so annoying," grumbled Ellie.

Rooney smiled: "You're being too hard on her. She did a great job.

But I'm sure your lead role will be even better! By the way, when is the premiere of your play?"

Ellie brightened up: "In two weeks! Hey, I haven't shown you my costume yet! It's absolutely amazing!"

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undesirable position or with less experience, boosting their confidence and making them feel more secure in their role. This bias can influence workplace dynamics, creating feelings of resentment, frustration, or excessive selfcriticism, especially when people are unaware of the subtle ways in which they engage in these comparisons. Organizations need to recognize how social comparison can impact morale and productivity, especially when the focus shifts from internal growth and development to externally driven competition and comparison (e.g., Lee, 2014).

About: Social comparison bias refers to the tendency to judge one’s own abilities or status by comparing with others. As described in Festinger’s Social Comparison Theory (1954), people seek validation and self-assessment through comparison, often resulting in distortions.

Upward comparisons—judging oneself against someone perceived as superior—can cause envy or low self-esteem. Downward comparisons— viewing others as worse off—may inflate selfworth temporarily. This bias is amplified by social media, where highly curated content skews reality and heightens dissatisfaction.

Replicability: Social comparison bias has been robustly replicated across psychological and organizational studies. Research by Buunk and Gibbons (2007) and Fardouly et al. (2015) demonstrates its influence on self-esteem, especially in digital environments. In workplace contexts, Festinger’s early work and subsequent studies confirm its effects on motivation and job satisfaction (e.g., Lee, 2014). Despite variation across individuals and settings, the phenomenon remains a common predictor of behavior and emotional response.

Trivia Example: On platforms like Instagram, people routinely compare their lives to idealized portrayals of others’ experiences. A person might feel disheartened by seeing lavish vacations or career milestones online, even though these glimpses are curated. Conversely, viewing others’ misfortunes may temporarily boost self-image.

This comparison-driven loop can distort one’s perception of both self and others, with emotional consequences that are often underestimated.

Business Example: Social comparison bias frequently plays out in workplace environments.

Employees often compare their salary, job status, or career progress to that of their colleagues. For instance, an employee may feel disillusioned when they perceive a colleague receiving a promotion while they have been overlooked, even if the promotion is based on different qualifications or achievements. On the other hand, downward social comparison can occur when employees find someone in a more

Selected References

Buunk, B. P., & Gibbons, F. X. (2007). Social comparison and health: A cognitive perspective. In A. S. R. Manstead, N. H. Frijda, & A. Fischer (Eds.), Feelings and emotions: The Amsterdam symposium (pp. 215–234). Cambridge University Press.

Fardouly, J., Diedrichs, P. C., Vartanian, L. R., & Halliwell, E. (2015). Social comparisons on social media: The impact of Facebook on young women’s body image concerns and mood. Body Image, 13, 38–45.

Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7(2), 117–140.

Lee, S. Y. (2014). Social comparison, self-esteem, and job satisfaction. Journal of Organizational Behavior, 35(5), 669–690.

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STEREOTYPING Expecting a member of a group to have certain characteristics without having actual information about that individual.

"How can you not see it?" Ellie insisted. "Your entire exhibition stand needs to be redone!"

"And why's that?" Rooney asked, puzzled.

"Because the girl in the pink dress and the boy in blue shorts are just blatant stereotypes!

You can't use that for your poster!"

"I don't understand. What's the problem? It shows them building a robot together.

Where are the stereotypes in that?"

"The stereotypes are exactly that – pink for girls and blue for boys. That's so last century!"

"So, what do you suggest?" Rooney shook his head, concern evident in his voice. "The exhibition is in two days!"

"Let me redraw it all for you, without any gender biases!"

"Alright, I'm open to that. I never thought the poster was stereotypical."

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qualified men in male-dominated fields, and racial stereotypes similarly disadvantage minority candidates. For example, Pogrebna et al. (2024) found that intersectional racial and gender biases hinder the advancement of minority women in leadership roles by reinforcing persistent stereotypes. To address such biases, some companies, including Google and Microsoft, have explored blind hiring practices—removing identifying information from resumes to promote merit-based evaluation. These initiatives aim to reduce bias and enhance workforce diversity.

About: Stereotyping is a cognitive bias where individuals attribute traits to people based solely on group membership, without direct evidence (e.g., Davine, 1989). It stems from unconscious mental shortcuts shaped by societal norms, media, and culture. While it simplifies decisionmaking, stereotyping often leads to inaccurate or unfair assumptions. Common examples include assumptions based on race, gender, age, or profession, which can influence hiring, legal outcomes, and educational assessments. In workplaces, stereotypes affect how competence and potential are perceived, contributing to discrimination and limited opportunities. The bias is particularly strong when people lack exposure to diversity and rely on generalizations (e.g., Greenwalk and Banaji, 1995). Reducing stereotyping requires awareness and increased interaction with diverse groups. These efforts help challenge assumptions and promote fairer, more individualized judgments.

Replicability: In the early work on stereotypes, Devine (1989) highlighted the automatic and unconscious nature of stereotyping, demonstrating that even well-intentioned individuals can harbor stereotypes. Further studies have replicated this finding, showing that stereotypes are pervasive across cultures and social settings. A study by Hewstone et al. (2002) demonstrates that stereotypes influence behavior in a variety of social contexts, including intergroup interactions, hiring decisions, and even jury verdicts. More recently, research into implicit biases has confirmed that people are often unaware of the stereotypes they hold, which can lead to discrimination despite consciously espousing egalitarian values (Greenwald and Banaji, 1995).

Trivia Example: Stereotyping often shapes how people perceive others based on superficial traits. For instance, individuals wearing hoodies in urban settings may be unfairly viewed as suspicious or threatening, especially if they belong to a minority group. This reaction stems not from personal experience but from cultural stereotypes perpetuated by media and social narratives. Such biases can influence behavior— like crossing the street or clutching belongings— despite no objective threat. These automatic judgments reflect how stereotypes distort perception and reinforce social divisions, even in routine interactions.

Selected References

Pogrebna, G., Angelopoulos, S., Motsi-Omoijiade, I., Kharlamov, A., & Tkachenko, N. (2024). The impact of intersectional racial and gender biases on minority female leadership over two centuries. Scientific reports, 14(1), 111.

Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5–18.

Greenwald, A. G., & Banaji, M. R. (1995). Implicit social cognition: Attitudes, self-esteem, and stereotypes. Psychological Review, 102(1), 4–27.

Hewstone, M., Rubin, M., & Willis, H. (2002). Intergroup bias. Annual Review of Psychology, 53, 575–604.

Business Example: In professional settings, stereotyping can significantly influence hiring and evaluation decisions. Research shows that women are often perceived as less competent than equally 433

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THIRD-PERSON EFFECT Belief that mass communicated media messages have a greater effect on others than on themselves.

"Hey, I see you're in a great mood today," Rooney said, noticing Ellie's smile. "What's got you so cheerful?"

"Hey, come in," Ellie replied, still smiling as she closed the door behind Rooney.

"Did you see Veronica?"

"Yeah, I just ran into her on my way here. Why?" "Oh, nothing. She's such a victim of adverts! She came to show off her new 'Versace' bag. She saw it on TV yesterday and bought it today.

She's becoming like a parrot – all branded stuff, but none of it matches! Like Gucci jeans, a Cavalli sweater, but looking like a hot mess. All different colours and completely mismatched combinations. She needs to watch less advertising."

"Look who's talking!" Rooney smiled and waved his hand dismissively.

"What do you mean? What are you talking about?" Ellie's expression changed as she stared intently at Rooney.

"And who bought new 'Converse' shoes after seeing an ad? And that 'Pandora' bracelet?

So, it's not clear who the real 'victim of advertising' is here."

"That's not true!" Ellie retorted, feeling offended.

"Okay, okay, I was just joking. I'm here for you.

Are you ready?" Rooney chuckled and, with a smile, handed Ellie her 'Prada' jacket.

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those featuring personalization or celebrity endorsements—affect others more than themselves. A notable example is Coca-Cola’s “Share a Coke” campaign, which featured bottles labeled with popular names. While many consumers acknowledged that such personalization might prompt others to buy the product, they denied being influenced themselves. This perception shapes marketing strategies, with advertisers targeting supposedly “vulnerable” groups, assuming that others—not the primary audience—are more easily persuaded. Ironically, this belief can increase receptivity among the actual audience, as they engage with the campaign while distancing themselves from its influence.

About: The third-person effect is a cognitive bias in which individuals believe others are more susceptible to media messages than they are themselves (e.g., Davison, 1983).

The phenomenon reflects a tendency to view oneself as less influenced by persuasive or controversial content—such as political ads, violent programming, or misleading news—while assuming others are more easily swayed. This perception often leads to support for censorship or media regulation, based on the belief that “other people” need protection from harmful content. A major factor driving this bias is psychological distance: people tend to see themselves as critical thinkers but perceive the general public as more impressionable.

Replicability: The third-person effect is consistently replicated.

Since Davison (1983), studies have repeatedly shown that individuals see themselves as less influenced by media than others. Price and Tewksbury (1997) demonstrated it in reactions to violent TV content. Kim and McLeod (2009) further confirmed the effect, showing it cuts across cultures and age groups. Though its strength varies—affected by media type, emotional appeal, and individual media literacy— the third-person effect remains a reliable and well-established cognitive bias with significant implications for advertising and policy.

Trivia Example: During election seasons, voters often deny being influenced by political ads while believing others are more susceptible. Kim and McLeod (2009) found that individuals thought such ads would sway less politically informed people, but not themselves. Similarly, Price and Tewksbury (1997) showed that support for regulating media content—like TV violence or political ads— stemmed from the belief that others were more easily influenced. This bias was stronger when participants were less familiar with or interested in the content. The third-person effect is most pronounced when individuals view themselves as more informed or media-savvy, leading them to overestimate their resistance to persuasive messages.

Selected References

Davison, W. P. (1983). The third-person effect in communication.

Public Opinion Quarterly, 47(1), 1-15.

Kim, Y., & McLeod, D. M. (2009). The third-person effect and public opinion: The role of perceived influence on others and perceived exposure. Journal of Broadcasting & Electronic Media, 53(4), 486–504.

Price, V., & Tewksbury, D. (1997). News values and public opinion: A theoretical account of media priming and framing. Journal of Communication, 47(1), 48–67.

Business Example: The third-person effect is evident in consumer responses to advertising, where individuals often believe that persuasive messages—especially

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WOMEN ARE WONDERFUL EFFECT A tendency to associate more positive attributes with women than with men.

"Can you show me the new photos?" Ellie scooted closer to Rooney and looked at his laptop screen.

"Yeah, sure," Rooney replied, "I was actually doing portraits and interior photos last week. Here – what do you think?"

"They're beautiful," Ellie observed, scrutinizing each snapshot. "But why are there only girls in these photos?"

"These are for a boutique owned by a friend of my mom’s."

"I figured that out, but does she only sell women's clothing?"

"Not exactly. She sells men's clothing too, but people generally respond more positively to women than men in advertisements.

You know that – it’s the same reason why women are predominantly featured in ad campaigns."

Ellie sighed: "You’re right, but I'd like to see more inclusive advertising campaigns with a variety of people…”

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interpersonal qualities such as warmth and empathy. This reflects a phenomenon known as role incongruity, where stereotypical expectations of women conflict with traits associated with leadership. The effect suggests that people tend to perceive women as kinder and more approachable, but these perceptions may not translate into equal opportunities or respect in competitive, leadership-heavy environments, ultimately affecting women’s career advancement. This bias can also be seen in social media discussions, where women are often lauded for their empathy and compassion, but when they exhibit assertiveness or authority, they may face criticism or be perceived as “bossy.”

About: The “women are wonderful” effect is a cognitive bias where women are viewed more favorably than men in traits like warmth, kindness, and nurturing—reflecting traditional gender roles tied to caregiving and emotional labor. Women are often perceived as more compassionate and selfless, but this also imposes pressure to conform to these ideals, reinforcing stereotypes.

Coined by Eagly and Mladinic (1994), the effect highlights how women are seen as more moral and kind, while men are viewed as more competent in leadership and intellectual roles.

This bias shapes media, workplace, and interpersonal dynamics, often elevating women’s warmth while downplaying their authority or competence.

Replicability: The “women are wonderful” effect has been widely replicated across cultures. Eagly and Mladinic (1994) found that women were consistently rated more favorably for warmth and kindness in both North America and Europe.

While these traits are advantageous in fields like healthcare or education, they can be seen as liabilities in business or politics, where authority is more valued. Rudman and Glick (1999) extended this effect to organizational settings, confirming its presence across gender roles.

Though the effect is robust, its strength varies by societal and professional context—being less pronounced in more egalitarian cultures. It also intersects with other phenomena, such as the “likability penalty,” where assertive women face backlash for defying nurturing stereotypes.

Trivia Example: The “women are wonderful” effect can be seen in how people often expect women to be more nurturing and emotionally supportive than men.

For example, in a classroom or workplace setting, if someone is upset or needs help, people are more likely to turn to a female colleague or classmate for comfort or emotional support— even if a male peer is equally capable. This reflects the stereotype that women are inherently more caring and empathetic. While this perception is positive on the surface, it can place an unfair emotional burden on women and reinforce gendered expectations that limit how both women and men are allowed to behave in social roles.

Business Example: An example of the “women are wonderful” effect can be observed in public opinion about women in leadership roles. While women in leadership are often praised for being caring, empathetic, and nurturing, these same qualities are sometimes seen as less appropriate for highstakes decision-making or assertiveness in business contexts. Research by Heilman and Okimoto (2007) found that women in positions of authority were rated as less authoritative than men, even though they were rated higher on

Selected References

Eagly, A. H., & Mladinic, A. (1994). Gender stereotypes and attitudes toward women and men. Personality and Social Psychology Bulletin, 20(5), 366–378.

Heilman, M. E., & Okimoto, T. G. (2007). Why are women penalized for success at male tasks?: the implied communality deficit. Journal of applied psychology, 92(1), 81.

Rudman, L. A., & Glick, P. (1999). Feminized management and backlash toward agentic women: The hidden costs to women of a kinder, gentler image of middle managers. Journal of Personality and Social Psychology, 77(5), 1004–1010.

437

BIG BAD BIAS BOOK

INDEX Page Number Actor-observer bias (Ac)

346

Allais Paradox: Common Consequence (Cc)

302

Allais Paradox: Common Ratio (Cr)

304

Ambiguity attitude (Aa)

12

Ambiguity effect (Ae)

300

Anchoring or focalism (Af)

116

Anthropocentric thinking (An)

316

Anthropomorphism or personification (Am)

318

Attentional bias (At)

118

Attribute substitution (As)

148

Automation bias (Au)

150

Authority bias (Ab)

344

Availability cascade (Av)

416

Availability heuristic (Ah)

20

Backfire effect (Bf)

240

Bandwagon effect (Bw)

418

Base rate fallacy or Base rate neglect (Br)

154

Belief bias (Bb)

242

Ben Franklin effect (Bn)

380

Berkson paradox (Bk)

152

Bias blind spot (Bs)

382

Bizarreness effect (Be)

22

Cheerleader effect (Cd)

348

Choice-supportive bias (Ch)

72

Clustering illusion (Ci)

156

Compassion fade (Cm)

384

Confirmation bias (Cf)

244 438

BIG BAD BIAS BOOK

Congruence bias (Co)

196

Conjunction fallacy (Cj)

158

Conservatism or Regressive Bias (Cn)

28

Conservatism or Belief Revision (Cv)

248

Consistency bias (Cb)

24

Context effect (Ce)

26

Continued influence effect (Cl)

246

Contrast effect (Ct)

74

Courtesy bias (Cu)

388

Cross-race effect (Cs)

30

Cryptomnesia (Cy)

32

Curse of knowledge (Ck)

386

Declinism (De)

76

Decoy effect (Dy)

164

Default effect (Dt)

162

Defensive attribution hypothesis (Db)

350

Denomination effect (Df)

216

Disposition effect (Ds)

218

Distinction bias (Di)

160

Dread aversion (Da)

322

Dunning-Kruger effect (Dk)

186

Duration neglect (Du)

130

Egocentric bias (individual) (Eg) Egocentric bias (social) (Ec)

34 352

Ellsberg paradox (Ep)

306

Empathy gap (Em)

324

End-of-history illusion (Eh)

252

Endowment effect (Ew)

220

Exaggerated expectation (Ex)

254

Experimenter's or expectation bias (Ee)

250

439

BIG BAD BIAS BOOK

Extrinsic incentives bias (Et)

354

Fading affect bias (Fa)

36

False consensus effect (Fc)

356

False memory (Fm)

38

False uniqueness bias (Fu)

360

Focusing effect (Fe)

120

Forer effect or Barnum effect (Fb)

256

Form function attribution bias (Ff)

258

Framing effect (Fr)

166

Frequency illusion or Baader-Meinhof effect (Fi)

122

Functional fixedness (Fn)

320

Fundamental attribution error (Fd)

358

Gambler's fallacy (Gf)

132

Generation/Self-generation effect (Gs)

40

Google effect (Go)

42

Group attribution error (Ga)

420

Groupthink (Gt)

422

Halo effect (Ha)

362

Hard-easy effect (Hy)

188

Herding (Hr)

424

Hindsight bias (Hb)

260

Hostile attribution bias (Hs)

390

Hot-hand fallacy (Hh)

262

Humor effect (He)

44

Hyperbolic discounting (Hd)

134

IKEA effect (Ie)

222

Identifiable victim effect (If)

392

Illicit transference (It)

200

Illusion of asymmetric insight (Ii)

364

Illusion of control (Ic)

264 440

BIG BAD BIAS BOOK

Illusion of external agency (Ix)

370

Illusion of transparency (Ip)

366

Illusion of validity (Iv)

268

Illusory correlation (Il)

266

Illusory superiority (Io)

368

Illusory truth effect (Iy)

270

Impact bias (Im)

326

Implicit association (Ia)

78

Information bias (Ib)

168

Ingroup bias (Ig)

426

Insensitivity to sample size (Is)

198

Interoceptive bias (In)

328

Irrational escalation/Escalation of commitment (Ir)

224

Just-world hypothesis (Jw)

372

Lag effect (Le)

46

Law of the instrument (Li)

202

Levels-of-processing effect (Lp)

50

Leveling and sharpening (Ls)

52

Less-is-better effect (Lb)

170

Licencing effect

136

List-length effect (Ll)

48

Look-elsewhere effect (Lk)

204

Loss aversion (La)

226

Mere exposure effect (Mx)

272

Misinformation effect (Me)

56

Modality effect (Mo)

58

Money illusion (Mi)

228

Mood-congruent memory bias (Mc)

54

Moral credential effect (Ml)

138

Moral luck (Mr)

374 441

BIG BAD BIAS BOOK

Naïve cynicism (Na)

376

Naïve realism (Nr)

378

Negativity bias or Negativity effect (Ne)

80

Neglect of probability (Ng)

172

Next-in-line effect (Nx)

60

Normalcy bias (Nb)

274

Not invented here (Nh)

230

Observer-expectancy effect (Ob)

206

Omission bias (Om)

276

Optimism bias (Op)

330

Ostrich effect (Os)

278

Outcome bias (Ot)

208

Outgroup homogeneity bias (Oh)

428

Overconfidence effect (Oc)

190

Pareidolia (Pa)

280

Parkinson's law of triviality (Pk)

174

Part-list cueing effect (Pc)

62

Peak-end rule (Pr)

68

Pessimism bias (Pb)

192

Picture superiority effect (Ps)

70

Planning fallacy (Pf)

210

Positivity effect (Socio-emotional selectivity) (Po)

66

Present bias (Pt)

144

Primacy, recency & serial position effect (Pi)

64

Pro-innovation bias (Pv)

332

Processing difficulty effect (Pd)

82

Projection bias (Pj)

142

Pseudocertainty effect (Pe)

232

Pygmalion effect

394

Reactance (Rc)

334 442

BIG BAD BIAS BOOK

Reactive devaluation (Rd)

282

Recency illusion (Ri)

140

Regressive bias (Rg)

176

Reminiscence bump (Rb)

108

Restraint bias (Re)

194

Rhyme as reason effect (Rr)

286

Risk attitude (Ra)

14

Risk compensation/Peltzman effect (Rp)

284

Salience bias (Sa)

336

Selection bias (Sb)

124

Selective perception (Sp)

292

Self-relevance effect (Sr)

92

Self-serving bias (Ss)

404

Semmelweis reflex (Sm)

290

Sexual over/underperception bias (Sx)

406

Shared information bias (Sh)

398

Singularity effect (Si)

400

Social comparison bias (So)

430

Social desirability bias (Sd)

396

Source confusion (Sc)

84

Spacing effect (Sp)

90

Spotlight effect (Sl)

88

St Petersburg paradox (St)

308

Status quo bias (Sq)

294

Stereotypical bias (Sy)

96

Stereotyping (Se)

432

Subadditivity effect (Su)

180

Subjective validation (Sj)

288

Suffix effect (Sf)

86

Suggestibility (Su)

94 443

BIG BAD BIAS BOOK

Surrogation (Sg)

212

Survivorship bias (Sv)

178

System justification (Sn)

402

Tachypsychia (Tp)

102

Telescoping effect (Tl)

100

Testing effect (Te)

98

Third-person effect (Td)

434

Time-saving bias (Tm)

146

Tip of the tongue (Tt)

106

Trait ascription bias (Ta)

408

Travis syndrome (Ts)

104

Ultimate attribution error (Ua)

410

Unit bias (Ub)

234

Verbatim effect (Ve)

112

Violation of dominance (Vd)

314

Violation of independence (Vi)

312

Violation of transitivity (Vt)

310

von Restorff effect (Rf)

110

Weber-Fechner law (Wf)

214

Well-travelled road effect (Wr)

182

Women are wonderful effect (Ww)

436

Worse-than-average effect (Wa)

412

Zeigarnik effect (Ze)

114

Zero-risk bias (Zr)

296

Zero-sum bias (Zs)

184

444

BIG BAD BIAS BOOK

NOTES

445

BIG BAD BIAS BOOK

446