Romanian Distribution Committee Magazine, Volume 10, Issue 2, Year 2019

UNDE RS T ANDI NGE MOT I ONS … QUI CKANDE AS Y , E MOT I ONSWHI CHCANMAKEAL LOFUSVUL NE RABL E .

E MOT I ONANDKNOWL E DGE

CONCE I VI NGANDUS I NGT HENEW S YS T E MS / T E CHNOL OGI E S WI T HABAL ANCEBETWE E NPE RPET UALHUMANVAL UE S / PRI NCI PL E S ANDT HERAT I ONALACT UALT RE NDS

VOL UME10 I S S UE2 2019

Editorial: Understanding Emotions… Quick and Easy, Emotions which Can Make All of Us Vulnerable. Emotion and Knowledge

On March 25 this year we find out thanks to Adweek that Stacy Martinet, VP of Marketing Strategy at Adobe, expressed the opinion that as U.S. consumers’ online engagement (with digital content across various platforms, devices and channels) is rising within the explosion of emerging technologies, companies will need to adapt accordingly, by using adequate (utilitarian and entertaining) content marketing strategies. Martinet showed, among other aspects, how: key in delivering personalized and relevant content and experiences will be to understand emotion (engagement will be redefined by multi-surface screens, coupled with mobile; personalization will be taken to the next level by biometrics, retailers having the opportunity to measure how their customers feel in-flight or in-store), the Zero UI (the use of sensory experiences – such as gestures, movement, voice – in order to trigger a particular reaction from a device) devices’ use for purchasing is rising etc. Three days later, we received an email from eMarketer Retail with regard to a January 2019 survey from iVend Retail in partnership with AYTM – and entitled “Global Shopper Trends Report”, Feb 19, 2019 – which revealed the main aspects of the retail shopping experience Internet users (age 18+) worldwide do value most: quick and easy check out (83% of respondents); earning rewards or loyalty points (58,7%); free or easy returns (56,7%); click and collect/buy online, pickup in-store (44,3%); personalized offers, experiences and communications (37,1%); technology like AR, voice-assisted shopping, virtual dressing rooms (17,7%).

The Future Stores Report 2019 of WBR Insights (they surveyed 100 Directors of Commerce from across Europe in Q1 of 2019) – “Destination: Shopping” – has a significant

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structure (Investing in technology; Mapping the customer journey; The future of in-store), which is speaking for itself, being highlighted from the Introduction (guest contributor Gary Bott, Managing Director, Gentle Monster) that the physical retail is challenged to integrate the best parts of the online experience into its stores, re-imagining the very foundation of the retail experience (both of the roles of staff and the use of space), taking into account the more convenient and personalized experience of eCommerce which made customer expectations to switch. Among other aspects, this report revealed: the biggest business advantages of leveraging mobile technology in-store (enhanced in-store shopping experience, helping to convert in-store sales, driving customer loyalty and retention, ability to provide personalized offers, brand promotion, closing the gap between online and in-store cx, enabling customers to self-serve in-store); that a “destination shopping” approach is preferred by 70% of Heads of Commerce surveyed (a sense of belonging, giving something back to the community etc.).

Within this framework we considered to be important to make reference to the discussion hosted on May 29 this year by JWT Intelligence with the futurist James Wallman, author of the new book “Time and How to Spend It”, about why time (the most valuable modern currency) is the new luxury, the importance of experiential intelligence and how brands can better engage consumers (who are finding happiness and status in experiences) in today’s experience economy (in the new era of experientialism, shifting from materialism), when what we do now matters. Wallman argued that there are three reasons for why people are misspending their time (weapons of mass distraction; the education system focused on the skills of production; being multitask at work, we are affecting our free time – the so-called by sociologists “contaminated time”, as discovered by Brigid Schulte in her book “Overwhelmed: Work, Love, And Play When No One Has The Time”), being continuously open to something else and needing to learn to live with technology and digital media, and never forgetting how a brand made them feel, beyond customer journey mapping and jobsto-be-done theory.

In this environment of never forgetting how a brand make its customers feel our thoughts took us to the latest annual Shopper Experience Index released by Bazaarvoice, Inc. (which surveyed 2,000 consumers in the US, France, UK, and Germany), the provider of user-generated content (UGC) and shopper data solutions, on April 16, 2019, Bazaarvoice (founded in 2005) being known as “connecting brands and retailers to consumers, so that every shopping experience feels personal”. (Globe Newswire, 2019) This latest report of Bazaarvoice identified five key things: the shopping journey is fueled by the UGC (shoppers want to see easy what other consumers think about products, rewarding brands and retailers accordingly – in other words, retailers need to understand customers’ feelings about ratings and reviews, questions and answers, and user photos); before a transaction, shoppers crave interaction (engagement with Q&A content is very important); everyone wins when brands and retailers collaborate (at the moment of truth it is necessary to deliver content and insights); an opportunity to stand out is represented by a great mobile experience (ensuring adequate interactions with UGC); a big payoff can be delivered by getting personal with shoppers (knowing how hungry are consumers for relevant shopping experiences; consumers becoming frustrated when retailers fail to provide relevant personalized experiences).

And it also shouldn’t come as a surprise that just a year ago (Purcarea, 2018) we concluded that history shows to us that there is nothing new in approaching emotion, at least if we want to understand some wisdom quotes: “Human behavior flows from three main

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sources: desire, emotion, and knowledge” (Plato); “When dealing with people, remember you are not dealing with creatures of logic, but creatures of emotion” (Dale Carnegie). We based this conclusion on significant approaches with regard to the real need of: making deeper emotional connections; providing personalized, engaging, relevant Omni-channel experiences (considering the connectedness across the experience); implementing an emotionalconnection-based strategy across the entire CX; not forgetting the important role played by emotions in both B2B and B2C marketing, because B2B marketing is also taking place between human beings; having seamless emotive conversations within a company’s Omnichannel strategy (across email, chat, SMS, video, social etc.); having personalized conversations regardless of location, device or channel.

Two years ago, David Frenay, CTO and co-founder of GetSmily, commented for Smart Insights: “By understanding the emotions that your customers share with you, you can give them what they really want. Remember that you can’t change your customers’ feelings on a dime. You can’t force them to like you, but what you can do is to find out why they feel in a certain way and improve what and how you offer it. A satisfied customer is a loyal one; don’t be deaf to their emotions, but learn from them instead”. (Frenay, 2017) At the end of the last year Adobe President and CEO Shantanu Narayen was cited as follows: “Feelings that create lasting memories build affinity and keep us chasing that experience”. (Adobe Experience Cloud, 2018) In May this year Mark de Bruijn, Vice President of Marketing in Europe, Middle East, and Africa at SAP Customer Experience, argued that: “If a transaction or process has been successfully completed, then it was a success, or so it is argued. But this method does not address the customer’s feelings about the transaction. It would thus be good for companies to change their measuring method. It is not the final transaction that determines customer satisfaction, but the feeling that customers are left with. Only then can you expose the improvement areas in the customer experience”.

There is no doubt about “The Power Of Emotional Marketing”, (Lofgren, 2019) behind customers’ everyday decisions emotions being the key drivers, emotions which can make all of us vulnerable.

Theodor Valentin Purcărea Editor-in-Chief References de Bruijn, M. (2019). Customer experience is about emotion, not technology, The Next Web, May 8. Retrieved from https://thenextweb.com/podium/2019/05/08/customer-experience-is-about-emotion-not-technology/ Frenay, D. (2017). Improve your customer experience by leveraging the power of emotions, Smart Insights, 30 Mar. Retrieved from https://www.smartinsights.com/customer-engagement/customer-engagement-strategy/improve-yourcustomer-experience-by-leveraging-the-power-of-emotions/ Lofgren, L. (2019). The Power Of Emotional Marketing, Quick Sprout — Make Better Content, April 18. Retrieved from https://www.quicksprout.com/emotional-marketing/ Koch, L. (2-19). Consumers Agree: In-Store Checkout Needs to Be Quick and Easy, eMarketer Retail Sent: Thursday, March 28, 2019, 13:10 Martinet, S. (2019). 4 Ways Emerging Tech Will Redefine Content Marketing, Adweek, March 25. Retrieved from https://www.adweek.com/digital/4-ways-emerging-tech-will-redefine-content-marketing/?

Purcarea, T. (2018). Brands and Emotionally Connected Customers in an Omni Channel World, Romanian Distribution Committee Magazine, Romanian Distribution Committee, Volume 9, Issue 2, pp.12-14, June *** Future Stores Report 2019, Destination: Shopping, WBR Insights 2019, connectedstores.wbresearch.com

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*** James Wallman, author, Time and How to Spend It - 05-29-2019 by JWT Intelligence - JWT Intelligence https://www.jwtintelligence.com/2019/05/james-wallman-author-time-and-how-to-spend-it/ *** http://www.brigidschulte.com/books/overhelmed/ *** Bazaarvoice Report: Shoppers Crave Connection and Conversation with Brands and Retailers, Globe Newswire, April 16, 2019. Retrieved from https://www.globenewswire.com/news-release/2019/04/16/1804664/0/en/Bazaarvoice-ReportShoppers-Crave-Connection-and-Conversation-with-Brands-and-Retailers.html *** Shopper Experience Index, Bazaarvoice Report, https://www.bazaarvoice.com/shopper-experience-index/ *** The Missing Ingredient for a Knockout Customer Experience? Emotional Data, Adobe Experience Cloud, December 13, 2018. Retrieved from https://theblog.adobe.com/why-measuring-emotion-is-the-key-to-a-better-experience/

The Magazine is the result of a true partnership, by bringing scientists and practitioners together proving the passionate pursuit of knowledge for wisdom, the real passion for acquiring and sharing this knowledge inviting the readers to maturing interdisciplinary dialogue and building a transparent culture network.

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The Information and Communications Technology is Driving Artificial Intelligence to Leverage Refined Knowledge for the World Sustainable Development -Part 3-

Prof.Eng.Ph.D. Victor GREU Abstract The paper approaches the analysis of the complex processes of artificial intelligence contribution to knowledge refining, in the general context of Information and Communications Technology (ICT) exponential evolution as main driving factor of the progress of the Information society (IS) toward Knowledge Based Society (KBS).

In this context ICT grows, but considering its complex proliferation and exponential development at Earth scale, lately by artificial intelligence (AI), as leading to a planetary digital disruption, it is necessary to estimate how big would be this iceberg, because this growing with no precisely known perspective offers enough reasons to be timely and responsibly analysed. The analysis is a dynamic challenge because the question has multiple angles to be answered, mainly twofold: how much ICT can really grow in its diverse directions (applications fields) and, on the other side, to which extent the specific and then global consequences of these growings (advances) are sustainable for humankind and Earth?

The author presented, by a systemic approach, some relevant examples of this complex space/time plan where ICT/AI is fast evolving, aiming both the growing and the knowledge refining potentials.

The domain of “understanding natural languageâ€? (UNL) was selected first just because it is actually one of the most prominent, prolific and challenging fields of AI, without mentioning the essential role of man-machine communication in this digital ĂŠpoque of humankind evolution and generally in the IS/KBS processes. UNL rises difficult problems of accuracy (false understanding) in the important applications for security, where the performance is critical for avoiding false identification or service denial.

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As the impact of AI to the health care field is enough important for humankind, it is developed and analysed with priority and perhaps one of the most prominent work in the AI use for the medical field is done by IBM, but the detailed analysis of this case showed that IBM powerful technology (Watson) is not enough for the complex reality of today’s health care system. At least when trying to apply Watson to cancer treatment, one of medicine’s biggest challenges, IBM faced a big difference between the way machines learn and the way doctors work.

One of the conclusions is that in the ICT/AI struggle to win higher and higher peaks of performance, especially in the health care field, where humankind expectations are naturally the most justified, all the progress efforts must be supported, encouraged but also carefully and realistically timely analysed in order to obtain the optimal results, even when “the downs” appear to be prominent. It is also very important to use and learn lessons from all the refined knowledge these ups and downs of ICT/AI provide, adding new human expertise and use all available resources to get sustainable progress in all activity areas, keeping humankind health as first priority, not only in the ICT/AI direct health care applications, but also in the indirect consequences that could come sooner or later from other fields progress.

The paper analysis includes another relevant systemic example of AI growing, the communications vast area, because, albeit the idea of intelligent network is not new, the actual AI potential and the trend of using most of wireless communication capacity are generating very important applications aiming optimization. Considering the complex picture of the factors that could influence wireless communications performance, it seems that the medium access control is a zone where they could benefit most from AI(machine learning) support in optimizing areas like Signal detection, Channel encoding and decoding, Channel estimation, prediction, and compression, Resource allocation etc.

An important conclusion of paper is that extending applications area of AI could be less efficient if we do not add some new approaches of the ways to understand and use the complex relations between data, information and knowledge resulting from these applications and more than these, add the cognitive principles we must develop AI on, in order to perform towards human brain-like models that leverage learning from that knowledge, i.e. properly refining knowledge.

Another conclusion is the necessity of conceiving and using the new systems/technologies with a balance between perpetual human values/principles and the rational actual trends. There is still a reasonable expectation that ICT/AI could better leverage the management of this balance by their implementation in most advanced cognitive systems, i.e. we have to keep alive wisdom principles and update them with the refined knowledge that reflects the actual needs of humankind and Earth, not only for immediate efficiency, but for a stable future of the available resources and life environment. The actual challenges of ICT/AI development must be synchronized with the humankind surviving (on Earth) challenges and risks, but here the point is that, more than AI, the cognitive computing systems (CCS) could really be a part of the right decision in a matter that is closing now to the human intelligence stage, just by the potential to approach high level problems.

Considering the high level of cognitive science, in the concrete development of AI toward CCS there is a long way, naturally similar to the IBM-Watson bitter-sweet evolution, i.e. very difficult and complex. Going to the core of CCS, the aim is the human brain map and functionality, which must be replicated in the future.

The paper also referred to concrete principles, methods and technologies to reach such performance and complex objectives, which are among the most sophisticated ingredients of the evolution from AI to CCS, without neglecting brain complex operating processes and the ways these are related to reality. For a progress from here ahead it is very

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probable to refer to the people’s changing behaviour and evolutionary epistemology, or simple to the brain. Without offering solutions here, this philosophy approach (one of the many possible!) has the quality to reveal the complexity of the AI target to follow the human brain model and in the same time is a good instrument of orienting the AI/CCS design to overpass inherent human limits of reflecting reality, by using objective measures/metrics for sensing most of reality parts, but unfortunately not for all.

Another useful conclusion is that the most difficult problems for AI/CCS progress are in the aria of managing knowledge associated to abstract concepts (like compassion, causality or democracy) where never the human perception, imagination and creation would be completely replaced.

Consequently AI/CCS should be developed in a close collaboration between AI and human intelligence, expertise and responsibility, i.e. CCS should include selected humans in all processes, from design to implementation and usage, as intrinsic parts of the systems and applications, valuing the AI natural language processing, computer vision or other similar advanced man-machine interfaces (like emerging brain-computer interfaces).

Although all the above (at least) human contributions are important, it is worth to notice that the most prominent should be in responsibly designing AI/CCS as the knowledge used and refined must have the potential to generate sustainable progress of humankind and Earth ecosystem.

Keywords: natural language, IBM Watson, knowledge refining, deep learning, physical layer optimization, machine learning, neural networks, medium access control, evolutionary epistemology, information society, knowledge based society.

JEL Classification: L63; L86; M15; O31; O33

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Failure is simply the opportunity to begin again, this time more intelligently Henry Ford

1. Where the Information and Communications Technology intelligence grows Typically, the humans have the ancestral tendency to grow everything they like and this is far from ‌ being limited to food.

This simple observation has major implications all around us and lately we can see that the Information and Communications Technology (ICT) became the main driving engine of the Information Society (IS) toward Knowledge Based Society (KBS), just by using its overwhelming influence on all humankind activity, as, step by step, ICT products and services succeeded to bring more and more benefits for humankind life and IS/KBS progress [22] [23] [26] [19].

Perhaps this is the main way ICT grows, but its complex proliferation and exponential development at Earth scale, reflected by Internet of Things (IoT), Cloud, Big Data, or lately artificial intelligence (AI), leading to a planetary digital disruption (DD), rise a question that we have repeatedly expressed [8] [3] [14]: How big would be this growing iceberg?

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With simpler words, this growing with no precisely known perspective offers enough reasons to be timely and responsibly analysed.

The analysis is a dynamic challenge because the question has multiple angles to be answered, mainly twofold: how much ICT can really grow in its diverse directions (applications fields) and, on the other side, to which extent the specific and then global consequences of these growings (advances) are sustainable for humankind and Earth?

This way we could observe the eventual link between this twofold dynamic challenge and the intelligence we expect to be found in every ICT growing.

More than these, a complete understanding of this section title/aim should include the inherent link between an intelligent growing and the AI that is the actually the most promising advance of ICT development.

Further we could analyse and eventually understand how these ICT/AI advances are leveraging the knowledge refining everywhere are used and this way easing the World sustainable development.

In such complex context, any analysis, far from being exhaustive, should consider both the dynamic of ICT/AI exponential pace of development and the ubiquitous horizontal spreading of applications fields at planetary scale.

Our approach will first consider some relevant examples of this complex space/time plan where ICT/AI is fast evolving, aiming both the growing and the knowledge refining potentials.

It is obvious that selecting examples from the huge diversity of ICT/AI context is itself a multicriteria problem and consequently a systemic approach is essential, as it is indirectly confirmed by this first example [1]: “...one of the major challenges in developing systems that understand natural language is coverage of possible inputs. This is a symptom of the limited imagination of individual humans, which can be remedied by harnessing the power of the crowd to amplify the imagination of an individual developer, and provide more complete coverage of the input space. The benefits of crowdsourcing are not limited to enhanced understanding of language, as the crowd can also provide common sense knowledge and enhanced creativity...”

Here we should observe that the systemic approach is provided by the global condition to cover all “possible inputs” (system parts) and the relevance of this example is also systemic if we recall that in the AI modelling theory an essential rule is to provide the logical coverage of all scenarios that could be generated in the problem context. This first observation shows in fact that this example has also relevance for the mentioned selection multicriteria problem.

In addition, we have approached “understanding natural language” domain just because it is actually one of the most prominent, prolific and challenging fields of AI, without mentioning the essential role of man-machine communication in this digital époque of humankind evolution and generally in the IS/KBS processes.

More than these, “the limited imagination of individual humans” and “benefits of crowdsourcing” were already presented in our previously papers [11] [21], but here we have one more confirmation of the fact that in the knowledge refining processes “crowd can also provide common sense knowledge and enhanced creativity”.

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The model and the technology used in this AI example is further relevant for our analysis: “Content creation is crowdsourced by recording thousands of human performances, which are mined for patterns representing elements of narrative structure (e.g. events, dependencies). Patterns guide a novel runtime architecture which combines plan recognition with casebased planning to replay fragments of recorded games at runtime. Initial work explored automatically discovering patterns in data. Ultimately, patterns were discovered through a human-machine collaborative process, where human annotated recorded performances with meta-data representing narrative structure, from which patterns were extracted. Browser-based tools allowed hiring people anywhere in the world to annotate transcripts of recorded human performances.”

It is worth to notice that another relevance of the example is given by the fact that “understanding natural language” (UNL) is a prominent class of AI complex applications, where deep learning (DL), a higher form of machine learning (ML), is used in a combined unsupervised-supervised process, as we generally already presented [3].

The last, but not the least, we should stress that “the limited imagination of individual humans” and “The benefits of crowdsourcing” confirm once again the objective necessity of combining AI and human(collective) intelligence HI in order to maximize the efficiency and performance of the ICT/AI processes [17][11].

In the case of UNL, this necessity is asked due to the huge diversity of languages, dialects, but especially variations from individual to individual even for the same language.

These variations rise difficult problems of accuracy (false understanding) in the important applications for security, where the performance is critical for avoiding false identification or service denial.

In the same direction, the emerging area of cognitive intelligence (CI), an ultimate performance horizon for AI [25][3], for example at humanoid robots, requires the capacity to understand and express sophisticated issues like emotions or intellectual creations, which is essentially challenging for UNL features.

Exceeding the UNL domain, it is worth to observe here that “Crowdsourced Common Sense” and “common sense knowledge” represent subjects very relevant for ICT/AI capacity to leverage knowledge refining.

First, we have already presented that Crowdsourcing and generally collective intelligence are prominent trends for the ICT/AI performance/efficiency improvement [11], but in this context they are increasing the potential to extract knowledge from large amounts of useful data.

Perhaps this subtle connection is even more interesting in the case of common sense knowledge, but for the emerging applications and benefits of new technologies like social media, the above example, [1], shows that when “... leveraging the crowd to understand language, however, the crowd is equally useful for providing common sense knowledge, and possible narratives... from which it is possible to learn common sense about everyday physical and linguistic interactions...”

Our opinion is that we can use the new AI technologies associated with UNL for leveraging knowledge refining in a very complex field of intelligence, like common sense,

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where, for AI, it will be one of the latest barricades to conquer in the fight to compete with humans.

Talking about common sense, it is obvious that it is a vast sphere, where always is something to observe, but, as AI/ML is progressing, one could believe there is few to discover or connect.

For example, when thinking for choosing the next “AI example” in this section, it could appear strange to imagine that it will be very tight with ... the natural language.

As this start was just an idea about how common sense could be tricky, let’s say that, for the mentioned systemic approach, the impact of AI to the health care field is enough important for humankind to be developed and analysed with priority [27].

Perhaps one of the most prominent work in the AI use for the medical field is done by IBM and a very comprehensive analysis of this case, we will shortly discuss here, is made in [2]: “In 2014, IBM opened swanky new headquarters for its artificial intelligence division, known as IBM Watson. Inside the glassy tower in lower Manhattan, IBMers can bring prospective clients and visiting journalists into the “immersion room,” which resembles a miniature planetarium. There, in the darkened space, visitors sit on swiveling stools while fancy graphics flash around the curved screens covering the walls. It’s the closest you can get, IBMers sometimes say, to being inside Watson’s electronic brain.

One dazzling 2014 demonstration of Watson’s brainpower showed off its potential to transform medicine using AI—a goal that IBM CEO Virginia Rometty often calls the company’s moon shot. In the demo, Watson took a bizarre collection of patient symptoms and came up with a list of possible diagnoses, each annotated with Watson’s confidence level and links to supporting medical literature.Within the comfortable confines of the dome, Watson never failed to impress: Its memory banks held knowledge of every rare disease, and its processors weren’t susceptible to the kind of cognitive bias that can throw off doctors. It could crack a tough case in mere seconds. If Watson could bring that instant expertise to hospitals and clinics all around the world, it seemed possible that the AI could reduce diagnosis errors, optimize treatments, and even alleviate doctor shortages—not by replacing doctors but by helping them do their jobs faster and better.”

As we have repeatedly presented [18] [3], as ICT/AI progress is aiming higher peaks, it is more difficult to progress and even to keep pace, performance, efficiency or credibility.

As a consequence, we have proposed to timely and carefully analyse these evolutions, in order to foresee not only benefits but also the less positive implications of their too fast proliferation at Earth scale.

If this general opinion could have, naturally, a level of relativity, it is sure that when speaking of the AI struggle to get closer to the human intelligence, this degree is lower and the IBM studied case is a good confirmation.

Anyway, it is important to stress, from the beginning, that we do not completely agree with all the (extreme) quoted opinions, but, as study example, we consider that the ups and downs of this AI challenging field could lead to realistic conclusions for the ICT/AI too fast pace versus the complexity of all the consequences for humankind and Earth, that must be analysed in too short time, counting ICT contributions to climate changes, Earth resource fading, social/human implications etc.[8][15][24][16].

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Coming back to the natural language we have mentioned above, as a coincidence, it lays at the Watson basics and explain an essential part of the IBM involved technology for medical support: <<The Jeopardy! victory in 2011 showed Watson’s remarkable skill with naturallanguage processing (NLP). To play the game, it had to parse complicated clues full of wordplay, search massive textual databases to find possible answers, and determine the best one.“It almost seemed that Watson could understand the meaning of language, rather than just recognizing patterns of words,” says Martin Kohn, who was the chief medical scientist for IBM Research at the time of the Jeopardy! match. “It was an order of magnitude more powerful than what existed.” What’s more, Watson developed this ability on its own, via machine learning. The IBM researchers trained Watson by giving it thousands of Jeopardy! clues and responses that were labeled as correct or incorrect. In this complex data set, the AI discovered patterns and made a model for how to get from an input (a clue) to an output (a correct response). Long before Watson starred on the Jeopardy! stage, IBM had considered its possibilities for health care. Medicine, with its reams of patient data, seemed an obvious fit, particularly as hospitals and doctors were switching over to electronic health records. While some of that data can be easily digested by machines, such as lab results and vital-sign measurements, the bulk of it is “unstructured” information, such as doctor’s notes and hospital discharge summaries. That narrative text accounts for about 80 percent of a typical patient’s record—and it’s a stew of jargon, shorthand, and subjective statements.>> The huge progress of ICT/AI/Watson has naturally impressed medical specialists and their hopes are partially confirmed, as: <<Kohn, who came to IBM with a medical degree from Harvard University and an engineering degree from MIT, was excited to help Watson tacke the language of medicine. “It seemed like Watson had the potential to overcome those complexities,” he says. By turning its mighty NLP abilities to medicine, the theory went, Watson could read patients’ health records as well as the entire corpus of medical literature: textbooks, peer-reviewed journal articles, lists of approved drugs, and so on. With access to all this data, Watson might become a superdoctor, discerning patterns that no human could ever spot.“Doctors go to work every day—especially the people on the front lines, the primary care doctors—with the understanding that they cannot possibly know everything they need to know in order to practice the best, most efficient, most effective medicine possible,” says Herbert Chase, a professor of medicine and biomedical informatics at Columbia University who collaborated with IBM in its first health care efforts. But Watson, he says, could keep up—and if turned into a tool for “clinical decision support,” it could enable doctors to keep up, too. In lieu of a Jeopardy! clue, a physician could give Watson a patient’s case history and ask for a diagnosis or optimal treatment plan.>> Unfortunately we have to comeback, this time to the mentioned AI ups and downs, as Watson is such case [2]: “MD Anderson Cancer Center partnered with IBM Watson to create an advisory tool for oncologists. The tool used natural-language processing (NLP) to summarize patients’ electronic health records, then searched databases to provide treatment recommendations.

Physicians tried out a prototype in the leukemia department, but MD Anderson canceled the

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project in 2016—after spending US $62 million on it. Outside of corporate headquarters, however, IBM has discovered that its powerful technology is no match for the messy reality of today’s health care system. And in trying to apply Watson to cancer treatment, one of medicine’s biggest challenges, IBM encountered a fundamental mismatch between the way machines learn and the way doctors work.”

Our opinion is that in the ICT/AI struggle to win higher and higher peaks of performance, especially in the health care field, where humankind expectations are naturally the most justified, all the progress efforts must be supported, encouraged but also carefully and realistically timely analysed in order to obtain the optimal results, even when “the downs” appear to be prominent [2]: <<At a 2017 conference of health IT professionals, IBM CEO Rometty told the crowd that AI “is real, it’s mainstream, it’s here, and it can change almost everything about health care,” and added that it could usher in a medical “golden age.” She’s not alone in seeing an opportunity: Experts in computer science and medicine alike agree that AI has the potential to transform the health care industry. Yet so far, that potential has primarily been demonstrated in carefully controlled experiments. Only a few AI-based tools have been approved by regulators for use in real hospitals and doctors’ offices. Those pioneering products work mostly in the visual realm, using computer vision to analyse images like Xrays and retina scans. (IBM does not have a product that analyses medical images, though it has an active research project in that area). Looking beyond images, however, even today’s best AI struggles to make sense of complex medical information. And encoding a human doctor’s expertise in software turns out to be a very tricky proposition. IBM has learned these painful lessons in the marketplace, as the world watched. While the company isn’t giving up on its moon shot, its launch failures have shown technologists and physicians alike just how difficult it is to build an AI doctor.>> We also consider that it is very important to use and learn lessons from all the refined knowledge these ups and downs of ICT/AI provide, adding new expertise from CI and use all available resources to get sustainable progress in all activity areas, keeping humankind health as first priority, not only in the ICT/AI direct health care applications, but also in the indirect consequences that could come sooner or later from other fields progress.

Another relevant systemic example of AI growing is placed, where else but in ... the communications vast area.

Although the idea of intelligent network is not new, the actual AI potential and the trend of using most of wireless communication capacity are generating very important applications aiming optimization [4]: “The field of machine learning (ML) has a long and extremely successful history. For example, the idea of using neural networks (NN) for intelligent machines dates back to as early as 1942 when a simple one-layer model was used to simulate the status of a single neuron. ML has shown its overwhelming advantages in many areas, including computer vision, robotics, and natural language processing, where it is normally difficult to find a concrete mathematical model for feature representation. In those areas, ML has proved to be a powerful tool as it does not require a comprehensive specification of the model. Different from the aforementioned ML applications, the development of communications has vastly relied on theories and models, from information theory to channel modelling. These

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traditional approaches are showing serious limitations, especially in view of the increased complexity of communication networks. Therefore, research on ML applied to communications, especially to wireless communications, is currently experiencing an incredible boom.”

Looking to the complex picture of the factors that could influence wireless communications performance, it seems that the medium access control is a zone where they could benefit most from AI/ML support in optimization, as the authors in [4] collected many papers and found: “This collection of Best Readings focuses on ML in the physical and medium access control (MAC) layer of communication networks. ML can be used to improve each individual (traditional) component of a communication system, or to jointly optimize the entire transmitter or receiver. Therefore, after introducing some popular textbooks, tutorials, and special issues in this collection, we divide the technical papers into the following six areas:  Signal detection  Channel encoding and decoding  Channel estimation, prediction, and compression  End-to-end communications  Resource allocation  Selected topics Even if ML in communications is still in its infancy, we believe that a growing number of researchers will be dedicated to the related studies and ML will greatly change the way of communication system design in the near future.”

In a concrete manner, a new and comprehensive approach of using deep learning in wireless communication for the physical layer optimization is given then by [6] as: “We present and discuss several novel applications of deep learning for the physical layer. By interpreting a communications system as an autoencoder, we develop a fundamental new way to think about communications system design as an end-to-end reconstruction task that seeks to jointly optimize transmitter and receiver components in a single process. We show how this idea can be extended to networks of multiple transmitters and receivers and present the concept of radio transformer networks as a means to incorporate expert domain knowledge in the machine learning model. Lastly, we demonstrate the application of convolutional neural networks on raw IQ samples for modulation classification which achieves competitive accuracy with respect to traditional schemes relying on expert features.”

Without discussing the theoretical details, it is worth to notice that such approaches show the potential of AI/ML to leverage the optimization, really needed, for one of the most complex issues of ICT development in the crowded/congested future networks (including IoT), especially due to the fact that this methods could be “extended to networks of multiple transmitters and receivers and present the concept of radio transformer networks as a means to incorporate expert domain knowledge in the machine learning model”.

More than these, we observe that the idea of aiming and then refining knowledge is included here and confirms this systemic way of thinking and implementing applications for the most advanced ICT/AI development fields.

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The analysis of this series of examples, of where AI growing is more needed and present, could be obviously completed by adding applications fields like climate changes, computer vision, self-driving cars, smart agriculture, blockchain, smart grid, wind/solar energy, bio-surveillance or weather forecast global prediction models.

Extending applications area of AI could be less efficient if we do not add some new approaches of the ways to understand and use the complex relations between data, information and knowledge resulting from these applications and more than these, add the cognitive principles we must develop AI on, in order to perform towards human brain-like models that leverage learning from that knowledge, i.e. properly refining … knowledge.

2. Learning from cognitive systems It is well known that the wise human is “learning from everything”, although actually this trend is not so spread like in the past, first because the whole humanity history data are equivalently generated in only two years of our days [5][10].

Perhaps a second reason is given by the people’s changing behaviour, which now are rather eager to be informed (only on priority issues) than to “learn from everything”.

For a sustainable ICT/AI and IS/KBS progress we all should take into account these realities by conceiving and using the new systems/technologies with a balance between perpetual human values/principles and the rational actual trends. There is still a reasonable expectation that ICT/AI could better leverage the management of this balance by their implementation in most advanced cognitive systems [12] [13] [20] [9] [3].

In a simpler expression, we have to keep alive wisdom principles and update them with the refined knowledge that reflects the actual needs of humankind and Earth, not only for immediate efficiency, but for a stable future of the available resources and life environment.

Our opinion is very interestingly confirmed, at a larger scale of cognitive science, where we could find solid foundations, like evolutionary epistemology, for the actual most complex theories to develop AI toward cognitive computing systems [7]: “The cybernetician Ashby [1960, 1964] noted that appropriate selection is the essence of intelligence. Indeed, we have defined intelligence as the ability to solve problems, and we have analysed problem solving as selecting the right sequence of actions that lead from the initial state to the goal state. Anything that helps us to make the right selection— such as heuristics or simply additional information about the problem situation—will therefore increase our power to solve problems, and thus amplify our intelligence. In essence, a cognitive system is therefore something that helps us to make the right selection from a variety of possibilities, i.e. the right decision. The larger the variety (i.e. uncertainty), the more difficult it becomes to find the solution by trial-and error, and the more need there is for some cognitive mechanism to reduce complexity and support adequate selection. This creates what evolutionary theorists call a strong “selective pressure” for cognition. Since we are all alive, we have adapted to that pressure. In other words, all the presently living agents have been selected to survive … The surviving agents must have evolved some mechanism(s) to choose adequate actions. Donald T. Campbell [1974], the founder of evolutionary epistemology, called these internal mechanisms “vicarious selectors”. They select

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appropriate actions from the myriad possibilities. In that way, they “stand in” for, substitute, or represent natural selection by the environment. (Note the meaning of the term “vicar”: delegate, representative, substitute). If the vicarious selector had not eliminated the wrong actions, natural selection would have eliminated the agent itself ... There exist many different types of vicarious selectors at different levels of complexity. These include “instinctive” knowledge inherent in the genes, perceptions, which “stand in” for the external situation, knowledge learned from experience, and information received via communication from others. From the point of view of evolutionary epistemology, all cognitive mechanism function essentially as vicarious selectors: they all help us to select the right actions, and do so in order for us to survive natural selection.”

Our opinion is that the actual challenges of ICT/AI development must be synchronized with the humankind surviving (on Earth) challenges and risks, as we have already presented [8], but here the point is that, more than AI, the cognitive computing systems (CCS) could really be a part of the right decision in a matter that is closing now to the human intelligence stage, just by the potential to approach high level problems – like <<“instinctive” knowledge inherent in the genes, perceptions, which “stand in” for the external situation, knowledge learned from experience, and information received via communication from others>>.

If the above “gene” inclusion could appear too much, it is the case to recall, for example, the genetic engineering actual achievements, where AI is more and more prolific in linking DNA genes analysis (and “processing”) with long expected results in practical health care.

In the same time, leaving the high level of cognitive science, in the concrete development of AI toward CCS there is a long way, naturally similar to the IBM-Watson bitter-sweet evolution, i.e. very difficult and complex.

The concrete principles, methods and technologies to reach such performance and complex objectives are among the most sophisticated ingredients of the evolution from AI to CCS [9]: ” 'Cognitive computing represents self-learning systems that utilize machine learning models to mimic the way brain works.' Eventually, this technology will facilitate the creation of automated IT models which are capable of solving problems without human assistance.

The result is cognitive computing – a combination of cognitive science and computer science.”

Going further to the core of CCS, the aim is the human brain map and functionality, which must be replicated in the future as: “Cognition comes from the human brain. So what’s the brain of cognitive systems?

Cognitive computing represents the third era of computing. In the first era, (19th century) Charles Babbage, also known as ‘father of the computer’ introduced the concept of a programmable computer. Used in the navigational calculation, his computer was designed to tabulate polynomial functions. The second era (1950) experienced digital programming computers such as ENIAC and ushered an era of modern computing and programmable systems. And now to cognitive computing which works on deep learning algorithms and big data analytics to provide insights. Thus the brain of a cognitive system is the neural

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network, the fundamental concept behind deep learning. The neural network is a system of hardware and software mimicked after the central nervous system of humans, to estimate functions that depend on the huge amount of unknown inputs.”

The next step is pointing the CCS model features to be implemented, further described as requirements to be fulfilled as [9]: „With the present state of cognitive computing, basic solutions can play an excellent role of an assistant or virtual advisor. Siri, Google assistant, Cortana, and Alexa are good examples of personal assistants. In order to implement cognitive computing in commercial and widespread applications, Cognitive Computing Consortium has recommended the following features for the computing systems – 1. Adaptive They must learn as information changes, and as goals and requirements evolve. They must resolve ambiguity and tolerate unpredictability. They must be engineered to feed on dynamic data in real time or near-real time.

2. Interactive Similar to a brain, the cognitive solution must interact with all elements in the system – processor, devices, cloud services and user. Cognitive systems should interact bidirectionally. It should understand human input and provide relevant results using natural language processing and deep learning. Some intelligent chatbots such as Mitsuku have already achieved this feature.

3. Iterative and stateful They must aid in defining a problem by asking questions or finding additional source input if a problem statement is ambiguous or incomplete. They must 'remember' previous interactions in a process and return information that is suitable for the specific application at that point in time.

4. Contextual They must understand, identify, and extract contextual elements such as meaning, syntax, time, location, appropriate domain, regulations, user’s profile, process, task, and goal. They may draw on multiple sources of information, including both structured and unstructured digital information, as well as sensory inputs (visual, gestural, auditory, or sensorprovided).”

After implementing, as much as possible, these complex features, the results are generally good but the target is still far, because of a lot of factors which remain, in turn, difficult to identify and control, as is finally regnized [9]: „Cognitive computing is definitely the next step in computing started by automation.

It sets a benchmark for computing systems to reach the level of the human brain. But it has some limitations as AI is difficult to apply in situations with a high level of uncertainty, rapid change or creative demands. The complexity of problem grows with the number of data sources. It is challenging to aggregate, integrate and analyze such unstructured data. A complex cognitive solution should have many technologies that coexist to give deep domain insights.”

Still, such approaches are far from the sophisticated ingredients we have mentioned above, at least from the point of view of brain complex operating processes and the ways these are related to … reality.

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Surprisingly, for a progress from here ahead it is very probable to comeback to the people’s changing behaviour and evolutionary epistemology or simple to the brain.

We have already presented [25] that, generally, ICT/AI development optimization is a multi-criteria function, but the implied parameters are sometimes dependent on function values and we could get in a “vicious circle” and on the other hand our target is fast moving and difficult to reach, as Morgan le Fay (Morgana mirage) [3].

This complex and dynamic face of reality was naturally discovered and analysed in studies of evolutionary epistemology, like problems of the reflection (of reality by brain) theory [7]: “… although simple and attractive, this philosophy leads to a range of fundamental problems. First, reality is much too complex to map in detail: we can only register and remember the tiniest fraction of the potentially available information. Moreover, why would we need such an accurate reflection if we have the world itself? Too detailed maps are essentially useless: just imagine a 1/1scale map of a city, where every stone, weed or broken bottle is reproduced in full detail … Simplifying a map may seem obvious, but the problem is that there is no objective way to decide what to leave out and what to include in the map. All maps, models and representations are strongly determined by the purpose for which they are used … More fundamentally, as Kant taught us, we have no access to the “Ding-an-sich”, i.e. the objective reality outside of us, only to our very simplified and distorted perceptions of it.

We cannot compare our mental contents to reality, only to our perceptions—which are themselves already part of our mental contents. Therefore, there is no absolute way that we can make sure that the reflection is accurate. This forces us to abandon accurate reflection as the ultimate criterion of truth. Yet another problem with the reflection view of mind is that it does not explain abstract or affective ideas. For example, how can you perceive compassion, the number zero, causality, or democracy? Which concrete objects are mapped onto these abstract concepts? Even for the phenomenon that initially inspired this philosophy, imagery, it turns that out that there is no true isomorphism between the mental image and the thing it represents…”

Without offering solutions here, this philosophy approach (one of the many possible!) has the quality to reveal the complexity of the AI target to follow the human brain model and in the same time is a good instrument of orienting the AI/CCS design to overpass inherent human limits of reflecting reality, by using objective measures/metrics for sensing most of reality parts, but unfortunately not for all.

Another useful observation is that the most difficult problems for AI/CCS progress are in the aria of managing knowledge associated to abstract concepts (like compassion, causality or democracy) where never the human perception, imagination and creation would be completely replaced.

This way we may consider that AI/CCS should be developed in a close collaboration between AI and human intelligence, expertise and responsibility, i.e. CCS should include selected humans in all processes, from design to implementation and usage, as intrinsic parts of the systems and applications, valuing the AI natural language processing, computer vision or other similar advanced man-machine interfaces (like emerging braincomputer interfaces).

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Although all the above (at least) human contributions are important, it is worth to notice that the most prominent should be in responsibly designing AI/CCS as the knowledge used and refined must have the potential to generate sustainable progress of humankind and Earth ecosystem.

3. Conclusions As ICT products and services succeed to bring more and more benefits for humankind life and IS/KBS progress, ICT grows, but considering its complex proliferation and exponential development at Earth scale, lately artificial by intelligence (AI), as leading to a planetary digital disruption, it is necessary to estimate how big would be this iceberg, because this growing with no precisely known perspective offers enough reasons to be timely and responsibly analysed. The analysis is a dynamic challenge because the question has multiple angles to be answered, mainly twofold: how much ICT can really grow in its diverse directions (applications fields) and, on the other side, to which extent the specific and then global consequences of these growings (advances) are sustainable for humankind and Earth?

We considered, by a systemic approach, some relevant examples of this complex space/time plan where ICT/AI is fast evolving, aiming both the growing and the knowledge refining potentials.

The “understanding natural language” (UNL) domain was selected first just because it is actually one of the most prominent, prolific and challenging fields of AI, without mentioning the essential role of man-machine communication in this digital époque of humankind evolution and generally in the IS/KBS processes. UNL rises difficult problems of accuracy (false understanding) in the important applications for security, where the performance is critical for avoiding false identification or service denial.

The impact of AI to the health care field is enough important for humankind to be developed and analysed with priority and perhaps one of the most prominent work in the AI use for the medical field is done by IBM, but the detailed analysis of this case showed that IBM powerful technology (Watson) is not enough for the complex reality of today’s health care system. At least when trying to apply Watson to cancer treatment, one of medicine’s biggest challenges, IBM faced a big difference between the way machines learn and the way doctors work.

Our conclusion is that in the ICT/AI struggle to win higher and higher peaks of performance, especially in the health care field, where humankind expectations are naturally the most justified, all the progress efforts must be supported, encouraged but also carefully and realistically timely analysed in order to obtain the optimal results, even when “the downs” appear to be prominent. It is also very important to use and learn lessons from all the refined knowledge these ups and downs of ICT/AI provide, adding new human expertise and use all available resources to get sustainable progress in all activity areas, keeping humankind health as first priority, not only in the ICT/AI direct health care applications, but also in the indirect consequences that could come sooner or later from other fields progress.

Albeit the idea of intelligent network is not new, the actual AI potential and the trend of using most of wireless communication capacity are generating very important applications aiming optimization for another relevant systemic example of AI growing, the

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communications vast area. Considering the complex picture of the factors that could influence wireless communications performance, it seems that the medium access control is a zone where they could benefit most from AI/ML support in optimizing areas like Signal detection, Channel encoding and decoding, Channel estimation, prediction and compression, Resource allocation etc.

An important conclusion of paper is that extending applications area of AI could be less efficient if we do not add some new approaches of the ways to understand and use the complex relations between data, information and knowledge resulting from these applications and more than these, add the cognitive principles we must develop AI on, in order to perform towards human brain-like models that leverage learning from that knowledge, i.e. properly refining knowledge.

Another conclusion is the necessity of conceiving and using the new systems/technologies with a balance between perpetual human values/principles and the rational actual trends. There is still a reasonable expectation that ICT/AI could better leverage the management of this balance by their implementation in most advanced cognitive systems, i.e. we have to keep alive wisdom principles and update them with the refined knowledge that reflects the actual needs of humankind and Earth, not only for immediate efficiency, but for a stable future of the available resources and life environment. Thus the actual challenges of ICT/AI development must be synchronized with the humankind surviving (on Earth) challenges and risks, but here the point is that, more than AI, the cognitive computing systems (CCS) could really be a part of the right decision in a matter that is closing now to the human intelligence stage, just by the potential to approach high level problems.

Considering the high level of cognitive science, in the concrete development of AI toward CCS there is a long way, naturally similar to the IBM-Watson bitter-sweet evolution, i.e. very difficult and complex. Going to the core of CCS, the aim is the human brain map and functionality, which must be replicated in the future.

A conclusion is also that the concrete principles, methods and technologies to reach such performance and complex objectives are among the most sophisticated ingredients of the evolution from AI to CCS, without neglecting brain complex operating processes and the ways these are related to reality. For a progress from here ahead it is very probable to comeback to the peopleâ&#x20AC;&#x2122;s changing behaviour and evolutionary epistemology or simple to the brain. Without offering solutions here, this philosophy approach (one of the many possible!) has the quality to reveal the complexity of the AI target to follow the human brain model and in the same time is an useful instrument of orienting the AI/CCS design to overpass inherent human limits of reflecting reality, by using objective measures/metrics for sensing most of reality parts, but unfortunately not for all.

Another useful conclusion is that the most difficult problems for AI/CCS progress are in the aria of managing knowledge associated to abstract concepts (like compassion, causality or democracy) where never the human perception, imagination and creation would be completely replaced.

Consequently, AI/CCS should be developed in a close collaboration between AI and human intelligence, expertise and responsibility, i.e. CCS should include selected humans in all processes, from design to implementation and usage, as intrinsic parts of

28

the systems and applications, valuing the AI natural language processing, computer vision or other similar advanced man-machine interfaces (like emerging brain-computer interfaces).

Although all the above (at least) human contributions are important, it is worth to notice that the most prominent should be in responsibly designing AI/CCS as the knowledge used and refined must have the potential to generate sustainable progress of humankind and Earth ecosystem.

REFERENCES [1] Jeffrey David Orkin, Collective Artificial Intelligence: Simulated Role-Playing from Crowdsourced Data, Dissertation, MIT, Feb. 2013.

[2] Eliza Strickland, IBM Watson, heal thyself: How IBM overpromised and underdelivered on AI health care, IEEE Spectrum, Volume: 56 , Issue: 4 , April 2019 ) [3]Victor Greu, The information and communications technology is driving artificial intelligence to leverage refined knowledge for the World sustainable development– (Part 2), Romanian Distribution Committee Magazine, Volume 10, Issue 1, Year 2019.

[4] Geoffrey Ye Li et all, Best Readings in Machine Learning in Communications, Issued March 2019, https://www.comsoc.org/publications/best-readings/machine-learningcommunications [5] Victor Greu, Extending information and communications technologies’s impact on knowledge based society through artificial and collective intelligence –(Part 3), Romanian Distribution Committee Magazine, Volume 9, Issue 3, Year 2018.

[6] Timothy O’Shea, Jakob Hoydis, An Introduction to Deep Learning for the Physical Layer, IEEE Transactions on Cognitive Communications and Networking ( Volume: 3 , Issue: 4 , Dec. 2017 ) [7] Francis Heylighen, Cognitive Systems a cybernetic perspective on the new science of the mind, Lecture Notes 2014-2015 ECCO: Evolution, Complexity and Cognition - Vrije Universiteit Brussel [8]Victor Greu, Searching the right tracks of new technologies in the earth race for a balance between progress and survival, Romanian Distribution Committee Magazine, Volume 3, Issue1, Year 2012.

[9] Rohit Akiwatka, Introduction to cognitive computing, may 2019, https://channels. theinnovationenterprise.com/articles/ introduction-to-cognitive-computing [10] Seth Earley, There Is No AI Without IA, 2016, IEEE IT Professional (Volume: 18, Issue:3, May-June 2016) [11] Victor Greu et all, Human and artificial intelligence driven incentive-operation model and algorithms for a multi-purpose integrated crowdsensing-crowdsourcing scalable system - paper submitted to International Conference Communications 2018 (Politehnica University of Bucharest, Romania Military Technical Academy, IEEE Romania), June 2018.

[12] Michael Copeland, What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning? https://blogs.nvidia.com/ blog/2016/07/29/ whatsdifference-artificial-intelligence-machine-learning-deep-learning-ai/ [13] Hans-Dieter Wehle, Machine Learning, Deep Learning and AI: What’s the Difference ? https://www.researchgate.net/publication/318900216, July, 2, 2017 [14] Victor Greu, Developing information and communications technologies with more artificial

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intelligence, using artificial intelligence, when internet of things is “intelligence everywhere”-(Part 1), Romanian Distribution Committee Magazine, Volume 7, Issue 4, Year 2016.

[15] ***, National Weather Service Enterprise Analysis Report Findings on changes in the private weather industry, June 8, 2017,10https://www.weather.gov/ media/about/Final_NWS%20Enterprise% 20Analysis%20Report_June%202017.pdf [16] Victor Greu, Information and communications technologies go greener beyond IoTbehind is all the earth-Part1, Romanian Distribution Committee Magazine, Volume 7, Issue 2, Year 2016 [17] Anas Baig, Artificial Intelligence Can Solve The Biggest Crowdsourcing Problem, Aug 11, 2017, https://crowdsourcingweek.com/blog/artificial-intelligence-can-solvebiggest-crowdsourcing-problem/ [18] Victor GREU, Evaluating the development steps based on life-inspired strategies for the information and communications technologies, Romanian Distribution Committee Magazine, Volume 2, Issue 4, Year 2011 [19] Niko Mohr, Holger Hürtgen, Achieving business impact with data - A comprehensive perspective on the insights value chain, Digital McKinsey 04.2018 Copyright © McKinsey & Company www.mckinsey.com [20] Mike Sirius, How artificial intelligence and innovation will interact, June 5, 2017, Idea Drop Ltd,http://ideadrop.co/artificial-intelligence-innovation/ [21] Victor Greu, Tomorrow’s paradox: refining knowledge by smarter information and communications technologies while humans tend to become a limited factor of performance, Romanian Distribution Committee Magazine, Volume 7, Issue1, Year 2016.

[22] Nelson Sizwe. Madonsela, Paulin. Mbecke, Charles Mbohwa, Integrating Artificial Intelligence into Data Warehousing and Data Mining, Proceedings of the World Congress on Engineering and Computer Science 2015 Vol II WCECS 2015, October 21-23, 2015, San Francisco, USA [23] ***World Economic Forum White Paper Digital Transformation of Industries: In collaboration with Accenture, Digital Enterprise January 2016, http://reports.weforum.org/digital-transformation/wp-content/blogs.dir/94/mp/files/ pages/files/digital-enterprise-narrative-final-january -2016.pdf [24] Jiandong Zhang, Xiaoyu Qu, Arun Kumar Sangaiah, A Study of Green Development Mode and Total Factor Productivity of the Food Industry Based on the Industrial Internet of Things ,IEEE Communications Magazine, Volume: 56 Issue: 5, 2018 [25] Victor GREU, Information and Communications Technologies are Learning from Nature’s “Research” to Push the Performance Limits, Romanian Distribution Committee Magazine, Volume 5, Issue 1, Year 2014 [26] Bhupinder Kour, The Rise of Machine Learning and AI is Improving Lives in 2018, https://www.smartdatacollective.com/rise-of-machine-learning-ai-improving-lives/ [27] Eliza Strickland, Making Medical AI Trustworthy, IEEE Spectrum, August 2018.

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Minimalism: A Marketing Approach of Creativity and Simplicity

Cosmin TĂNASE Abstract When people want to simplify their lives, they just eliminate the elements they do not need.

That means less elements create room for greater and more creative expression. There is a kind of emancipation in limitation. Less decisions have to be made. People begin to focus inward more, on that organic creativity within the shell, and that is where the pure element is. Minimalism represents a proper reaction to complexity whereas simplicity relies directly on understanding the convolution and this is an important difference. One is about the surface, about the stuff and the other is about our experience and requires a deep appreciation of how things work so as to make them just simple enough to understand. The “less is more’’ motto revival in today’s world isn‘t just happening in marketing. It is everywhere and that should not come as a surprise: the same need for seamless experiences and a fast and simple path to the information people want expands into all domains where they are involved and that is everywhere indeed — in an increasingly digital and very connected surrounding.

Keywords: Ad Design, Minimalistic Marketing, Simplicity, Minimalism, Creativity JEL Classification: L81, M31

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Minimalistic marketing is an approach where unnecessary marketing practices and elements are eliminated and marketers focus on the mandatory things whic h are important.

This marketing approach means to work on the ultimate marketing objective which is necessary for that product. Here the marketers need to understand the human nature and according to that they design the advertising campaign and logos to capture the attention of the audience. “Less is more” is the motto of minimalistic marketing. Marketers’ main concern is to provide greater quantity of information, articles, posts, tweets, impressions but at the same time their motto “less is more” will not be diverted according to the context. Minimalistic movement is taking away all the unnecessary elements and focuses only on the exact needs.

What actually “simple” means from the consumer’s point of view can be very difficult to understand, but people nowadays demand it. Simple does not mean lack of information. It means being creative, innovative. It means customer-centric with precision and it means smart with trend as in thinking out of the box, understanding what the customer wants and using smart data in an actionable way.

Significance of minimalistic marketing Minimalism can be described as the removing of all unnecessary elements and focusing on what needs to be there and is essential. In this sense, minimalism marketing encourages the exact purpose. While minimalism at first sight appears simple on the outside but a lot of thought, practice and time goes into the production and actually development of a minimalistic idea.

Brand identity plays an important role in minimalism, a minimal brand can be incredibly useful when it comes to creating a unique brand identity. By keeping the logo simple and the colour palette very minimal, it can become flexible and easy enough to be used throughout the rest of the other branding seamlessly, creating a consistent and very attractive and memorable brand.

Minimalism also allows for the spatial relationship of your design in a way you might not have think before. Consider how your design interacts with other elements of other brands and to create a wider design, just as these business cards designed by Trevor Finnegan do when they precisely lined up.

Minimalism has continuing to stay a significant trend throughout 2018 and 2019 in additional ways than one. Artistic movement influences wardrobe, home style and regular

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lifestyle wherever there is minimalism, there's deliberation, clarity and purpose. A simple approach will be compelling thanks to advertising and captures the audience‘s attention. In design, artistic movement concentrates solely on the necessities by keeping the arrangement clean and straightforward.

Four important areas to consider when simplifying Personalised ad design 1. CUT THE CLUTTER It is critical just not to overwhelm viewers with too much information in a packed space. Keeping in mind that minimalist approach means “less is more” which include the only essential information the audience needs to know about the service or product. After captured the attention of the viewer, the company only has a particular amount of time before the customer will move on to the next eye-catching ad.

2. LIMIT THE COLOUR PALETTE Limiting the amount of colours used in an advertisement will help with avoiding visual noise. Fewer colors will cause less mental overload which can draw the eye of the viewer to the most important content within the advertisement.

An example would be a monotone colour palette also and can be different. Using a single colour, followed by tints and tones of that colour creates an attractive composition that is simple for the viewer to understand.

3. STRAIGHTFORWARD TYPOGRAPHY Similar to the way touse -in advertising, the same goes for typography. A vital rule of thumb is limiting the ad to just couple of fonts.

This will communicate the message in a way that is eye catchy, effective and easy to read by audience, all in a particular time frame.

4. WHITE SPACE it plays a role in the way your advertisement is received, the insufficient white space can end in associate unbalanced style and visual litter. Each component is ought to operate along to avoid competitors for visual attention.

Composing the text and image content fittingly with white space in mind can highlight the necessary items of the style. Same like the colour selection and placement of visual components generate a chance for a powerful focus and the attention whic h gravitate towards the brand, so every part of the style desires a touch space to breathe.

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Where Did the Minimalist Design Trend Come From?

Minimalism was a rejection of the extraordinarily subjective styles and works of abstract expressionism. By distilling a product, painting or subject all the way down to its clean necessities, minimalists needed to showcase its true kind.

Action painting is associate degree approach to style that mixes self-denial and emotional intensity, that produces styles that some see as chaotic, rebellious, and even school of thought. Unsurprisingly, naturalness (or a minimum of the impression thereof) is that the main feature of action painting. Minimalism, in stiff distinction, takes form, colour, and area that reduces them to such simplicity to attain their essential nature.

Conclusion Minimalistic Marketing is sequential. It is a team work where everything is organised and simple so that work accomplish easily. It represents the crux of marketing through logos, design, branding elements etc. which tend to capture the attention of audience.

Marketers want to attract the attention of viewers for a fraction of a s econd on each element so that they can deliver the message or maket impact on their mind which enables the recall of the brand later. Visual perception will enhance the marketing of that brand so marketers should understand the customers of that product fi rst and gather information for that brand after that they provide information and awareness about that brand in their marketing strategy.

Minimalism isn‘t just about complete lack of explicative elements, but rather it is a careful choice of where and when to use them effectively by working an illustrative element that relates directly to the brand name into a unique logo, similar to the way most of companies have done with their brands, we can create a very visual, and yet with very minimal design.

References [1] Battock, G (2014). “Minimal Art: a critical anthology”, pp 161–172, Harlow Publishing.

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[2] Cerver, F. (2017). The Architecture of Minimalism. New York: Arco. ISBN 0- 8230-6149-3.

[3] Espartaco, C. (2019). “The Experience of Limits.” Buenos Aires: Ediciones de Arte Gaglianone.

[4] Hubble, E . (2016). “Minimalism in Marketing”, https://www.ve.com/blog/minimalism-inmarketing-17-brands-getting-it-right [5] Keenan, D. and Nyman, M. (2011). "Claim to Frame". The Sunday Herald.

[6] Marzona, D. and Grosenick, U. (2014). “Minimal Art”, pp 12.

[7] Parasjeet, S. (2017). “The Art of Minimalist Marketing” , http://www.dignitasdigital.com/blog/theart-of-minimalist-marketing/ [8] Pickton, D. and Broderick, A. (2005). “Integrated Marketing Communications”. Harlow: Pearson Education.

[9] Schenker, M. (2018). “The Minimalist Design Trend: Why Less Is More”, https://creativemarket.com/blog/minimalist-design-trend [10] Warden, S. (2017). “Keeping it Simple: Why Minimalist Design is Taking Over the World”.

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Retailers’ Reinvention in Harmony with the Shopping Tendencies Theodor PURCĂREA

Abstract Challenged to build high value retail experiences, retailers are investing accordingly, struggling to better understand customers’ context and offer them a true Omni channel experience, developing POS capabilities and becoming more technology-enabled. It is interesting to note within this context the impact of Amazon’s involvement in U.S. grocery ecommerce’s fierce competition with Walmart, Kroger etc., a competition which stimulates the innovation. New research confirmed that: BOPIS is considered the most valuable aspect of the retail shopping experience, and that reputed retailers are planning for leveraging BOPIS, which ensure clear benefits for both customers and retailers, and can be enabled with the help of an adequate AI-powered personalization engine integrated with the in-store customer engagement analytics; retailers need to prepare for the impact of automation and AI technologies across all core functions, taking into account the workforce implications and the shopping tendencies defined by generational gaps, the shopper behavior being reinvented by the digital revolution. All this evolution also reconfirmed that the next-generation retail merchandising will be driven by analytics and digital, organizational enablers being essential in this retailers’ approach.

Keywords: Experiential Retailing; Business Models’ Transformation; Next-Generation Point of Sale; Technology-Enabled Revolution in CX and Efficiency; Shopping Tendencies JEL Classification: L81, L86, M31, Q55

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Is there a key for key for “Next level” in-store experience? The reinvention of retail In June last year we show, among other aspects, how retailers are challenged to ensure a smart and seamless shopping experience in the current digital landscape, using proper digital marketing strategies, considering both marketing’s hidden treasure of CPG companies, and the entrance of Amazon into grocers’ industry and its true technological battle with Walmart. We underlined within this framework retailers’ imperative of creating a digitally connected environment. (Purcarea, 2018) Awareness, sales, and loyalty are clear targets for the physical spaces of the U.S. best-inclass retailers which are acknowledging that brick and mortar stores are still living and healthy, within the context in which from the total retail sales ecommerce sales accounted for just 9.9% in the fourth quarter of 2018 (according to the U.S. Census Bureau), and this beyond all the wellknown store closures and debate on the so-called death of physical retail. There are significant current pledges for combining tried-and-tested strategies with modern and digital solutions, considering this balance as the key for “Next level” in-store experiences (see: The Disney Store for Delight; Atelier Beauté CHANEL for Ease + Elegance; Showfields for Eye-Catching; Athleta for Partnership; Target for Niche Labels; Sephora: Human + Tech). (Nicasio, 2019) Experiential retailing confirms consumers’ curiosity and pleasure of seeing, touching and feeling beautiful things, their emotionally engagement with authentic stories. (Stein, 2019) In the opinion of the retail designer and trend forecaster Sanford Stein (author of the book “Retail SchmetailTM”, Beaver’s Pond Press, February 14, 2014) a meaningful and memorable customer experience (CX) has three distinct levels of experience (engagement, immersion, and transformation), being necessary a mix of great skill and much orchestration in order to move customers right up the experience ladder (what the best brands are often able to do it). According to him, building high value retail experiences involves enabling face-time between brand ambassadors and customers with the help of new brand-stands behaving as much like media as store (ensuring this way a more comprehensive view of the customer’s purchasing behavior on and offline, enabling personalization, and improving customers’ movement from engagement to immersion, and the blending of online with offline selling). Retailers need: to invest in highly narrative spaces with short half-lives, considering the impermanence of the pop-ups which is drawing out the reaction to Fear of Missing Out (FOMO) factor influencing those customers expecting the unexpected (mainly Gen Y and Z); to move customers across the experience spectrum by creating emotion around retailers’ brands (using a pull marketing approach, deploying solution-based selling); to develop Consumer Engagement Spaces (CES), which are mixing aspects of socialization, cultural relevance and multifaceted engagement; to face the Omni channel world by offering Display Only Retail Environments (DORE), which ensure visitors assisted and unassisted selling (on the basis of digital and physical tools).

Recent opinions underline that the business models are forced to transform by Millennials’ shopping behavior all over the world, being necessary a new marketing’s mindset to

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convert this Gen Y (who also enjoy shopping in brick and mortar stores – not only online – if they perceive an engaging shopping experience) to loyal customers. The majority of retail sales in Southeast Asia, for example, are made up by the traditional retail, but the small mom and pop stores are reinvented thanks to the new retail which ensures (with the help of new inventory selected by algorithms) true complete store makeovers, so as that the modern retailers are competed at every corner by a lot of “everything stores”. (Solvsteen, 2019) The right approach of Millennials by the physical stores in this new environment is seen as being either experiential or functional, or combining both, but delivering simplicity, authenticity, and intimacy. What presupposes to understand customer context, ensuring relevant and personal engagement at every touchpoint in the customer journey (the right interaction at the right moment).

Transforming the in-store experience with the help of a next-generation point of sale As argued by McKinsey’s representatives in May this year, the future of retail belongs to companies that can offer a true Omni channel experience, retailers being challenged to transform the in-store experience by using emerging technologies and adequate data on their customers wanting personalized shopping experience (which can increase store revenues by 20-30%), the shopping experience being reshaped by technologies (shopping convenience being powered by technology, as shown in the figure below).

Figure no. 1: The consumer’s journey is evolving Source: Adhi, P., Burns,T., Davis, A., Lal, S. and Mutell, B. (2019). A transformation in store, McKinsey & Company, May, p. 3 (work cited)

McKinsey’s representatives also demonstrated that there is a clear financial impact of instore technology in the store of the future, and expressed their belief that technology will likely double store profitability (EBIT margins - the operating earnings over operating sales), considering the benefits added by an improved CX, a better employee engagement, and an easier-to-run store (see the figure below). McKinsey’s recommendation for retail leaders is to be already prepared for a technology-enabled revolution in CX and efficiency. (Adhi et al., 2019)

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Figure no. 2: Technology will likely double store profitability Source: Adhi, P., Burns,T., Davis, A., Lal, S. and Mutell, B. (2019). A transformation in store, McKinsey & Company, May, p. 5 (work cited)

On the other hand, observing with care consumers’ desires to be more environmentally conscious, the majority of retailers (as revealed by a January 2019 report from online resale marketplace thredUP) want to advance their company’s circular fashion efforts by 2020, the implementation of a circular business model presupposing to consider both their product offering and how it fits into the fashion ecosystem. (Koch, 2019) More recently, new research revealed that for higher-priced markets the circular business models is most profitable (applying to all), mid-level and premium markets having also the possibility of benefitting of this model (a report from Accenture Strategy and Fashion for Good, May 2019). The implementation of the circular business initiatives in the fashion industry has been introduced by companies with the view to cut back on their carbon footprint and to appeal to conscious consumers.

Incisiv Inc. in partnership with Manhattan Associates provided this year a so-called “The Next-Gen Point of Sale Buyers’ Guide”, which prioritized features and capabilities useful in the selection criteria of a company’s point of sale. From the very beginning this guide underlined that the physical stores changed forever their role by: fitting into shoppers’ lives more seamlessly, offering customers personalized service, being profitable hubs of Omni channel fulfillment, and creating an emotional bond with shoppers. According to this guide: ▪ retailers’ next-gen POS must be both functionally rich (enabling the business to create brand ambassadors, drive profitable fulfillment, and delight customers with personalized service), and technologically modern (offering rapid innovation, risk-free resilience, and future-proof architecture); ▪ there are clear POS capabilities for CX roles (focused on redefining the CX) in context of key business needs, as shown in the table below:

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Table no 1: Next-Gen Point of Sale Capabilities for Customer Experience Roles in Context of Key Business Needs

Source: The Next-Gen Point of Sale Buyers’ Guide, Incisiv Inc. in partnership with Manhattan Associates, 2019, p.

6 (work cited)

▪ there are clear POS capabilities for brand management roles (focused on elevating the shopper– brand relationship) in context of key business needs, as shown in the next table below: Table no 2: Next-Gen Point of Sale Capabilities for Brand Management Roles in Context of Key Business Needs

Source: The Next-Gen Point of Sale Buyers’ Guide, Incisiv Inc. in partnership with Manhattan Associates, 2019, p.

8 (work cited)

Of course, there are also other POS capabilities revealed by this guide, such as: for store ops & supply chain roles (focused on executing CX flawlessly at scale), for solution architecture roles (focused on creating an agile platform to support future growth), and for executive management roles (focused on maximizing business value), all of them in context of key business needs.

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Drones’ use for home deliveries and the struggle of the early mover status. Could be a connection including with the involvement in US grocery ecommerce? Adequately enabling BOPIS On the occasion of the Amazon re:MARS 2019 AI & ML Conference (a new global AI event on Machine Learning, Automation, Robotics, and Space; this new event was inspired by the well-known event MARS hosted by Jeff Bezos dedicated to advance a golden age of innovation), which took place at the beginning of June this year, was announced a new Prime Air delivery hybrid drone functioning as part helicopter and part plane. The recent discussion questions launched by RetailWire (Retail News and Analysis) brought to readers’ attention interesting comments from practitioners with regard to: (Anderson, 2019) the uncertainty about the drone delivery services’ future considering the many challenges with this type of delivery; the lack of real “highways” for drones to stick to; the risks related to the air full of delivery drones; the need of exploring both the technologies and the potential regulatory and cultural barriers involved in the automated delivery; the need of a better system taking into account the carbon footprint of human appetite for goods etc.

It is interesting to note within this context the impact of Amazon’s involvement in U.S. grocery ecommerce (where one of the key drivers of this fastest-growing product category online is “Buy Online, Pick Up In-Store” - BOPUS or BOPIS), Amazon being ranked as No. 1 digital retailer for US online grocery sales in 2018, followed by Walmart and Kroger. (Koch, 2019) According to a June 2019 report from Edge by Ascential, the considerable increase of Amazon online grocery sales in 2018 was fueled by the etailer’s evolving omnichannel grocery strategy.

It is known that Amazon: expanded a year ago its same-day Whole Foods delivery service Amazon Prime Now to 88 US markets and by 2021 it will open thousands of Amazon Go stores; following its other Key offerings (in-home delivery/launched in 2017, and in-car delivery/launched in 2018), it announced in April 2019 its in-garage delivery program – “Amazon Key for Garage” – to Prime members in carefully choosen US cities. And taking into account the recently introduced “InHome” groceries delivery (the Walmart employee delivering groceries directly to the shopper’s fridge), there is no doubt that the competition is fierce and it stimulates the innovation.

It is also known that four years ago Amazon began to introduce U.S. locations for sameday pickup, and two years ago launched “Instant Pickup” points (BOPIS) around five college campuses, planning to add the program to more sites by the end of 2017. (Dastin, 2017) As shown by Reuters at that time this Instant Pickup program targeted impulse buys, appearing (as a cited analyst from Morningstar highlighted) as a natural extension of Amazon’s larger push into the grocery deliveries, also entering in competition with vending machine services.

A February 2019 report from iVend Retail Globally confirmed that for more than four in ten consumers BOPIS is considered the most valuable aspect of the retail shopping experience, big-box retailers – such as Walmart (announcing announced its Grocery Pickup offering) and

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Target (offering its Curbside Pickup, allowing its store employees to bring out the products customers ordered to their vehicles) – announcing their plans for leveraging BOPIS. (Ewald, 2019) And as argued very recently by a representative of Reflektion (Real-Time Intelligent Personalization Platform), BOPIS ensure clear benefits for both customers (flexible fulfillment; avoidance of the shipping costs, inspection of the product) and retailers (solution for online cart abandonment; stimulus for impulse buys or some window-shopping; generation of more crosssell orders through interesting offers via personalized promotional emails or messages). And taking into account the more and more higher customers’ expectations (for personalization, meaningful experiences, and relevant engagement) from retail marketers, in the case of those retailers with both offline and online presence BOPIS can be enabled with the help of an adequate AI-powered personalization engine (which powers the eCommerce experience for shoppers) and by integrating this personalization engine with the in-store customer engagement analytics (completing the online-offline-online feedback loop by shaping the future online engagement for those customers via search or recommendations).

It is well-known that with a view to know who the company’s ideal customers are and give them a superior customer engagement experience, companies need to profile their database.

Going on this way they can not only use than that information accordingly to generate additional sales from their existing customers, but also to find new customers interested in buying from such companies. (Allan, 2019) Coming back to the above mentioned Reflektion (Real-Time Intelligent Personalization Platform), it is also worth underlining their pledge for delivering connected shopping experiences across all touchpoints (search, recommendations, pages, personalized content, email), their approach presupposing retailers’ struggling to deliver on the promise of eCommerce personalization (through 1:1, real-time, AI and NLP-powered personalization across these touchpoints) by implementing strategies improving conversion rates (see the figure below). (Verma, 2019)

Figure no 3: Strategies improving conversion rates Source: Verma, G. (2019). (Final) Part 5 – Practical tips for growing your eCommerce conversion rates, Reflektion, June 4 (work cited)

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On the other hand, we should not forget: • (as the French Professor François Lévêque showed in May this year) Amazon’s appetite for competitors and former associates, within the context in which competing with it is far from being simple; Lévêque argued that Amazon uses all three models generally used by the brickand-mortar or online retailing (reselling products purchased from third parties, mainly for popular products; a marketplace with its very specific network effects; partial vertical integration), shifting its position over time (looking at good expectation of higher added value), prioritising growth over profit, while learning continuously from what is happening on the marketplace; (Lévêque, 2019) • (as demonstrated by Ralf Seifert, Professor of Operations Management, IMD Business School and Richard Markoff, Supply Chain Researcher, EPFL- École Polytechnique Fédérale de Lausanne - Swiss Federal Institute of Technology in Lausanne) that Amazon’s most of the profit in 2018 was not from retail activities, more operating income being generated by Amazon Web Services (a cloud-hosting business unrelated to ecommerce); the small margins or logistical challenges of the so-called CRaP products (“cannot return a profit”, such as bottled water, fizzy drinks and snack foods) will put the online giant to choose between charging more for them or delisting them; Walmart’s new approach to CRaP products (in order to make online sales more profitable) is to hide these products from view in Walmart consumer search results, showing them as out of stock alongside alternatives); The new report by the Capgemini Research Institute, “The last-mile delivery challenge: Giving retail and consumer product customers a superior delivery experience without impacting profitability” (which showed that retailers’ profitability will be will hurt by their efforts of meeting demand and service-level expectations from consumers shifting to online ordering and expecting frequent deliveries), revealed that online grocery orders have a negative margin of about 15%. (Seifert and Markoff, 2019) Instead of conclusions In our last issue we have seen that digital transformation, new shopping behaviors and values, Omni experience, in-store personalization, and retail’s convergence are some of the retailers’ current topics in discussion. We also underlined the need to rethink strategy assumptions by better understanding CX, caring for customers and inspiring their loyalty.

(Purcarea, 2019) At the top of every retail management team’s agenda, highlighted McKinsey’s representatives in May this year, should be to address automation (preparing for the impact of automation and AI technologies across all core functions) – which will reshape retail business models and the broader value chain – and the workforce implications (a workforce empowered by real-time data and analytics). (Begley et al., 2019) Within this context it was showed that automation will have an impact on most elements of the merchant role (see the figure below):

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Figure no 4: Automation will have an impact on most elements of the merchant role Source: Begley, S., Hancock, B., Kilroy, T. and Kohli, S. (2019). Automation in retail: An executive overview for getting ready, McKinsey & Company, May, p.4 (work cited)

Retailers also need to take into account the shopping tendencies defined by generational gaps, tracking closely both digital (who are using almost any technology making their buying process more speeder and self-sufficient, being mobile apps’ or social media’s users) and traditional consumers (who are driven more by cost and ease of use), both of them: researching prices online before they visit a store, sharing experiences via word-of-mouth, and looking for a wide range of simple and value-driven experiences. (eMarketer Retail, 2019) There is no doubt that the physical and digital worlds are brought together by the Omni channel, a huge factor shaping purchases being represented by consumers’ pre-store preferences, the shopper behavior being reinvented by the digital revolution (the digital retail landscape being enabled by technology) and that we are witnessing a continuous evolution of new disruptive e-commerce models. (RetailWire, 2019) It is also worth remembering finally what McKinsey’s representatives demonstrated a year ago the fact that the next-generation retail merchandising will be driven by analytics and digital. (Begley et al., 2018) They underlined within this context that with the view to setting up next-generation merchants for success the following organizational enablers will be critical: Digital-talent management (key elements: talent quality, recruiting, and value proposition); Digital culture (key elements: risk culture, leadership style, and vision and values); External networks and partnerships (key elements: partnerships and expert networks); Key performance indicator (KPI)-based steering (key elements: measurement and communication, steering, and performance culture); Performance management (key elements: continuous improvement culture, collaboration and process automation).

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References Adhi, P., Burns,T., Davis, A., Lal, S. and Mutell, B. (2019). A transformation in store, McKinsey & Company, May. Retrieved from https://www.mckinsey.com/business-functions/operations/our-insights/a-transformation-instore?

Allan, J. (2019). 7 reasons why you should profile your customer database, February 9. Retrieved from https://jamie-allan.com/6-reasons-profile-customer-database/ Anderson, G. (2019). How long before Amazon launches its fleet of drones? RetailWire, Jun 07. Retrieved from https://www.retailwire.com/discussion/how-long-before-amazon-launches-its-fleet-of-drones/ Begley, S., Hancock, B., Kilroy, T. and Kohli, S. (2019). Automation in retail: An executive overview for getting ready, McKinsey & Company, May. Retrieved from https://www.mckinsey.com/industries/retail/ourinsights/automation-in-retail-an-executive-overview-for-getting-ready?

Begley, S., Fox, R., Lunawat, G. and MacKenzie, I. (2018). How analytics and digital will drive next-generation retail merchandising, McKinsey & Company, August. Retrieved from https://www.mckinsey.com/industries/retail/ourinsights/how-analytics-and-digital-will-drive-next-generation-retail-merchandising Dastin, J. (2017). Amazon adds 'Instant Pickup' in U.S. brick-and-mortar push, Reuters, August 15. Retrieved from https://www.reuters.com/article/us-amazon-com-pickup/amazon-adds-instant-pickup-in-u-s-brick-and-mortarpush Ewald, R. (2019). Stronger Together: BOPIS and AI-powered Personalization, Reflektion: Real-Time Intelligent Personalization Platform, June 17. Retrieved from https://reflektion.com/now-trending-bopis/ Koch, L. (2019). Can a Circular Business Model Be a Profitable and Sustainable Approach for Your Brand? eMarketer, Jun 2. Retrieved from https://www.emarketer.com/content/can-a-circular-business-model-be-aprofitable-and-sustainable-approach-for-your-brand?

Koch, L. (2019). Amazon, Walmart and Kroger Lead US Grocery Sales Online ... How Do They Do It? “eMarketer Retail", retail_newsletter@emarketer.com, Tue, June 18, 2019 2:12 pm Lévêque, F. (2019). Amazon’s bottomless appetite, The Conversation, May 14. Retrieved from https://theconversation.com/amazons-bottomless-appetiteNicasio, F. (2019). Rack to the Future, The Next Brick, May 15. Retrieved from https://www.thenextbrick.com/innovation-in-retail-stores/rack-to-the-future?

Purcarea, T. (2018). Retail digital marketing strategies, Romanian Distribution Committee Magazine, Volume 9, Issue 2, June, pp. 30-40 Purcarea, T. (2019). Retailers’ Current Topics in Discussion, Romanian Distribution Committee Magazine, March 2019, Volume 10, Issue 1, pp. 38-46 Seifert, R. and Markoff, R. (2019). Online shopping: why its unstoppable growth may be coming to an end, The Conversation, Retrieved from https://theconversation.com/online-shopping-why-its-unstoppable-growth-may-becoming-to-an-end-118616?

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Solvsteen, R. (2019). How to Make Your Brand Matter in the New Retail Paradigm, Ogilvy, May 20, article originally published at Campaign Asia. Retrieved from https://www.ogilvy.com/feed/how-to-make-your-brand-matter-inthe-new-retail-paradigm Stein, S. (2019). From Storing to Exploring, The Next Brick, May 14. Retrieved from https://www.thenextbrick.com/innovation-in-retail-stores/from-storing-to-exploring-retails-reinvention?

Verma, G. (2019). (Final) Part 5 – Practical tips for growing your eCommerce conversion rates, Reflektion, June 4.

Retrieved from https://reflektion.com/part-5-conversion-rates/ *** The Next-Gen Point of Sale Buyers’ Guide, Incisiv Inc. in partnership with Manhattan Associates, 2019.

Retrieved from https://www.manh.com/resources/white-paper/point-of-sale-buyers-guide *** https://remars.amazon.com/ *** Digital vs. Traditional Consumers: How Generational Gaps Define Shopping Tendencies, "eMarketer Retail" retail_newsletter@emarketer.com, Fri, April 26, 2019 2:11 pm *** Do you know the most important factors that influence your customer’s journey? RetailWire – Retail News and Analysis, May 29, 2019. Retrieved from https://www.retailwire.com/resources/do-you-know-the-most-importantfactors-that-influence-your-customers-journey/

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Target Group Youth, ALDI China, World Leader ANUGA, Innovation Driver China, Eurasia, EECSA, Trade Innovation Cycles, Green Future, Wealth of Nations, AWC Gothenburg, and Land/Food/Nature Bernd HALLIER

Prof. Dr. Bernd Hallier, President of the European Retail Academy (ERA: http://www.european-retailacademy.org/), an Honorary Member of the Romanian Distribution Committee, and distinguished Member of the Editorial Board of “Romanian Distribution Committee Magazine” attracted our attention on great events happening in the second quarter 2019, and allowed us to present them. It is also worth remembering that: immediately after visiting Romania for the first time on the occasion of the 24th International Congress of the International Association for the Distributive Trade (AIDA Brussels), Prof. Dr. Bernd Hallier sent us, in May 2008, a memorable letter we have referred initially in the Journal of the Romanian Marketing Association (AROMAR), no. 5/1998, and also later, in 2010, in the first issue of the Romanian Distribution Committee Magazine; the Romanian-American University has awarded Prof. Dr. Bernd Hallier a “Diploma of Special Academic Merit”; the “Carol Davila” University of Medicine and Pharmacy, Bucharest, has awarded Prof. Dr. Bernd Hallier a “Diploma of Excellence”.

Target Group Youth Reviewing the historical Nobel activities at the 28th Associations’ World Congress in Gothenborg/Sweden Laura Sprechmann from Nobel Media AB pointed also out that for the

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penetration of the brand/ideas of Nobel youth groups are an interesting target-group.

The Nobel organization for example collaborates with the Telenor Youth Forum to bring together young leaders around the world to develop digital solutions that reduce inequality and empower scientists. The European Retail Academy reports about vocational training for young people and about youth activities mainly at its special Site www.european-retailacademy.org/EUCVOT/.

ALDI China ALDI (Albrecht Discount) has its roots in Germany with a success business history of more than 100 years. In Germany ALDI is the benchmark for the store-format/marketing of discount; in the UK ALDI was just rated by consumers as the best supermarket; in China ALDI now has launched its first two pilot-stores bringing high quality products and an unique life-style to the customers.

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For Prof. Dr. Bernd Hallier - watching ALDI since the mid 70ies - it is an example how in the world of globalization marketing-concepts should be adapted to local/regional/national habits and not just being copied from one country for other countries. His credo is “retail has to act locally”! ALDI started in China at April 2017 through its cross-border e-commerce store on Tmall, Now for the Chinese target-group the first two brick-and-stone pilot stores are customized/tailored and will be used for trials/tests to adjust by data collection/feedback the further optimization of ALDI's China approach.

World Leader ANUGA ANUGA is the abbreviation of the German heading “Allgemeine Nahrungs- und GenussmittelAusstellung” - shortly translated : exhibition for food products . It was founded in 1919 in Stuttgart, followed in the next years by exhibitions in Munich, Hannover, Berlin and Magdeburg.

In 1924 it moved to Cologne, which was also a political demonstration as at that time the Cologne area was separated after World War I from the rest of Germany. In fact it remained in that town up till today.

After World War II the fair was run bi-annually. Since 2003 ANUGA was labelled “10 special shows under one roof” aiming to promote ten food segments like “milk-products”, “meat”. In 2017 a total of 7400 companies from 107 countries exhibited at ANUGA - being visited by 165 000 food specialists from 198 countries. In 2017 also at ANUGA the special Site www.european-retail-academy.org/TUN was launched as a Thematic University Network to promote standards for food and food education. (Download Presentation).

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Innovation Driver China In Foshan City/Guangdong Province/China Prof. Dr. Bernd Hallier will be key-note speaker together with the Korean Nobel Laureate Prof.Dr.R.Chung at the Second International Twodimensional Code Industry Development Summit in August 2019. Among the technical aspects also politics play an important role: one of the Conference chapters will explore in a Round Table the possibilities to link actions of the Eurasian New Silk Road and Belt initiative and the infrastructure of the Great Bay Area - 23 presidents from Arab Universities and Ministers of Education will participate in that Round Table.

Two weeks later another high caliber Congress with 3.500 people will be organized in China by FARA and APRE. The Federation of Asian Retailers Association (FARA) was founded in 1989 to promote bi-annually in one of the member-countries an exhibition and congress (Asian Pacific Retailers Exhibition) : being in 2015 in Manila/Philippine and in 2017 in Kuala Lumpur/Malaysia. In 2019 the APRE will be organized in Chongqin/China - a destination also for travellers at the Yangtze River. This Conference is labelled by Prof.Dr.B.Hallier "as an Asian retail family event based on thirty years of peaceful cooperation beyond the borders".

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Eurasia At the XII Astana Economic Forum in Nur-Sultan /Kazakhstan Prof. Dr. Bernd Hallier pointed out the importance of the Eurasian Region for Peace Building and Economic Innovation. The forum was visited among others by the first President of Kazakhstan and the Presidents of Armenia and Georgia, the Managing Director of IMF Christine Lagarde, bankers like Herman Gref/Russia and Nobel Laureates.

In an interview with the business-channel Atameken Prof. Hallier explained that the area has developed within the last 12 years from a follower of innovation towards a driver. There can be seen in Eurasia dramatic investments into new technologies and human resources.

(More: https://www.youtube.com/watch?v=LqBXB2r8F4s)

EECSA The Eurasian Economic Club of Scientists (Association) was established in 2008 as an initiative of the first President of the Republic of Kazakhstan, Nursultan Nazarbayev. Among its members are the Nobel Laureates of Economics : Robert Aumann, Finn Kydland, Eric Maskin, Sir James Mirrless, Robert Mundell, John Nash (1928-2015), Edmund Phelps, Christop Pissarides and Edward Prescott. The European Retail Academy is represented at EECSA by the professors Hanon Barabaner/Estonia, Mikhail Fedorov/Russia and Bernd Hallier/Germany.

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In 2019 the 2018 Laureate Prof. Dr. Paul Romer (photo) reflected in Astana/Nur-Sultan about the proper role of governments within market economies which is of utmost importance to switch economic thinking from short-term profit-goals towards long-term sustainability-goals.

Trade Innovation Cycles Since 1800 the Trade Sector in Europe has run through major innovation cycles roughly every 25 years as Prof.Dr.B.Hallier showed in his former research on Applied Sciences. Now he defined the forthcoming changes for the distribution systems in the period 2025 - 2050.

Logarithms/AI will dominate the whole ordering, storing and distribution processes; the limitation of store-sizes will be challenged by unlimited assortments on Sales Platforms supported by the Internet of Things or influencers; neuro -marketing 02 will not only analyze the human brain of consumers but directly intervene in decisions; brick-and-stone markets will become cash-zone free; robotic delivery will go into first major field applications; know-how and investment will be bundled by across-sector mergers/joint ventures between retail/wholesale/data-pools/technology experts/ logistics/label-manufacturers and others: becoming partners in a world-wide â&#x20AC;&#x153;distribution machineâ&#x20AC;?.

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Green Future Originated in Sweden in 2018 political protests of young people started under the slogan â&#x20AC;&#x153;Fridays for Futureâ&#x20AC;?. Meanwhile it became a worldwide movement and shows how concerned the young generation is about the climate change and green issues.

It is worth mentioning that already in May 2013 student delegates on the way from Yekaterinburg/Russia to the Astana Economic Forum/ Kazakhstan drafted a declaration under the leadership of Prof. Dr. M. Fedorov/USUE and Prof. Dr. B. Hallier/ERA which was signed by the Nobel Laureate Prof. Dr. R. Chung/Korea as the first external professor - and which ended by the Site www.european-retail-academy.org/GGU/ (Global Green University) designed by Dr. Alina Pukhovskaya.

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Wealth of Nations After a nearly thirty years long hyper globalization cycle as a driver for innovation, worldtrade and modern liberal society now there is the danger of an upcoming period of protectionism by populist, protectionist and national oriented platforms.

The Astana Economic Forum 2019 will focus on dangers like trade-wars or Brexit for the world economy. This hot topic of the AEF is for Prof. Dr. Bernd Hallier a chance to defend open market systems and the global growth of the wealth of nations. The Conference will be opened by the first President of Kazakhstan, Nursultan Nazarbayev; key-speakers among others are Christine Lagarde/Managing Director IMF and Paul Romer/ Nobel Laureate Economics in 2018. More about the Program (Link).

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AWC Gothenburg The 28th Associations' World Congress (AWC) was organized in 2019 in Gothenburg/Sweden.

Behind the Association of Association Executives (AAE) are 24.000 members and subscribers located in Europe, Africa, India and other countries/regions.

Prof. Dr. Bernd Hallier (at the photo together with Damian Hutt/Executive Director of AAE) praised the Swedish hospitality and the excellent opportunity to learn beyond the borders of the own sectors like in Gothenburg for example by case studies presented by the Volvo Group/Paul Welander or the Nobel Media AB/Laura Sprechmann.

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Land/Food/Nature Under the leadership of the Faculty of European Studies and Regional Development of the Agrarian University of Nitra/ Slovakia and co-funded by the Erasmus+ Program of the European Union a conference focused the topic “Land Protection” (see also european-retailacademy.org/TUN). 10 countries presented in 21 contributions the status quo of the legal frame to use land and discussed the relationship between land for food, forestry, tourism, and the other sectors of human life.

Prof. Dr. Bernd Hallier presented his holistic trio of economics, ecology and ethics and underlined that “the factor land” should not only be evaluated in terms of economic output, but should include in a formula also the UN-sustainability goals and the fair distribution between the different social groups - even globally. One point in this concept could be the transformation of a percentage of farmers into “landscape rangers” to preserve historical landscapes and to work for anti-climate change activities (full lecture: Download).

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Léon F. WEGNEZ (by courtesy of) -“Lex mercatoria and international commercial arbitration”, “La Gazette Diplomatique”, No. 67, Novembre 2010, Brussels (in his capacity of Administrator Secretary General Diplomatic Club of Belgium) Sharing with our distinguished Readers a well-known source of usable and useful knowledge… Prof. Dr. h. c. Léon F. WEGNEZ is an Honorary Member of the Romanian Distribution Committee, and distinguished Member of the Editorial Board of our “Romanian Distribution Committee Magazine“. The distinguished Léon F. WEGNEZ was honored by the European Retail Academy (ERA) as the 2015 “Man of the Year”. Knowing our distinguished readers’ thirst for knowledge, we offer you, by courtesy of this remarkable personality, the above mentioned article published in the prestigious “La Gazette Diplomatique”, Brussels.

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Note from the Editor-in-Chief In a recent message received from Professor Léon Wegnez (see below a photo on the occasion of a DHC ceremony) we were informed that the painter Jean Wegnez (who is the brother of Professor Léon Wegnez) has just painted four very interesting paintings (“la Porte de Halle aux 4 saisons”), being also invited to find attached the painting of the Spring (see below this wonderful painting by courtesy of Professor Léon Wegnez).

It is also worth mentioning that: ● Jean Wegnez’ s painting entitled “Carousel of the Distribution” was displayed for the first time at the end of 2004 in the Conference Room of the famous “Palais d’Egmont”, Brussels (see below); ● four years ago, on May 5, 2015, within the generous framework offered by “Forum Art Business” (see also below) of the European Retail Academy - ERA (thanks to another distinguished Member of our Romanian Distribution Committee Magazine, ERA President Prof.

Dr. Bernd Hallier, who is publisher of “Culture and History of Commerce” and “Collectors and Sponsors of Commerce”), it was announced the opening of another painting exhibition of Jean Wegnez at Cercle Artistique de Spa (“the water city”).

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Source: “La Gazette Diplomatique”

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● Aurel DOBRE’s book – “Școala de la Miraveda” (School in Miraveda) – reviewed by Prof. Dr. Victor GREU

Note from the Editor-in-Chief In September last year we have commented on a successful book launch: http://www.crd-aida.ro/2018/09/prozatorul-aurel-dobre-scoala-de-lamiraveda/. As we remembered on another occasion, according to the reputed President of Harvard University (1834-1926): “Books are the quietest and most constant of friends; they are the most accessible and wisest of counsellors, and the most patient of teachers.” While according to the reputed American poet, essayist, and philosopher Ralph Waldo Emerson: “Nature and books belong to the eyes that see them”.

On the other hand, as according to our great Nicolae Iorga “Many writers make out of their soul a book and other books from that book”, while in the opinion of our great Alexandru Vlahuţă “Books are eternal voices in space”, it is our honor and pleasure to share with our Readers a recent review of this challenging book – “Şcoala de la Miraveda”, Autor Aurel Dobre – made by one of our respected colleagues, Prof. Dr. Victor Greu.

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MIRAVEDA NOASTRĂ - Puține gânduri inspirate de ... multă inspirație: “Școala de la Miraveda”Prof. Dr. Victor GREU 3 iunie 2019 JEL Classification: Y30

Eu cred că, pentru majoritatea oamenilor, a scrie o carte este un fel de a te arunca în valuri, pentru a te răcori (față de căldura vieții), fără a ști cât de adâncă sau cât de rece e apa, dar mai ales ... fără a ști să înoți prea bine. Există însă oameni care, fără a “ști”, au neobișnuita capacitate de a-și imagina și zugrăvi o realitate congruentă cu cea înconjurătoare, cu atâta talent nativ, încât pentru ceilalți oameni e dificil să le distingă.

Așa se face că astfel de oameni aleși pot oricând, adică mai devreme sau mai târziu, să adune masa critică și curajul pentru a scrie o carte surprinzător de originală și captivantă, raportat la timpul necesar acumulării.

Aurel Dobre este, după părerea mea, un astfel de scriitor, la care factorul timp reflectă o personalitate complexă ce înglobează atât o multilaterală capacitate de analiză și sinteză, în tot ce a întreprins, cât și covârșitoarea sa calitate de a comunica uman, cu căldură și spontaneitate.

Numai așa îmi explic eu modul în care a fost scris și ni se prezintă romanul său “Școala de la Miraveda” - povestea evoluției unui spirit înalt și a unui mic univers.

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Subiectivismul oricărei opinii are în cazul meu premise esențiale, legate cel puțin prin firul trainic al formării noastre comune, precum și prin cunoașterea “sevei” din Călărași a acelui mic univers de pe malul Borcei.

Cred că tocmai datorită acestui context, citind cu firească atenție cartea, am putut remarca atât realismul detaliilor cât și inefabila armonie în care acestea se împletesc cu episoade epice vizionare, într-un stil ce atestă talentul prolific al autorului.

Vorbind concret despre originalitate și valoare literară, am avut senzația că universul Miraveda are rezonanțe cu Macondo din romanul lui Gabriel García Márquez, Un veac de singurătate, așa cum stilul și savoarea descrierilor casei și acareturilor în care Elaur începe să vadă și să înțeleagă lumea au precizia și farmecul pe care Ion Creangă le-a arătat în mod magnific în Amintiri din copilărie, iar trăirile adolescentine ne amintesc de Ionel Teodoreanu și La Medeleni.

Dar evoluția spiritualității universale, prin cunoscuta revenire în spirală, poate fi observată și amintind aici cele spuse de Rodica Grigore (Revista Transilvania, 2014): “acea mult comentată şi apreciată coexistenţă a celor vii cu cei morţi, care a părut o noutate absolută în Un veac de singurătate, era cunoscută în spaţiul cultural latino-american încă din romanul lui Juan Rulfo, Pedro Páramo (1955)”.

Mai simplu spus, universul mirific al Miravedei, incluzând spiritul viu și plin de curiozitate al lui Elaur, dar și extensiile vizionare ale acestuia în sfere cosmice odată cu Nion, orbul Tinu, monstrul Codrus sau meditativa Lexia, nu fac decât să pună temelii valorice universale povestirii originale brodate pe vatra amintirilor din Miraveda.

Mai presus de toate acestea, așa cum aprecia și Stela Anghel citându-l pe R.M. Alberes, “tonul” acestei povestiri reprezintă componenta cea mai originală, care în cazul de față nu numai că te face să resimți emoția ce transcende timpul și spațiul în toate episoadele epice, ci te face și să citești captivat pagină după pagină.

La acest efect benefic contribuie însă și stilul direct al autorului, care nu este afectat nici măcar de regionalisme, ce sunt admirabil explicate sau ajutate de context. Între valorile universale pe care mesajul romanului le transmite epic, tuturor vârstelor, trebuie remarcate cele asociate mamei și familiei, prietenilor și tradițiilor. În mod deosebit, mama (Martia) este zugrăvită, prin mai multe procedee stilistice, indirect ca o icoană pilduitoare, care ne transmite nu numai tradiționala dragoste maternă, ci și înțelepciunea aplicată, prin puterea exemplului în lupta cu realitățile locului și simplitatea școlii vieții. Este remarcabilă însă și zestrea imaginației robuste, transmise indirect și lui Elaur, prin

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care Martia asigură progresul familiei și un viitor mai bun copiilor, adică depășirea condiției predestinate, asemenea celebrei mame a lui Ion Creangă.

Valoarea acestor mesaje, către universalitate, este protejată și prin grija autorului de a lega minimal micul univers al Miravedei (incluzând personajele), de timp, spațiu, tehnologie, filozofie sau politică, chiar dacă, spre exemplu, Noua Autoritate (comunistă) era arhicunoscută prin acțiunile ei nefaste.

Revenind și încheind, cum altfel decât subiectiv, pentru mine, ca prieten de aproape jumătate de veac de ne-singurătate al autorului, această apoteotică întreprindere a sa consolidează și adaugă punți de comuniune spirituală și umană, fiind și un cadou (MIRAVEDA noastră) prin care opune timpului imagini și emoții pe care tehnologia anilor ‘70 nu le putea fixa în memoria noastră colectivă decât prin prea puține fotografii și melodii ca Free electric band by Albert Hammond (prietenii știu de ce!). De aceea sper să se adauge și ... aceste puține gânduri.

(Prof. Dr. Victor Greu, 3 iunie 2019)

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