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Assessing the Effectiveness of Using Comparative Advertising in Premium Car Segment Mark Chen

Supervisor:

Mr. Graham Manville

Academic Year: 2010-2011 Presented for MSc. Digital Marketing This project is entirely the original work of student registration number 23952326. Where material is obtained from published or unpublished works, this has been fully acknowledged by citation in the main text and inclusion in the list of references. Word Count: 15,970 words


Abstract Because of the increasingly fierce competition in the global premium vehicle segment, comparative advertising, the one that was widely recognized as an unsustainable advertising strategy, has been adopted by a growing number of premium car manufacturers to strengthen their sales in some certain market. The central issue of concern of this research is the effectiveness of using comparative advertising: whether it is appropriate for using by premium car manufacturers. The researcher investigated the nature of comparative advertising in a carefully-selected theoretical framework existed in previous literatures, and then assessed its real performance in an empirical way through this primary study. Conclusions got in this research are of great value to advertisers working with premium car manufacturers. From a post-positivist perspective, the researcher conducted this study in a deductive approach. Data will be collected and analyzed in both qualitative and quantitative manners. Specifically, the qualitative phase comes first by the means of participant observation, providing researchers necessary contextual information to better understand the object we studied. The following quantitative phase begins with the distribution of questionnaires. By analyzing the obtained data in a strict statistical way, we’ve got a clear picture about the different effectiveness of using comparative advertising in various contexts, and for different group of customers, helping us to answer whether this kind of advertising is worthy to use for premium car brands. Based on this Empirical research, we found that the effectiveness of using comparative advertising is substantially varied in different markets. Since premium brands are usually seen as an extension of one’s identity, the customer’s prior brand experience and preference become much more crucial


in their advertising evaluation process. Therefore, comparative advertising, due to its drawbacks of decreasing brand credibility, is not recommended to use for premium car manufacturers.


Acknowledgement Looking back to the four-month hard work of studying and researching, it is like an amazing journey that teaches me all the things about academic research. It is a pleasure to thank all my friends who were by my side throughout this period of time. I am heartily thankful to my parents, who gave me the moral support when I encountered difficulties and felt depressed. I would also like to express my respect to Mr. Graham Manville, this person provided me necessary assistance and helped me with the research material. Lastly, I offer my regards and blessings to all of those who supported me in any respect during the completion of the project.


Contents Introduction

1

Ⅰ Literature Review

3

1 Advertising Overview

4

1.1 The Essence of Advertising

…………………………………………….4

1.2 The Function of Advertising

…………………………………………….6

2 How Advertising Works 2.1 The Framework for Studying

9 …………………………………………….9

2.2 The Taxonomy of Models …………………………………………………11 2.2.1 Market Response Models

……………………………………....11

2.2.2 Cognitive Information Models

………………………………….11

2.2.3 Pure Affect Models …………………………………………………11 2.2.4 Persuasive Hierarchy Models

………………………………….12

2.3 Perception/Experience/Memory Models

…………………………….13

2.3.1 Framing Perception …………………………………………………14 2.3.2 Organizing Memory …………………………………………………14 2.3.3 Enhancing Experience ……………………………………………14

3 Involvement, Emotion, and Affect in Advertising 3.1 The Concept of Involvement

16

…………………………………………….16

3.2 The Role of Emotion in Mediating the Effects of Advertising …………17 3.3 The Role of Affect in Advertising

……………………………………….18

3.3.1 People May Pay Greater Attention to Affective Advertising ……19 3.3.2 Affect May Enhance the Degree of Processing

……………...19

3.3.3 Affective Executives May Lead to More Positive Judgments of the


Advertised Message ……………………………………………………….19 3.3.4 Affective Executives May Be Remembered Better ………………20

4 Discussion of Comparative Advertising

21

4.1 Definition of Comparative Advertising

…………………………………..21

4.2 How Comparative Advertising Works

…………………………………..22

4.3 Advantages of Using Comparative Advertising ………………………...24 4.4 Brand Building and Comparative Advertising

………………………...25

Ⅱ Research Methodology

28

5 Research Methodology

29

5.1 Research Philosophy, Approach, and Strategy ………………………..29 5.2 Research Design ..................................................................................32 5.3 Data Collection

..................................................................................34

5.3.1 Participant Observation .............................................................34 5.3.2 Questionnaire ...........................................................................37 5.4 Validity and Reliability ………………………………………………………39

6 Data Interpretation

41

6.1 Respondent’s Profile ………………………………………………………41 6.2 Data Transformation ………………………………………………………44

Ⅲ Data Analysis and Discussion

46

7 Qualitative Research Stand

47

8 Quantitative Research Stand

48

8.1 H1-related Findings

………………………………………………………49

8.1.1 Descriptive Analysis of q3 and q6

……………………………..49

8.1.2 Paired Sample T-test for q4 and q18 ……………………………..50 8.1.3 Paired Sample T-test for q5 and q20 ……………………………..51 8.2 H2-related Findings

………………………………………….……………52


8.2.1 Test of H2-1

………………………………………………………53

8.2.2 Test of H2-2

………………………………………………………58

8.3 H3-related Findings

………………………………………………………93

8.3.1 Descriptive Analysis of q8 and q9

………………………….….94

8.3.2 Descriptive Analysis of q10 and q11 ……………………………..95 8.3.3 Descriptive Analysis of q14 and q15 ……………………………..95

Ⅳ Conclusion

97

9 Research Conclusions

98

Bibliography

101

Appendix Ⅰ Appendix Ⅱ Appendix Ⅲ


List of Figures Figure 1.1: Seven-step purchase process ………………………………………5 Figure 1.2: Three major functions of advertising………………………………….7 Figure 2.1: A framework for studying How Advertising Works …………………..9 Figure 2.2: The Perception/Experience/Memory model ……………………….13 Figure 3.1 Four-level audience involvement model ……………………………17 Figure 3.2: The communication model ……………………………………...……18 Figure 4.1: A framework for studying how comparative advertising works …..22 Figure 5.1: Elements of post-positivist paradigm

…………………………….31

Figure 5.2: The “hourglass” notion of research ………………………………….32 Figure 6.1: Age composition ………………………………………………………41 Figure 6.2: Gender composition Figure 6.3: Education level

…………………………………………………41

………………………………………………………42

Figure 6.4: Employment status

…………………………………………………42

Figure 6.5: Household yearly income ……………………………………………42 Figure 6.6: Nationality composition

……………………………………………43

Figure 6.7: Driving ability …………………………………………………………..44 Figure 8.1: Distribution of responses for q6 crossing q2 ……………………….58 Figure 8.2: Distribution of responses for q8 crossing q7 ……………………….60 Figure 8.3: Distribution of responses for q9 crossing q7 ……………………….62 Figure 8.4: Distribution of responses for q10 crossing q7

………………….64

Figure 8.5: Distribution of responses for q11 crossing q7……………………….66 Figure 8.6: Distribution of responses for q12 crossing q7

………………….69

Figure 8.7: Distribution of responses for q13 crossing q7

………………….72

Figure 8.8: Distribution of responses for q14 crossing q7

………………….76

Figure 8.9: Distribution of responses for q15 crossing q7

………………….78


Figure 8.10: Distribution of responses for q16 crossing q7

………………….80

Figure 8.11: Distribution of responses for q17 crossing q7

………………….83

Figure 8.12: Distribution of responses for q18 crossing q7

………………….86

Figure 8.13: Distribution of responses for q19 crossing q7

………………….88

Figure 8.14: Distribution of responses for q20 crossing q7

………………….91

Figure 8.15: Distribution of responses for q21 crossing q7

………………….93


List of Tables Table 5.1: Typology of participant observation researcher roles Table 8.1: Descriptive analysis of q3 and q6

…………….35

…………………………………50

Table 8.2: Paired sample T-test for q4 and q18 …………………………………51 Table 8.3: Paired sample T-test for q5 and q20 …………………………………52 Table 8.4: One-way ANOVA analysis for q2 against q3, q4, q5

…………….54

Table 8.5: Cross-tab analysis with Chi-square test for q2 and q6 …………….57 Table 8.6: Cross-tab analysis with Chi-square test for q7 and q8 …………….59 Table 8.7: Cross-tab analysis with Chi-square test for q7 and q9 …………….61 Table 8.8: Cross-tab analysis with Chi-square test for q7 and q10

……….63

Table 8.9: Cross-tab analysis with Chi-square test for q7 and q11……….65 Table 8.10: Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q12 ……………………………………………………………………………………67 Table 8.11: Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q13 ……………………………………………………………………………………70 Table 8.12: Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q14 ……………………………………………………………………………………74 Table 8.13: Cross-tab analysis with Chi-square test for q7 and q15

……….77

Table 8.14: Cross-tab analysis with Chi-square test for q7 and q16

……….79

Table 8.15: Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q17 ……………………………………………………………………………………81 Table 8.16: Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q18 ……………………………………………………………………………………84 Table 8.17: Cross-tab analysis with Chi-square test for q7 and q19

……….87

Table 8.18: Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q20 ……………………………………………………………………………………89 Table 8.19: Cross-tab analysis with Chi-square test for q7 and q21

……….92


Table 8.20: Descriptive analysis of q8 and q9

…………………………………94

Table 8.21: Descriptive analysis of q10 and q11 …………………………………95 Table 8.22: Descriptive analysis of q14 and q15…………………………….96


Introduction A brand is a set of expectation and association evoked from a company or product; it is how your customers, employees, shareholders etc. experience what you do. One ultimate objective in advertising design is to let your customers being able to tell the brand just through your ads. Most advertisers recognized the fact that advertising gradually informs the customer’s perception towards brands. Therefore, the company’s advertising strategies is always set to be aligned with its brand positioning. This is especially the case for premium car manufacturers, whose products are a combination of tradition, history, art, technology, and humanities. The car serve “more than their utility as a mode of transport, and invoke emotional and psychological attachments in the owner”, as Fraine (2003) suggested. A highly acclaimed premium car brand lives either on its superior product and service, or on a remarkable historic heritage. As a result, advertisers served for these brands usually put a lot of effort on enhancing customers’ experience by creating ads that best reflect the brand’s image. Comparative advertising, according to many previous studies (Diamond, 1978; Levine, 1976), was neither considered as a sustainable advertising strategy, nor a primary technique to build brands in the long run. However, more and more premium car advertisements have been observed to featuring comparative elements. Some manufacturers, especially for those who were in somehow competitive disadvantage positions, even place comparative advertising as their primary advertising strategy to claim market attention. As we thought, the purchase of cars is hardly an impulsive decision. Instead, it is more like a mix of both objective and subjective evaluation process, making it distinct from the process of buying commodity goods. Although some positive 1


effects of comparative advertising have been revealed by previous researchers (Wilkie and Farris, 1974; Giges, 1980; Muehling et al., 1990), its real effectiveness when being used in premium car segment is questioned by our researchers. Relevant literature on advertising, branding, and psychology has been considered by the researcher. Various advertising working theories, models of consumer purchase process, concept of audience involvement, and discussion about the role of affect and consumption-related emotions have been critically evaluated to identifying a proper framework for the present study. The objective of this piece of research is to accessing the effectiveness of using comparative advertising in premium car market. By conducting participant observation and survey research in a chronological order, the following research questions will be getting answered. 

Is there any difference in the effectiveness of comparative advertising being used in FMCG market and premium car market?

In premium car market, whether comparative advertising is perceived as more convincing than non-comparative advertising?

In premium car market, whether comparative advertising has greater ability to raise customers’ purchase willingness than non-comparative advertising?

Would comparative advertising damage the brand credibility of premium car manufacturers?

Whether customer’s prior brand experience is an influential factor in their assessment of comparative ads?

Whether comparative advertising is an appropriate strategy for premium car manufacturers to use?

2


Part â… 

Literature Review

3


Chapter 1

Advertising Overview In this chapter, an overview of advertising will be given. Specifically, we will demonstrate how consumers approach the ultimate purchase in a gradual manner, to help us understand the function of advertising. 1.1

The Essence of Advertising

Brand building is a function that rooted in the very nature of advertising. The goal of most advertising is to shape social behaviour, control and form people’s attitudes and choice, and persuade consumers to recognize and prefer a particular product or brand (Fisher, 1993; Sandage, Fryburger & Rotzoll, 1979). A company’s advertising strategy is informed by their belief about the customers’ demand and the advertisers’ understanding about what they are capable of providing (Barabba and Zaltman, 1991). The way in which a company advertised their product usually conveys the brand image they are trying to portray. As a result, the design of much advertising is focused on its “long-term” effectiveness, rather than producing immediate purchases on the audiences. However, before something is going to happen in the future, there must be something happened in the short run, such as an increase in sales. According to Lavidge and Gary (2000), this short-term effect can be used as an “indicator”, to tell us the expected performance of the ads that being used. Based on this position, Lavidge and Gary (2000) further revealed that, for

4


most consumers, they approach the ultimate purchase in a gradual process manner, which can be divided into seven steps: Figure 1.1: Seven-step purchase process

Source: Lavidge and Gary (2000) On one hand, this seven-step purchase process provides us a framework to evaluate the effectiveness of advertising, by means of measuring potential customers’ movement on such a flight of steps. One the other hand, it could help us to get a better understanding about the role of advertising as related to the various positions on the steps. Simply put, the role of advertising is to move potential consumers up the final steps toward purchase. A great deal of advertising is designed to “help pave the way for the salesman by making the prospects aware of his company and

5


products, thus giving them knowledge and favourable attitudes about the ways in which those products or services might be of value”. Even within a specific product, different advertisements or campaigns may be tailored for people at different steps in the purchase process. Therefore, the role of advertising will then be varied along with the progress of a product in its entire lifeline. Additionally, in the real market, it’s not the truth that all potential customers will “start from scratch”. Sometimes their original negative attitudes about a product or brand will “place them even further from purchasing the product than those completely unaware of it”, according to Lavidge and Gary (2000). In this situation, the role of advertising has changed to “geting them off the negative steps, before they can move up the additional steps which lead to purchase”. In regard to this purchase process, the authors remind us that “the various steps are not necessarily equidistant”. In some cases the distance from preference to purchase is larger than that from awareness to preference, and in some other instances this will be another situation. Furthermore, the phenomenon of “impulse purchase” arose authors a great attention to investigate the “psychological/economic commitment” involved in the purchase of a particular product. As Lavidge and Gary (2000) summarized, “the more serious the commitment is, the longer it will take to bring consumers up these steps”. A demonstration of this theory can be shown when we compare customers’ shoes purchase behaviour and vehicle purchase process: one may make a quick decision on buying his or her new shoes because this purchase choice involves a comparatively low psychological and economic commitment. On the contrary, people are less likely to go almost “immediately” to the top of the steps in cases of buying cars because it usually evokes an intensive psychological evaluation, and it does cost a lot compared to a pair of shoes. Under the light of this theory, we developed the first hypothesis of this research. 6


H1: The result of using comparative advertising is different in Fast Moving Consumer Goods industry (FMCG) and automotive industry. 1.2

The Function of Advertising

Literatures about advertising often associated functions of advertisement with psychological theories, because both of advertising and psychology researchers invest heavily on studying human being’s behaviour (Lavidge and Gary, 2000). A classic psychological model divided behaviour into three components: the cognitive component, associated with “rational” states; the affective component, linked to “emotional and feeling” states; and motivational component, related to the tendency to treat objects as positive or negative goals. Under the light of this psychological model, Lavidge and Gary (2000) further summarized three major functions of advertising (figure 1.2), derived from their “seven-step purchase process”. Figure 1.2: Three major functions of advertising

7


Source: Lavidge and Gary (2000) The second and third step in the purchase process have been labelled “awareness” and “knowledge”, altogether constitute the first function of advertising, namely “information” or “ideas”. The following two steps, “liking” and “preference” formed the second function of advertising as favourable attitudes or feelings toward the product. Lastly, the final two steps, “conviction” and “purchase” are to produce “action”, which is its third function. As can be seen in figure 1.2, these three functions are highly aligned with the three components of behaviour as we mentioned above, and they will also form the basis of our understanding about how advertising works in the next chapter. Furthermore, this advertising function taxonomy also informed the design of the questionnaire (see Appendix Ⅱ) in our quantitative research phase. Each question is designed to examine the effectiveness of the given ad sample in terms of its functions. Specifically, by asking people’s attitude toward the shown ad, we get responses regarding the “liking and preference” function of the ad; by asking them whether they are convinced by the given ad, we are 8


able to evaluate this ad in terms of its “conviction� function.

Chapter 2

How Advertising Works In order to exam advertising effectiveness comprehensively, both of advertisers and researchers need to think about with how advertising affects consumers, and eventually, how it works. In this chapter, we recognized the framework for studying how advertising works, and also the taxonomy of models, proposed by Vakratsas and Ambler (1999). Following this framework, we critically evaluated the theoretical principles of several models, and then introduced a new approach for measuring advertising effectiveness. This new

9


approach helps us better understand the rationale of using comparative advertising. 2.1

The Framework for Studying

After reviewing more than 250 journal articles and books, Vakratsas and Ambler (1999) studied a large number of advertising-related models on the basis of a simple framework of how advertising works as shown in Figure 2.1. Figure 2.1: A framework for studying How Advertising Works

Source: Vakratsas and Ambler (1999) As can be seen in this framework, all elements of advertising, including message content, scheduling of advertising, and repetition (Singh and Cole, 1993) are labelled as inputs for the consumer. As Vakratsas and Ambler (1999) explained, “they constitute the advertising strategy that triggers a consumer’s response”. These initial advertising inputs will then go through a “filter”, which is constituted by factors such as consumer’s ability to process information (MacInnis and Jaworski, 1989) and their attitudes toward the ad (MacKenzie, Lutz, and Belch, 1986). One’s response to advertising may determined by these mediating factors extensively.

10


Once the initial inputs are being filtered, our attention will be drawn to the issue of advertising effects. Vakratsas and Ambler (1999) believed that, advertising must yield some mental effect before it can affect consumers’ behaviour. Therefore, they classified advertising effects into intermediate effects and behavioural effects. The concept of intermediate effect implies that, advertising effects should be studied in a space in which affect, cognition, and experience constituted its three dimensions. Specifically, cognition has been viewed as “a system of beliefs structured into some kind of semantic network to form complex belief systems” (Holbrook and Batra, 1987). It reflects the “thinking” dimension of people’s response. Affect, on the other

hand,

is

measured

by

scales

such

as

like/dislike,

favourable/unfavourable, positive/negative, and is linked to the “feeling” dimension of people’s response. We will further discuss the role of affect in advertising in chapter three. When it comes to the behavioural effect of advertising, researchers usually regarded it as synonymous with buying response or usage behaviour, which can be measured by brand choices or purchase decisions (Holbrook and Batra, 1987). As Vakratsas and Ambler (1999) pointed out, “the consumer’s mind is not a blank sheet awaiting advertising”, most of them possess different levels of product purchasing and usage memories. Therefore, behaviour often feed back to experience. 2.2

The taxonomy of models

Vakratsas and Ambler (1999) proposed this taxonomy of models, aimed for describing the various theories of how advertising works. 2.2.1

Market Response Models

This model typically relate advertising, price, and promotional measures directly to behaviour measures such as sales, market share, and brand

11


choice, the investigate intermediate effects is not featured at all. Studies on this model are conducted on both aggregate level, of which behaviour measures are derived from market data such as sales figures and market share, and individual level where individual’s brand choice are used as measurement. The only advantage of this model is, it eliminates the uncertainties of intermediate measurements. 2.2.2

Cognitive Information Models

This class of models assumes that consumer preferences and decisions are not changed by advertising, they are rather rational. Such models of advertising has been regarded purely as information transfer that providing strictly factual information to reduce customers’ search costs (Nevett, 1982). This model partly explained why Reeves (1961) encourage brands to “differentiate themselves through tangible product attributes and then communicate that differentiation positively”. 2.2.3

Pure Affect Models

In contrast with cognitive information models, pure affect models pay little or no attention to cognition but focus on affective responses (Aaker, Stayman, and Hagerty, 1986). Researchers on this ground believed that consumers formulate their preferences and decisions based on their feelings and emotions induced by the advertisement, rather than strictly factual attribute information. According to this approach, Batra and Ray (1986) claimed, “awareness of the advertisement is not necessary, though awareness of the brand is”. However, Franzen (1994) argued that, “models based purely on affective responses are rather improbable”. Instead, what is widely accepted is that cognition and affect altogether constitute the intermediating effects of 12


advertising (Holbrook and O'Shaughnessy, 1984). The pure affect models “essentially introduced affective responses to the study of advertising effects”, according to Vakratsas and Ambler (1999). The role of affect in advertising will be further evaluated in Chapter three. 2.2.4

Persuasive Hierarchy Models

This class of models follows “cognitiveaffectivebehaviour” sequence, indicating this process begins with customers changed their mind about a product, leading to a favourable attitude, which then being reflected on the customer’s behaviour. This “hierarchy of effects” is originated from the first formal advertising model, which is known as the “AIDA” model: AttentionInterest-Desire-Action. This model was emerged at 1898 as a personal selling model, and was then adapted for advertising researches (Strong 1925, p.76). Both of the original AIDA model and this Persuasive hierarchy model begin with cognition and followed by affect in their essentials, indicating these models deemed that advertising is perceived as persuading the consumer to buy. The concept of persuasive hierarchy models has been widely accepted through the development of advertising research. Its underlying pattern has been maintained for decades although the number of stages within the model may be increased or refined under different research context (Aaker and Day, 1974). However, after critically evaluated this long-been-used conceptual model, Hall (2001) claimed that if we accept the concept that the consumer response path is flowed from “cognition” to “affect” to “behaviour”, the purpose of advertising will be defined as “primarily to drive trial by inserting the brand into the consumer’s head, and keep it there”. This is not the case in human experience, and is “certainly not the case in consumers’ responses to advertising”, according to Hall (2001).

13


2.3

Perception/Experience/Memory Model

As Hall (2001) argued that, the weakness of traditional approaches is in the assumption that beings are rational, our belief systems are closely related to objective truths, and therefore “cognition plays a primary role in consumer response”. Conversely, he believed that the cognition is the consumer’s interpretation of reality, and it is in fact “the outcomes of a complex process of perception, experience, and memory, a process that is driven primarily by emotions and feelings”. This reverse-hierarchical model could be described as flowing from “Affect” to “Behaviour” to “Cognition”. Figure 2.2: The Perception/Experience/Memory model

Source: Hall (2001) This model of consumer’s response to advertising maps a process that reflecting three key functions of advertising: framing perception, enhancing experience, and organizing memory (Figure 2.2). The emphasis of this model is placed on advertising’s function of enhancing experience. Accordingly, the author divided the ad exposure into two phases, one is “Pre-experience exposure”, and the other one is “Post-experience exposure”.

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2.3.1

Framing Perception

In this phase, the most important function of advertising is to frame perception. Firstly, framing could let the consumer “creates a perceptual prompt that brings the advertised product into a particular frame of reference” (Hall, 2001), enabling the emergence of any meaningful expectation or perception about this product. Secondly, the pre-experience exposure could help consumers creating a sense of anticipation of a certain experience. 2.3.2

Organizing Memory

This phase has the key function of organizing memory. Post-experience advertising provides every possible sensory cues to prompt the customers to unlock a whole set of recollections and wonderful experience, leading to the recall of the ad, the product, and the brand. More importantly, post-experience exposure not only makes the consumer feeling that the experience was a good one, more importantly, “it also provides reasons to believe that it was” (Hall, 2001). 2.3.3

Enhancing Experience

As can be seen in Figure 1, both pre-experience and post-experience exposures play the function of enhancing experience. This conclusion has benefited from earlier work by Braun (1999), whose groundbreaking experiment empirically showed that exposure to advertising can transform “objective” sensory information in a consumer’s memory before and after the judgement process. This breakthrough expanded our understanding of perception and memory in a psychological approach, because advertising has shown to be able to “enhance sensory experience both when exposed to the consumer before the experience, and in retrospect, when exposed afterward”

15


(Hall, 2001). Before the experience, advertising could be used to establish trust and relationship between customers and the brand, whereas the postexperience advertising could make them believe that “their past product experience had been as suggested by the advertising” (Braun, 1999). In summary, this perception/experience/memory model dictates a complete rethinking of what constitute people’s cognition and perception: 

Emotion, feelings, affect, and experience inform cognition at every stage of the process, the role of cognition has been greatly reduced.

Perception becomes a dependent variable in this model. It is greatly determined by advertising, experience, and the consumer’s priors. As Sheehan et al. (2006) summarized, “Perceptions formed through prior experience can be reaffirmed, changed, or reversed entirely due to the subjective interpretations gleaned from the advertisement”.

Chapter 3

16


Involvement, Emotion, and Affect in Advertising In this chapter, the concept of involvement will be proposed as a mediating factor of individual responses to advertising, models of information processing will also be discussed. Then we will move on to analyze the emotional aspects of consumer behaviour, and finally, the role of affect in improving the advertising effectiveness will be given. 3.1

The Concept of Involvement

Involvement has been identified as a mediating factor of individual responses to advertising. It has been extensively studied within the persuasive hierarchy models as we discussed above (Batra and Ray, 1985). Involvement can be understood as “the number of linkages made between the advertised product and the consumer's life during exposure to an advertisement” (Krugman, 1967). Another definition was proposed by Rothschild (1984, p. 127) as “an unobservable state of motivation, arousal, or interest. It is evoked by a particular stimulus or situation and has drive properties. Its consequence is types of searching, information-seeking and decision making”. With a clear understanding about this concept, Greenwald and Leavitt (1984) proposed a four-level audience involvement model, and related each level in this model to stages of consumer information processing (Gardner, Mitchell, and Russo, 1978) as shown in Figure 3.1. Figure 3.1 Four-level audience involvement model

17


Source: Greenwald and Leavitt (1984) According to this four-level involvement model, Hall (2001) suggested that “complex advertisements requiring inferences of brand quality based on persuasive arguments should mainly require elaboration, which is a high level of involvement. In contrast, advertising that links a brand to attractive objects should only require a lower-level type of involvement: focal attention for instance”. 3.2

The Role of Emotion in Mediating the Effect of Advertising

An increased attention has been drawn on consumption-related emotions (Holbrook and Hischman, 1982). Several global measures such as “attitude toward the ad” (Gardner, 1985), and “subcategories of affective responses evoked by advertisements” (Batra and Ray, 1986) have been recognized by researchers. Holbrook and Batra (1987) proposed a communication model intended to portray the role of emotions as mediators of consumer responses to advertising (Figure 3.2).

18


Figure 3.2: The communication model

Source: Holbrook and Batra (1987) This communication model explicitly recognized the emotional responses of the consumer as an important mediator of advertising effects. Specifically, the role of people’s attitude toward the ad has been documented as “a variable that intervenes between advertising content and attitude toward the brand” (Batra and Ray, 1986). In other word, consumers develop a liking for a brand based at least partly on “how affective that brand’s advertising is” (Vaughn, 1980). 3.3

The Role of Affect in Advertising

Researches on affect have benefited from earlier work in emotion studies. According to Vakratsas and Ambler (1999), affective responses to advertising can be classified into two types: “One leads to the formation of an attitude toward the brand, and one leads to the formation of an expression of the likability of the advertisement itself”. Biel (1990) further proved the ad likability is correlated positively with consumer preference and behaviour through an experimental study. Batra and Ray (1982) made a conclusion about the role affect played in advertising: “the attitude to the advertised brand is formed not only on the basis of the evaluation of the advertised brand’s attributes, but may also be

19


based on the classically conditioned affect for the brand from the attitude to the ad itself”. Based on this ground, they concluded affective advertising could lead the audience to a more favourable evaluation of the advertised brand, because “it is attended to more, processed more, evaluated, more favourably, and remembered more”. 3.3.1

People May Pay Greater Attention to Affective Advertising

As Broadbent (1977) found that, “words that have emotional content are perceived more readily than those which don’t”. Previous literatures also indicated affects play a prominent role in models of attention and perception (Posner and Snyder, 1975). Consequently, “affective advertising should prove to be more effective in getting such attention” (Ray, 1977). 3.3.2

Affect May Enhance the Degree of Processing

This conclusion is derived from Kroeber-Riel’s (1979) argument that “the degree of information processing for a message is a function of the degree to which the message evokes arousal or phasic activation”. 3.3.3

Affective Executives May Lead to More Positive Judgements of the Advertised Message.

Firstly, as psychological researchers suggested, people’s judgments are highly influenced by their feeling at the moment. As a result, “affective ad executions could favor recipients’ evaluations of the assertions in the ad” (Bower and Cohen, 1982). Moreover, in some cases, affective executions may also capable of reducing audiences’ counter-arguing, making it to be

20


uncritically accepted (Festinger and Maccoby, 1964). Secondly, because people in positive affect are willing to avoid cognitive strain, the complexity of the judgement task will be therefore reduced. This results in a higher message acceptance, and promoted people to “engaged in speedy, simplified, non-compensatory processing” (Isen et al., 1982). 3.3.4

Affective Executions May Be Remembered Better

Affective elements in advertising have been proved to be able to arouse “recall”, it makes the ad, the advertised product or brand easier to be remembered (Dutta and Kanungo, 1975).

21


Chapter 4

Discussion of Comparative Advertising Regardless the controversy toward comparative advertising, this kind of advertising technique has been serving in industries for decades. Its benefits have been proven by numerous companies in the history (Golden, 1976). In this chapter, we will study this type of advertising by fitting it into an existing model. By doing so, the nature of comparative advertising, both of its advantages and disadvantages will be presented, leading to the formulation of our second and third hypotheses. 4.1

Definition of Comparative Advertising

To begin with, from a customer’s perspective, comparative advertising is simply a combination of the advertiser’s knowledge and wisdom; its result can be either spectacular or devastating. A vivid explanation of this advertising technique has been found on the web: “In the advertising world, the gentle ribbing of competitors is almost a given. Whether it’s dish soap, paper towels, computer companies or automobiles, poking a little fun at your main rivals is the name of the game” (http://ca.autoblog.com/2011/03/26/report-ford-suesnissan-over-commercial-with-bikini-models-in-brazil/).

Meanwhile,

a

more

concise definition of comparative advertising is also provided by Aluf and Shy (2001, p1) as follow: “Comparative-advertising is defined as one in which the 22


advertised brand and its characteristics are compared with those of the competing

brands.

Comparative-advertising,

whether

persuasive

or

informative, attempts to reduce the value of competing brands relative to the advertised brand�. Comparative advertising has being widely used by global advertisers. According to Muehling et al. (1990), around 40% of all advertising involved in comparative elements. Pechmann and Stewart (1990) also suggested that the majority of all ads (60%) are indirectly comparative while 20% contain direct comparative claims and only the rest 20% ads totally do not get involved in this sea of troubles. Further more, we also noticed that the form and style of comparative advertising is diverse, and they are developing all the time (Muehling et al., 1990). 4.2

How Comparative Advertising Works

After evaluating many comparative-advertising-related journal articles, our researchers deduced a two-way framework of how comparative advertising works (Figure 4.1). Figure 4.1: A framework for studying how comparative advertising works

In this framework, we take the market positions of the advertised brand and its 23


comparative brand into account. The method of using comparative advertising has been divided into two ways: “Top-down” and “Bottom-up”. Researchers on the former ground thought comparative advertising is a strategy that aims at differentiating the sponsor’s brand with others. They believed that “in the absence of comparative advertising, brands are viewed as identical from consumers’ point of view. What comparative advertising does is to ‘convince’ consumers that the brands are differentiated” (Aluf and Shy, 2001). This is the case for those who are in market leading positions. In such a situation, their emphases are usually placed on making the consumers to believe this brand is different from its competitors, so as to establish or maintain its leading position over the followers. On the contrary, in the empirical business reality, comparative advertising strategy is often observed as using by new entrants, market challengers, or disadvantageous brands. Their advertising objectives usually appear to be placing themselves “in the same league as the brand leader in the mind of the consumer”, continued by Gorn and Weinbery (1984), “A favourable result for the challenger's comparative ad could be less psychological distance between the two brands”. This “Bottom-up” comparative advertising approach has been proved to be a useful strategy to narrow down the gap between the challenger and the market leaders in customers’ perception. Recall back to the perception/experience/memory model (P/E/M model) in Chapter two, it emphasized on exposing consumers to the advertising “in a continuous loop between post-experience and pre-experience” (Hall, 2001). However, comparative advertising doesn’t adhere to this principle. The “topdown” approach advertising can be regarded as “post-experience exposure” in the P/E/M model, whereas the “bottom-up” one could be classified as “preexperience exposure” advertising. As Hall (2001) explained, “pure preexperience exposure only occurs in the case of a completely new product

24


prior to launch, or among non-triers of an existing product. Non-triers could be new to the brand or product if distribution has expanded, or they may be simply unfamiliar with it for whatever reason”. From this respect, comparative advertising can be fitted into “Persuasive hierarchy models” very well. This particular kind of advertising operates under the assumption that cognition is the primary driver of purchase behaviour. Once consumers positively changed their minds about a product, an affective executive will be produced, leading to increased purchase willingness. The focus of this process is always placed on “cognition” and “affect”, simply put, comparative advertising is purely perceived as persuading the consumer to buy. “Enhancing experience”, the central function in P/E/M models, doesn’t feature at all. As Hall (2001) indicated, the perception/experience/memory model “explicitly incorporates a role for cognition and perception that is consistent with modern psychology and neuroscience”. It has been widely accepted as an advanced model which is more consistent with empirical business reality compared to any of the alternatives currently in the literature. In Hall’s (2001) model, perception is a dependent variable, influenced by advertising and experience, more specifically, by customers’ priors. However, comparative advertising, as an application of the inferior “persuasive hierarchy models”, has been criticized for its ignorance of enhancing experience in its nature. Our researchers believed that, failure to recognize the significance of customer’s prior experience is an inherent disadvantage of comparative advertising. Advertisers need to know that “the customer’s mind is not a blank sheet awaiting advertising but rather already contains conscious and unconscious memories of product purchasing and usage” (Hall, 2001). Thus, a hypothesis regarding the impact of consumers’ prior experience on comparative advertising evaluations has been formulated.

25


H2: Customers’ prior brand experience is a significant factor in their comparative advertising assessment process. 4.3

Advantages of Using Comparative Advertising

Some literatures suggested that “comparative advertising appeal to a wider audience

and

enhance

sponsor's

brand

identification,

message

persuasiveness and market share” Giges (1980). Firstly, comparative advertising produces greater mental activity (Wilso and Muderrisoglu, 1980). As Muehling et al. (1990) suggested that, “a comparative ad which contains direct references to a well-known brand has an inherent advantage over non-comparative ads because the structure and content of the comparative ads lead consumers to be more ‘involved’ with the advertised message”, this increased involvement will lead to the formation of a more retrievable brand-memory trace. Secondly, Muehling et al. (1990) further concluded that, people usually considered the information in this kind of ad may be more useful and meaningful. Therefore the ad will be perceived to be more relevant (Wilkie and Farris, 1974). As a result, a large percentage of customers deemed that comparative advertising is a useful way to help facilitate decision-makings, and reduce current or later search efforts. Last but not the least, according to Wilkie and Farris (1974), because of its “relative novelty, visual prominence, and its increased relevance for users of the brands employed for comparisons”, comparative advertising could attract more attention than non-comparative ads. As a result, “comparative advertising allows a small unknown firm to successfully compete with much larger firms”, concluded by Muehling et al. (1989).

26


4.4

Brand Building and Comparative Advertising

As Holbrook and Batra (1987) suggested, “for many purposes, it makes sense to regard the ads themselves as having different ‘personalities’ or ‘emotional profiles’ to which members of the target audience react with a fair degree of homogeneity”. This suggestion prompts our researchers to allocate a great attention to associate comparative advertising with the concept of brand personality. Brand personality can be defined as “the set of human characteristics associated with a given brand”. Because consumers tend to prefer brands featuring personalities that are similar to theirs, or to those whom they admire, brand personality is increasingly seen as a valuable factor in increasing brand engagement and brand attachment. Specifically, by creating a personality for brands, companies could accordingly differentiate their brand identity, make an effective communication strategy, and construct superior brand equality. One direct way to form and influence brand personality is user imaginary, this include the company employees, the brand’s product endorsers, and even the characteristics of a brand’s loyal customers. Indirectly, the brand personality is informed by all the elements of the marketing mix: price, retail store locations, all phases of the brand communication, sales promotion, and eventually, the media advertising. Because brands can be personalized in much the same way as humans, sometimes people speak of them as an extension of themselves, brands are being used to express one, and this is especially true for cars. This emotional attachment on cars has been presented by Fraine (2003) as follow, “vehicles are represented less as a product and more as a marker for social status and group membership. The car serves more than its utility as a mode of transport, and invokes emotional and psychological attachments in the 27


owner”. Nowadays, automotive manufacturers have drawn increasing attention to differentiate the emotional pay-off of their products. In entry-level segment, customers usually look for aspects such as reliability and fuel efficiency. Advertising, accordingly, tends to focus more on the rational or functional benefits of a certain model. However, when it comes to the premium car segment, the emotional pay-off of a car is highly sought after by the customer. Therefore, the symbolic attributes of the vehicles are always highlighted in advertising. Because of several disadvantages of comparative advertising, such as “increasing consumer awareness of competitors' brands”, “decreasing claim credibility”, and “producing confusion rather than effective communication” (Levine, 1976; Diamond, 1978), our researchers came out to question the appropriateness of using comparative advertising in premium car segment. Under this consideration, the third hypothesis is emerged. H3: Non-comparative advertising is more appropriate for premium car brands to use.

28


Part â…Ą

Research Methodology

29


Chapter 5

Research Methodology In order to turning our research question into a robust research project, every step in the project needs to be planned thoughtfully and comprehensively (Robson, 2002). This chapter discussed the methodology we adopted in the qualitative and quantitative phases, covering from the philosophical perspective we assumed, to all detailed data collection/analysis techniques and procedures. The data validity and reliability are also under discussion.

5.1 Research Philosophy, Approach, and Strategy As Guba and Lincoln (1994:105) pointed out, questions of any specific research methods are of less important to questions of which paradigm is applicable to the research. In our researcher’s view of the world, we hold the belief that “there is a method for studying the social world that is value-free, and that the explanations of a causal nature can be provided� (Mertens, 2009,

30


p.10). As a consequence, a post-positivism paradigm is applied to guide the development of this research. Post-positivism can be seen as the successor of classic positivism. In contrast with an interpretivist, suggested by Trochim (2006), both positivists and postpositivists thought there is an external reality independent of our thinking about it that science can study, and both of them believed that the universe was operated by laws of cause and effect that we could explore if unique approach of the scientific method is applied. In a positivist view of the world, “scientific knowledge is utterly objective and only scientific knowledge is valid, certain, and accurate” (Crotty, 1998, p.29). However, this highly-objective assumption falls short when applied to investigating human behaviour. According to Trochim (2006), human experience is an important factor in studying our social world, but much of it is not observable, and therefore being classified as illegitimate topics in a positivist study. Post-positivist, on the other hand, rejected the positivists’ narrow view that we could only study what could be directly observed and measured. Instead, they believed “all observation is fallible and has error and that all theory is revisable” (Trochim, 2006). Therefore, researchers do not have the ability to know reality with certainty, but we could modify our claims to understandings of truth based on probability, suggested by Mertens (2009, p.10-11). This leads to the discussion of what is meant by objectivity in a postpositivist world: generally, they still hold beliefs about the importance of objectivity. However, since we are all inherently biased by our cultural experiences and world views, no one can see the world perfectly as it really is (Figure 5.1). Our best way to achieve objectivity is to triangulate across multiple fallible perspectives to try to get a better idea on what’s happening in reality, instead of putting aside our biases and seeing the world as it really is. “We never achieve objectivity perfectly, but we can approach it”, claimed by

31


Trochim (2006). Figure 5.1: Elements of post-positivist paradigm

Source: adapted from Cuba and Lincoln (1994) The association of deductive research approach with the post-positivist paradigm is supported by many researchers (Saunders et al., 2009; Creswell and Clark, 2007; Trochim, 2006). As a consequence of adopting deductive approach, the structure of this research is following the shape of an “hourglass” (Figure 5.2). The research starts with a broad question that the researcher wishes to study. The initial interest of this research is to investigate the

effectiveness

of

using

comparative

adverts

for

premium

car

manufacturers. Since this research question is too broad to study in a single research project, we need to “narrow it down to one that can reasonably be studied in a research project” (Trochim, 2006). As a consequence, several focus questions have been emerged as listed in the introduction. These focus questions guided the development of all the hypotheses, which will be then tested in the quantitative phase of the research. Once initial conclusions have been formulated, the researcher will attempt to “address the original broad 32


question of interest by generalizing from the results of this specific study to other related situations”, as suggested by Trochim (2006). Figure 5.2: The “hourglass” notion of research

Source: adapted from Trochim (2006) From a strategic point of view, survey strategy is a powerful tool to suggest possible reasons for particular relationships between variables and to produce models of these relationships (Saunders et al., 2009). Our researchers considered we have the ability to define a theoretical framework once valuable insights are rolling out from the qualitative phase of the research. Under the light of this framework, each research question will be developed into several context-related hypotheses, which will be then tested in a quantitative manner by the means of collecting and analyzing questionnaire data. Through the application of this survey strategy, we will be able to explain causal relationships between variables of interest in our research area (Robson, 2002).

5.2 Research Design As we believed a mixed method design could supply us more valuable

33


information on the subject of interest, compared with those supplied by a single method (Greene et al., 1989), a sequential mixed method project will be deployed in our research as an answer to Saunders et al.’s (2009) effort to discourage us from thinking of a particular research method as the sole means that we should employ in the study. That means both qualitative and quantitative research techniques and procedures will be used, they will be occurred in chronological order with one strand emerging from the other (Tashakkori and Teddie, 2009). Specifically, participant observation will be added as a complement to the questionnaire, it enable us to discover some valuable insights that quantitative research techniques can not help (Curran and Blackburn, 2001), and also to obtain a more understandable picture about people’s mental activities during their evaluating process, before using questionnaires to predict and explain their thoughts and behaviour in statistics manners. Mixed method research is frequently associated with the post-positivism paradigm (Creswell and Clark, 2007). In post-positivists’ view of the world, all observation and measurement is fallible, therefore the importance of multiple measures and observations is highly awarded in this research paradigm (Trochim, 2006). “The advantage of mixed method design is that it brings together the differing strengths and non-overlapping weaknesses of quantitative methods with those of qualitative methods”, suggested by Creswell and Clark (2007). More importantly, this research design is usually very efficient, because one phase may inform the other during data collection, any surprising results from the former will be better understood by employing the following phase (Niglas, 2004). In this study, the qualitative phase comes the first. By the means of participant observation, the researcher got a clear picture of our research area, including real-life cases, people’s perspectives and viewpoints, and any contextual

34


information on the conjunction of comparative advertising and cars. All findings emerged in this phase will be the foundation for the upcoming quantitative phase. In other word, the scope of the quantitative research will be expanded under the light of the initial understanding gained from the qualitative research. Moving onto the quantitative phase, questionnaires, as the most common and traditional method of survey strategy, will be used to inexpensively generate large numbers of response that produce information across a broad range of survey topics (Tashakkori and Teddie, 2009). These information will be used to determining whether a hypothesis should be accepted or rejected, leading to the answer of our research questions. In terms of time horizons, our research will be a cross-sectional study. As Robson (2002) claimed, cross-sectional studies are particular suitable for survey strategy. In spite of this, we’ve also asked ourselves the question ‘has there been any change over a period of time?’ (Bouma and Atkinson, 1995: 114). The answer is: firstly, this study is not aimed at investigating change and development; secondly, time is a much less significant factor in the topic we chose; lastly, longitudinal studies are usually time-consuming work, which is not allowed in our current situation.

5.3 Data Collection 5.3.1

Participant Observation

The advantages of participant observation have been summarized by Gill and Johnson (2002:144) as follow: “Participant observation enables researchers to share their experiences by not merely observing what is happening but also feeling it”. Furthermore, it could raise the researcher’s awareness of significant social processes (Saunders et al., 2009). As a result, participant observation could imply a much higher level of immersion in the research

35


setting. This characteristic makes it much different from data collection by means of questionnaire, where researchers usually will know little of the context in which the respondents’ comments are set (Delbridge and Kirkpatrick, 1994:37). However, as Saunders et al. (2009: 290) stated, participant observation has not being widespread used in management and business researches. It encourages us to assess the disadvantages of adopting participant observation in our research: most concerns regarding this qualitative data collecting method are focused on the role of observers and the observer bias. The primary work involved in planning participant observation is to determine the researcher roles (Saunders et al., 2009). This is literately a trade-off among four options developed by Gill and Johnson (2002) in their fourfold categorisation (Table 5.1) Table 5.1: Typology of participant observation researcher roles Researcher’s identity is revealed

Researcher takes part in activity Participant as Complete observer participant Observer as participant

Complete observer

Researcher’s identity is concealed

Researcher observes activity

Source: Gill and Johnson (2002) We consider that, the choice of researchers’ position in the observation is a major influential factor to its results. This choice should be guided by the appropriateness of the method for our research questions and objectives. In the present study, we will collect people’s comments, dialogues, and debates regarding comparative ads in automotive industry from a variety of sources. Although revealing the research purpose in a participant observation has tend to be less problematic in terms of ethics (Saunders et al., 2009), we still prefer to conceal our identity to those we are observing. In our opinion, once people are willing to express their personal viewpoints on a forum site, their voice will 36


be a mirror of their personality and experience (Valck et al., 2007). Concealing our true purpose to the group members enable us not to condition the behaviour of the research subjects we are studying, and also avoid observer effects on data collection (Saunders et al., 2009). Another threat to the reliability of our research conclusions produced as a result of a participant observation study is known as ‘observer bias’. As Delbridge and Kirkpatrick (1994: 43) claimed that, “we cannot avoid observer bias, all we can do is to be aware of the threat to reliability it poses and seek to control it”. Our measure is to let the researchers staying away from the activities of participants, and keeping ask themselves “did he or she really mean that?” in the following data interpreting stage. In summary, the researcher’s role we adopted is “Complete observer”. In this observation process, some important contextual factors will be revealed, such as major players in the competition of comparative advertising in premium car segment, and their current branding achievement by using comparative advertising. In order to reach some particularly informative cases during participant observation, purposive sampling method is used in the qualitative phase of this research (Neuman, 2005). This type of non-probability sampling is particularly useful when the researchers know exactly “what they need to find out, what will be useful, what will have credibility and what can be done within the available resources” (Patton, 2002). Based on the researcher’s own judgement, the Virtual Communities of Interest (VCI) media platform has been identified as our main sample source. This choice is informed by the fact that people’s interactions on VCI platforms are based on shared enthusiasm and knowledge for a specific activity. Their particular focus upon information exchange and social interaction make them become a sub-group of virtual communities (Valck et al., 2007).

37


Our purposive sampling strategies consist of both “maximum variation sampling” and “deviant sampling”, purposed by Patton (2002). Under the light of the first strategy, we thought social media sites such as some auto maker’s YouTube channel could provide us plenty of samples to analyze. People’s comments, debates toward a particular subject (e.g. an ad) showing on a site will be evaluated, compared and contrasted by the researcher, enabling us to describe and explain the key themes in the research area. Meanwhile, we also agree on Patton (2002)’s statement that “findings from extreme cases will be relevant in understanding or explaining more typical cases”. Therefore, several car enthusiasts’ forums and discussion groups are identified to supplying more controversial samples for us to analyze. People on these online communities are usually more knowledgeable, they are also considered to be possessing greater critical thinking ability on areas of our interest, their feelings and opinions will provide us plenty of information to help us discover valuable insights during the participant observation stage. A full list of sample sources can be found in Appendix Ⅲ.

5.3.2 Questionnaire Questionnaire will be used to collect precise data that allowed us to explore our research questions and gain theoretical insights. Considering no sampling frame was available in this quantitative phase, all samples were selected through a self-selection sampling system, where each individual is able to identify their desire to take part in the research (Saunders et al., 2009). The questionnaire was stored and administered online, and is accessible by simply clicking on a hyperlink offered by the online survey platform. The researcher combined this hyperlink with a brief of our study, we publicised them altogether on a range of social media sites, enthusiast forums, bulletin boards, and online discussion groups, to attract people who are interested in

38


the research topic, or considered it important, devote their time to answer the questionnaire. Internet-mediated questionnaires are open to everyone, it enables us to contact a wide range of people, including difficult-to-access groups, while at the same time, remain them anonymous accessing the questionnaire (Saunders et al., 2009). However, the cost is, it is very difficult for us to obtain a representative sample from which we might generalize as we have little control over the sample cases (Coomber, 1997). The procedure of administering the online questionnaire is guided by Saunders et al. (2009), and is outlined as follow: 

Set up the questionnaire on the online survey platform; make sure the hyperlink offered by it is fully worked

Pre-running pilot test, revise the questionnaire when necessary

Identify a dozen of websites that could be used to advertise the questionnaire

Publicise the objective and rationale of our research, along with the questionnaire access hyperlink on the identified websites

Ensure that the online survey platform is capable of saving the responding data automatically and safely, and is also able to prevent multiple questionnaire replies from one IP address

Three types of data will be collected through questionnaires (Dillman, 2007): Firstly, opinion variables, containing how respondents feel about something or what they believe is true or false, will be collected through a series of likertstyle rating questions. Four options are provided for choosing: “Totally agree”, “Agree”, “Disagree”, and “Totally disagree”, the absence of “Neutral” option is due to the concern of avoiding “uninformed response” (Saunders et al., 2009). Secondly, behavioural variables, recording data on what people did in the past, or will do in the future. This type of variable will be presented through category questions, where each respondent’s answer can fit only one category. The last one is attribute variables, which is collected through list 39


questions regarding respondents’ profile such as gender and age. As a response to Robson (2002)’s suggestion that “questionnaires work best with standardised questions that you will be interpreted the same way by all respondents”, only closed questions are included in the questionnaire. This makes the questionnaire easier and quicker to answer; meanwhile a reduced tendency of “uninformed response” is achieved, because minimal writing is required for the respondent (Dillman, 2007). In order to facilitate the questionnaire answering process, filter questions are added to make the questionnaire more logical. All these measures are aimed at making the questionnaire more attractive, so as to encourage people to complete it. Furthermore, considering the most critical point arose from the pilot test is the excessive number of questions; we confine the length of the questionnaire in four A4 pages in an effort to getting a satisfied response rate (Edwards et al., 2002; Saunders et al., 2009). 5.4

Validity and Reliability

Throughout the entire project, the researcher has drawn a lot of attention to improve the validity of this research. In terms of internal validity, “the ability of your questionnaire to measure what you intend it to measure” (Saunders et al., 2009), two measures have been adopted to secure “the questions in our questionnaire provide adequate coverage of the investigative questions” (Cooper and Schindler, 2008). The first one is to combine the knowledge we learned from previous literatures and the theoretical insights we got in the qualitative phase to inform the design of the questionnaire. The second one is by conducting pilot test to detect any problems in relation to the clearness and effectiveness of each question. When it comes to external validity, the researcher has made an effort to enable our research conclusions to be generalized to a wider context by enlarging the diversity of the quantitative

40


research samples. In order to obtain a robust questionnaire, two approaches have been used to assessing its reliability. Firstly, the researcher measured the consistency of responses across a sub-group of the questions from the questionnaire. These questions are designed bearing similar intentions, and are presented at least two times across the first two sections of the questionnaire. Therefore the consistency of responses from these questions would be a good indicator of the reliability of the questionnaire. Secondly, as a mixed method research, both of the qualitative and qualitative research stands are set up under the same objective. Responses from one stand of the research could be compared and contrasted with the findings flowing out from the other. A robust questionnaire design in our research should be able to reveal consistent findings in line with those found in the participant observation.

41


Chapter 6

Data Interpretation 6.1

Respondent’s Profile

The questionnaire was designed using iSurvey platform, and is administered since 1st August until 31st August in 2011. 224 people have been surveyed, achieving a completion rate of 24.8%. The profile of survey respondents in terms of age, gender, education level, employment status, household yearly income, ethnicity, and their drive ability in illustrated below. Figure 6.1: Age composition

42


Figure 6.2: Gender composition

Figure 6.3: Education level

Figure 6.4: Employment status

43


Figure 6.5: Household yearly income

The age composition (figure 6.1) of the sample is normally distributed, 73.2% (n=164) of respondents are aged 20-29, 17.9% (n=40) between 30 and 44; people aged below 20 or between 45 and 59 are rarely involved in this study. Among the 224 respondents, 71.9% (n=161) of them are male and 28.1% (n=63) are female, showing a significant bias toward male (figure 6.2). Surprisingly, our questionnaire reached a sample of highly educated people (figure 6.3), where 51.3% (n=115) of them are carrying out or have completed their master’s degree, 27.2% (n=61) having bachelor degree, only 8 people reported their education level as “high school�. When it comes to the employment status of our sample (figure 6.4), students (55.8%, n=125) and full-time workers (33.0%, n=74) constitute the majority of the respondents,

44


only 10 and 11 people are being recorded under “part-time workers” and “selfemployed”, respectively. Moving on to their household yearly income (figure 6.5), people earned less than

£ 10,000 represented 20.1% (n=45) of

respondents, 34 and 32 people received £10,001- £20,000 and £ 20,001£40,000 household income annually in our sample, just few people are being recorded in higher income levels. Figure 6.6: Nationality composition

Looking at the nationality composition (Figure 6.6), non-British white people is the largest ethnicity group in our respondents, representing 37.5% (n=84) of the sample. They are followed by Chinese and British people, who constitute 18.8% (n=42) and 10.7% (n=24) of our 224-respondents sample. Figure 6.7: Driving ability

45


Our questionnaire also attracted people with differed level of driving ability (Figure 6.7), where 61.2% (n=137) of respondents claimed that they have at least one car to drive; 27.2% (n=61) have driving licenses but do not own a car; only 11.6% (n=26) can’t drive. 6.2

Data Transformation

All questionnaire responses are initially stored in University of Southampton iSurvey platform. Although this platform is capable of presenting the gathered data in either chart or tabular view, the researcher sticks to using SPSS statistics software to get more in-depth insights from the data. Before performing any statistical tricks, the first thing we need to do is to organize and transform the raw dataset, so as to facilitate the analysis procedure and make the results easy to be understood. Data is recorded in a format of numeric values rather than text responses. This is due to the consideration that, by performing parametric analysis, we could be able to detect more hidden patterns in the data than a nonparametric one (Pallant, 2010). After all relevant download options getting properly checked, the dataset file is available for downloading and importing into SPSS software. While each variable is setting up automatically by SPSS in accordance to the data it received (any missing data has been coded as “.�), several columns in the variable view still arouse our attention. Firstly, the 46


name of each variable is specified by its corresponding question statement on the questionnaire, the researcher replaced them with easy-to-recognized code “q1”, “q2”, go up through to “q21”. Secondly, both label and values columns are leaving blank by default. The researcher labelled each variable with question number and description; we also assigned each response value with its actual meaning in the values column. These actions enabled every variable easy to be recognized in the output window, and it is also beneficial for the following statistics activities. Last but not the least, since the questionnaire is made up of two types of questions: single choice and likert scale questions, the type of each variable is initially set as Nominal data. In the data analysis stage, the researcher will accordingly switch the measure of some particular variables for various statistics analysis and tests. After all these changes have done, the dataset is ready for analysis. The modified variable setting of the dataset is listed on Appendix Ⅰ.

47


Part â…˘

Data Analysis and Discussion

48


Chapter 7

Qualitative Research Stand Due to the global economic recovery, all of the top three German premium car manufacturers, Audi, BMW, and Mercedes-Benz saw bountiful sales increases in recent two years. Although Audi surpassed Mercedes in sales for the first time in the first quarter of 2011, BMW is still the world's best selling premium car brand. In particular, both BMW and Mercedes-Benz have heavily investment in marketing and manufacturing in North America, they are on track to beat Lexus, the Toyota Motor Corp. luxury marque that has dominate U.S. premium car sales over most of the last decade. When it comes to Audi, although this VW Group’s premium brand have managed to sell more than 100,000 units in the U.S. for the first time, which is a large increase of 23% for 2010, these numbers still leave it way behind its arch-rivals BMW and Mercedes-Benz. According to our observation result, most people attribute BMW’s success in America to the difference between the brand image of BMW and Audi. For many entry-level luxury-sedan buyers, BMW cars are considered as the “gold standard” in many categories. This brand, in itself, is glamorous and established in customers’ mind. However, Audi seems more like “an arriviste trying to overcome a reputation for poor quality that lasted until the mid1990s” (Lienert, 2005). Given that Audi plans to become the world’s top-

49


selling premium brand by 2015 with 1.5 million unit annual sales, its primary challenge is to raise the brand’s name recognition in the U.S., making it as well known there as they are in other markets such as Europe. Consequently, Venables had been chosen as Audi’s North America advertising agency three years ago to help this German brand to initiate a series of comparative advertising campaigns. This type of advertising, has been considered to be “an effective way for Audi to go to the market in a way that is engaging, and that will get Audi popularized“, according to Venables. The traffic statistics indeed has proven its ability of boosting audience attention for Audi. Specifically,

the

“Godfather”

spot

(http://www.youtube.com/watch?

v=6N6_0y1YJA0) made “R8” become a popular term in Google’s key word ranking, and generated a 365% increase in traffic to Audi’s dedicated website. But whether these comparative ads can get better reviews from the consumer is still in question. In order to estimate the long-term effect of these ads, our researchers viewed a large amount of comments people posted on various website, and summarized findings as follow: Regarding to a certain Audi comparative ad, some people admitted it is interesting, creative, and entertaining, whereas most people deemed it is somewhat childish, meaningless, and confusing the audience. Interestingly, for those who posted positive arguments toward a certain Audi comparative ad, they usually possessed favourite attitude toward the Audi brand. On the contrary, those who thought the shown Audi comparative ad is annoying are usually BMW enthusiasts. When it comes to the debate of comparative advertising campaigns initiated by BMW, a similar pattern is also appeared. The general opinion about this kind of advertising is negative. In most cases, the most negative comments are come from Audi enthusiasts. BMW supporters, on the other hand, are more likely to be convinced by BMW comparative advertising.

50


The primary finding we got in the participant observation is, for most consumers, the process of evaluating comparative advertising is always intervened by their existing brand experience or preference. This finding will be further analyzed in-depth in the following quantitative research phase.

Chapter 8

Quantitative Research Stand 8.1 H1-related Findings The first section of the questionnaire is designed to receiving respondents’ opinions towards a pair of Pepsi’s comparative print ads (see Appendix Ⅱ). While the third section shifts its object from FMCG market onto automotive industry. Specifically, an Audi comparative TV commercial is selected for discussion in section three (see Appendix Ⅱ). People’s responses in these two sections are ideal resources for doing comparison. The result will tell us whether our first hypothesis “the result of using comparative advertising is different in FMCG and premium car market” is valid. Firstly we will evaluate the distribution of people’s responses of q3 and q6 to get a general idea about their attitudes toward the given Pepsi comparative ads. Then, paired sample T-test will be performed on q4 and q18, q5 and q20 respectively to find out the differences of consumer’s attitude toward comparative ads for Fast Moving Consumer Goods and premium cars. For doing this, variable q4, q5, q18, and q20 need to be measured as “scale” data for performing parametric analysis. 8.1.1

Descriptive Analysis of q3 and q6

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Table 8.1.a: Frequency distribution of people’s responses regarding q3 “The two Pepsi comparative ads are well-designed, and their ideas are very creative”

Table 8.1.b: Frequency distribution of people’s general comments regarding the two given Pepsi comparative ads

As seen from Table 8.1.a; 41.0% (n=91) of respondents generally deem that the given comparative ads are creative and well-designed. Combined with 87 respondents who have ticked on “agree” option, the majority of people (80.2%, n=178) hold positive attitude toward the design of the two Pepsi comparative ads. Moving on to Table 8.1.b; There are 54.9% (n=123) of respondents agree on the statement that the given cases are interesting and funny. 27 out of 224 respondents comment on them as “annoying and pointless”. Rather than like or dislike, 33.0% (n=74) of people choose to being neutral, showing a relative high percentage of people are insensitive to comparative ads used in FMCG industry.

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8.1.2

Paired sample T-test for q4 and q18 Table 8.2.a: Descriptive analysis of q4 and q18

Table 8.2.b: Paired samples T-test for q4 and q18

Both q4 and q18 are designed for investigating the persuasive power of comparative ads. Specifically, q4 collected responses toward the Pepsi ads, and q18 played the same role regarding the Audi comparative ad in section three. A lower average score means a higher persuasive power of its corresponding comparative ad. As seen in the paired samples T-test for those two variables (Table 8.2.b), we can conclude that there is a significant difference in the score of the Pepsi adâ&#x20AC;&#x2122;s and the Audi adâ&#x20AC;&#x2122;s persuasive power, t (219) =-2.840, p=0.005<0.05. The Pepsi comparative ads (M=2.52, SD=1.079) are rated as possessing greater persuasive power on the exposed respondents than the Audi comparative ad (M=2.76, SD=0.882). In other word, although the overall responses for both questions are slightly negative (both average scores are above 2.50), the Pepsi comparative ads are more likely to convince the audiences than the one presented by Audi.

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8.1.3

Paired sample T-test for q5 and q20 Table 8.3.a: Descriptive analysis of q5 and q20

Table 8.3.b: Paired samples T-test for q5 and q20

As Fisher (1993) claimed, advertising is designed to forester a higher willingness of potential customers to buy for the products or service of the advertised brand. In our research, both q5 and q20 can be used to measure whether a comparative ad finally evoke customers’ purchase willingness. Q5 receives responses regarding the statement “After watching the Pepsi comparative ads, I would like to choose Pepsi in the future”. A similar question is also asked for the Audi comparative ad in q20. A lower average score indicates a higher effectiveness of its corresponding comparative ad. As shown in table 8.3.a and 8.3.b, we can conclude that there is a significant difference in the result of comparative ads being used in these two different context, t (219) =-2.668, p=0.008<0.05. Although the willingness of buying for both Pepsi and Audi are generally below anticipation after the respondents being exposed under comparative ads (both average scores are above 2.50), the Audi ad (M=2.98, SD=0.896) received a more negative result in customer’s willingness to buy compared to the Pepsi ad (M=2.77, SD=1.027),

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because of the use of comparative ads. 8.2

H2-related Findings

Our second hypothesis “Customers’ prior brand experience is a significant factor in their comparative advertising assessment process” will be tested in both contexts of FMCG and premium car market. The customer’s existing brand preference data has been collected through q2 and q7. Our first mission (test of H2-1) is to putting q2 against q3, q4, and q5 in a one-way ANOVA, and using cross-tabulation and Chi-square analysis method for q2 and q6. Both of these two analyses will help us find out whether there is a link between customers’ brand preference and their attitudes toward a FMCG brand’s comparative advertising. Our second mission (test of H2-2) is to explore this link in automotive industry, the premium car segment to be exact. All questions designed for collecting people’s opinion towards the given BMW and Audi comparative ads (see Appendix Ⅱ) in section two and three (q8 to q21) will be involved in a series of cross-tabulation and Chi-square analysis against q7, where respondents’ brand preference between BMW and Audi is recorded. This will be followed by one-way ANOVA analysis between q7 and the same block of questions (q8 to q21) to getting more insights from the relationship between people’s brand preference and their attitudes toward premium car comparative ads. 8.2.1

Test of H2-1: In a FMCG Industry Context, Customers’ prior brand preference is a significant factor in their comparative advertising assessment process.

8.2.1.1 One-way ANOVA for q2 against q3, q4, q5

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Table 8.4.a: Frequency distribution of responses in q3, q4, and q5, break down by q2

Table 8.4.b: One-way ANOVA for q3, q4, and q5, break down by q2

Table 8.4.c: Post Hoc Tests for q3, q4, and q5, break down by q2

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In doing this one-way ANOVA analysis, the measure of variable q3, q4 and q5 has been specified as “scale”. As seen in table 8.4.a, people who choose Pepsi as their favourite brand reported the lowest average score in all of these tested variables: 1.56 in q3, 1.97 in q4, and 1.94 in q5. This suggested that the given Pepsi comparative ads are more recognized in Pepsi communities than anywhere else (q3); people who love Pepsi are more likely to be convinced by the given ads (q4), and they are also more willing to choose Pepsi in the future after watching these ads than Coca-cola supporters and the neutrals (q5). Back to the “Mean” figures again, although average scores of q3 in groups “Pepsi”, “Coca-Cola” and the neutrals are varied, the overall opinion towards the design and idea of the given ads are generally positive in all three groups of people (all below 2.50 in q3). However, regarding the statements in q4 and

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q5, responses from groups “Coca-Cola” and the neutrals tends to be much more negative. In particular, both highest value means in q4 and q5 are coming from Coca-Cola supporters: 2.82 and 3.20 respectively, suggesting the most negative reviews of the given Pepsi comparative ads are reported from people who love Coca-Cola. According to the one-way ANOVA test (table 8.4.c), we can confidently conclude that, in this Pepsi case, there is a significant effect of people’s brand preference on their attitudes toward the design of this comparative ad, F (2, 219) =10.373, p=0.000<0.05; and on their perceived persuasive power of this comparative ad, F (2, 221) =14.046, p=0.000<0.05; as well as on their willingness to purchase for the brand after watching its comparative ads, F (2, 219) =41.862, p=0.000<0.05. To further examine the effect of people’s brand preference, a LSD post hoc test was employed. As can be seen in table 8.4.c, Pepsi supporter’s (M=1.56) average opinion toward the design of the given comparative ads is significant different from those in group Coca-cola (M=1.85, p=0.035<0.05) and neutrals (M=2.29, p=0.000). The difference between Pepsi supporter’s (M=1.97) and Coca-Cola supporter’s (M=2.82) perceived persuasive power of these ads is significant (p=0.000). In terms of the willingness to buy for the advertised brand, the difference between Pepsi supporters (M=1.94) and Coca-Cola supporters (M=3.20) is also significant (p=0.000). All of the above analysis are based upon the Pepsi comparative ads shown in section one of the questionnaire, therefore all above mentioned findings can only be valid in a FMCG industry context. 8.2.1.2 Cross-tab analysis with Chi-square test for q2 and q6 Table 8.5.a: Cross-tab analysis for q2 and q6

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Table 8.5.b: Chi-square tests for q2 and q6

Figure 8.1: Distribution of responses for q6 crossing q2

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Most Pepsi supporters (77.4%) considered the given Pepsi comparative ad samples as “interesting and funny”. More than half of Coca-Cola supporters (53.6%) also tick on this option, and the percentage of response to “pointless and annoying” category among Coca-Cola groups is smaller than 12%. It is noteworthy that, among the neutral people, half of them give neither positive nor negative comments for the given ads. In table 8.5.b, the p-value for each reported test version is very small (p<0.05), suggesting that the differences between each pair of expected and actual numbers in the Cross-tab analysis are not due to random chance. In other word, people’s attitudes toward a brand’s comparative ads are highly related to their existing brand preference in this Pepsi case. 8.2.2

Test of H2-2: In The Premium Car market, Customers’ prior

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brand preference is a significant factor in their comparative advertising assessment process. 8.2.2.1 Cross-tab analysis with Chi-square test for q7 and q8 Table 8.6.a: Cross-tab analysis for q7 and q8

Table 8.6.b: Chi-square test for q7 and q8

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Figure 8.2: Distribution of responses for q8 crossing q7

As seen from the cross-tab analysis (Table 8.6.a), the differences between each pair of expected and actual numbers are very small. This finding is confirmed by the following Chi-square test (Table 8.6.b), where an above-0.05 p-value is reported (p-value=0.432), suggesting q7 and q8 are mutual independent. Looking down to the detail of the responses, we can find more than 75% people in each brand preference group choose â&#x20AC;&#x153;non-comparative adâ&#x20AC;? as their answer to q8. Combined all these findings, we can summarize that most people believed the non-comparative BMW ad sample (Ad-1) communicate a clearer advertising message than the comparative one, regardless of their brand preference between Audi and BMW. 8.2.2.2 Cross-tab analysis with Chi-square test for q7 and q9 Table 8.7.a: Cross-tab analysis for q7 and q9

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Table 8.7.b: Chi-square test for q7 and q9

Figure 8.3: Distribution of responses for q9 crossing q7

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87.5% Audi supporters chose the non-comparative ad (Ad-1) as their answer to q9, this percentage in BMW group is 85.5%. Surprisingly, more than 90% people in group â&#x20AC;&#x153;Neutralâ&#x20AC;? did the same choice in q9. However, the Chi-square test (Table 8.7.b) suggests that the above mentioned differences in responses between these three groups of people are due to random chance (P=0.618>0.05). That means q7 and q9 are mutual independent; most people would like to choose the non-comparative BMW ad (Ad-1) for BMW marketing department, regardless of their brand preference between Audi and BMW. 8.2.2.3 Cross-tab analysis with Chi-square test for q7 and q10 Table 8.8.a: Cross-tab analysis for q7 and q10

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Table 8.8.b: Chi-square test for q7 and q10

Figure 8.4: Distribution of responses for q10 crossing q7

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14.1% Audi supporters totally agree that the non-comparative BMW ad (Ad-1) is too simple, this figure is almost twice as much as the proportion of BMW supporters (8.9%) who have the same viewpoint. Conversely, there is a bigger percentage of BMW people (52.4%) who totally donâ&#x20AC;&#x2122;t agree on this point of view than those in Audi communities (29.7%). However, none of significant values in the Chi-square test reported any below-0.05 number, suggesting the relationship between q7 and q10 is weak. 8.2.2.4 Cross-tab analysis with Chi-square test for q7 and q11 Table 8.9.a: Cross-tab analysis for q7 and q11

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Table 8.9.b: Chi-square test for q7 and q11

Figure 8.5: Distribution of responses for q11 crossing q7

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A larger percentage of people in group “Audi” (15.6%) totally agree that the comparative BMW ad (Ad-2) is more likely to be remembered by the audiences, compared to group “BMW” (7.3%) and “neutral” (11.1%). On the contrary, 72.6% BMW supporters and 72.2% “neutral” generally disagree on that statement. However, according to the Chi-square test, all significant values are above 0.05, suggesting that q7 and q11 are mutual independent. 8.2.2.5 Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q12 Table 8.10.a: Cross-tab analysis for q7 and q12

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Table 8.10.b: Chi-square test for q7 and q12

Table 8.10.c: Frequency distribution of responses for q12, break down by q7

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Table 8.10.d: One-way ANOVA for q12, break down by q7

Table 8.10.e: Post Hoc Test for q12, break down by q7

Figure 8.6: Distribution of responses for q12 crossing q7

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After performing cross-tab analysis with Chi-square test for q7 and q12, the measure of variable q12 will be specified as “scale” to conduct the one-way ANOVA analysis. As seen in table 8.10.a, combining “tend to disagree” and “disagree” together, 82.8% Audi supporters do not think they’ve been convinced by the comparative BMW ad (Ad-2). A similar proportion is also reported from “neutral” group, where 80.6% of them express the same opinion toward Ad-2. However, among BMW supporters, 18.5% of them ticked “agree”, and 46.8% chose “tend to agree”, both are the highest figures in its category. The following Chi-square test (table 8.10.b) suggests that the differences between each pair of expected and actual numbers in this cross-tab are not due to random chance (p=0.000). The one-way ANOVA analysis (table 8.10.d) also confirms that people’s existing brand preference highly influence their

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perceived persuasive power of the given comparative BMW ad, F (2, 221) = 31.764, p=0.000. In order to further examine the effect of people’s brand preference on q12, a LSD post hoc test was employed. As seen in table 8.10.e, responses between BMW supporters (M=2.27) and Audi supporters (M=3.27) are significant different (p=0.000). In addition, the differences between BMW supporters’ responses and the neutral’s responses (M=3.06) are also significant (p=0.000). That means the given BMW comparative ad is more convincing for BMW supporters, whereas it failed to convince people who do not treat BMW as their favorite brand. 8.2.2.6 Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q13 Table 8.11.a: Cross-tab analysis for q7 and q13

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Table 8.11.b: Chi-square test for q7 and q13

Table 8.11.c: Frequency distribution of responses for q13, break down by q7

Table 8.11.d: One-way ANOVA for q13, break down by q7

Table 8.11.e: Post Hoc test for q13, break down by q7

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Figure 8.7: Distribution of responses for q13 crossing q7

After performing cross-tab analysis with Chi-square test for q7 and q13, the measure of variable q13 will be specified as â&#x20AC;&#x153;scaleâ&#x20AC;? to conduct the one-way ANOVA analysis.

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As seen in table 8.11.a, combining “tend to disagree” and “disagree” together, 97.2% neutrals and 89.1% Audi supporters are not willing to purchase BMW cars in the future after seeing the given BMW comparative ad (Ad-2). However, there are 52.4% of BMW supporters still consider BMW as their preferred brand in the next purchase, Both Chi-square test (table 8.11.b), p=0.000, and the following one-way ANOVA analysis (table 8.11.d) tell us that personal brand preference is a significant factor to determine people’s willingness to purchase for the brand initiating the comparative ad campaign in this BMW case, F (2, 221) = 33.361, p=0.000. A LSD post hoc test has been employed to further investigating the effect of people’s brand preference on q13. As seen in table 8.11.e, BMW supporters’ average opinion (M=2.39) regarding q13 are significant different from those in group “Audi” (M=3.41) and the “neutral” (M=3.22), p(BMW vs. Audi)= 0.000, p(BMW vs. neutral)=0.000. That means the BMW comparative ad (Ad-2) is generally harmful for raising customer’s desire to buy for BMW brand, and this is especially true for people who originally don’t treat BMW as their preferred brand. But for BMW supporters, this negative effect has been minimized compared to others, there are still a comparative large proportion of people in this group insist on their favorite brand after the release of the BMW comparative ad (Ad-2). 8.2.2.7 Cross-tab with Chi-square test and one-way ANOVA analysis for q7 and q14 Table 8.12.a: Cross-tab analysis for q7 and q14

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Table 8.12.b: Chi-square test for q7 and q14

Table 8.12.c: Frequency distribution of responses for q14, break down by q7

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Table 8.12.d: One-way ANOVA for q14, break down by q7

Table 8.12.e: Post Hoc test for q14, break down by q7

Figure 8.8: Distribution of responses for q14 crossing q7

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After performing cross-tab analysis with Chi-square test for q7 and q14, the measure of variable q14 will be specified as “scale” to conduct the one-way ANOVA analysis. As seen in table 8.12.a, combining “tend to disagree” and “disagree” together, 21.9% Audi supporters, in general, do not agree on the statement “it’s stupid to mention competitors in ads for a premium brand like BMW”. This proportion is a little bit higher in group “neutral”, where 33.3% of them hold the same viewpoint. However, among BMW supporters, 53.2% of them ticked “agree”, and 34.7% chose “tend to agree”, both are the highest figures in its category. The following Chi-square test (table 8.12.b) suggests that the differences between each pair of expected and actual numbers in this cross-tab are not due to random chance (p=0.005). The one-way ANOVA analysis (table 8.12.d) also confirmed that people’s attitude toward comparative ads being used by

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premium car brands are varied according to their existing brand preference, F (2, 221) = 3.495, p=0.032. In order to further examine the effect of peopleâ&#x20AC;&#x2122;s brand preference on q14, a LSD post hoc test was employed. As seen in table 8.12.e, responses between BMW supporters (M=1.59) and neutrals (M=2.00) are significant different (p=0.011<0.05). 8.2.2.8 Cross-tab analysis with Chi-square test for q7 and q15 Table 8.13.a: Cross-tab analysis for q7 and q15

Table 8.13.b: Chi-square test for q7 and q15

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Figure 8.9: Distribution of responses for q15 crossing q7

Combining “agree” and “tend to agree” together, the vast majority of people in group “Audi” (87.5%) believe that BMW will receive decreased brand credibility after showing their comparative ad (Ad-2). A similar situation is also appeared in the neutral group, where most people in that group (72.2%) have the same concern. BMW supporters, however, are tend to be slightly more optimistic regarding the brand image decreasing issue. 21.8% of them do not

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totally agree on that viewpoint, and 9.7% of them even consider that the BMW comparative ad (Ad-2) have no negative impact on its brand value at all. 8.2.2.9 Cross-tab analysis with Chi-square test for q7 and q16 Table 8.14.a: Cross-tab analysis for q7 and q16

Table 8.14.b: Chi-square test for q7 and q16

Figure 8.10: Distribution of responses for q16 crossing q7 81


Combining “agree” and “tend to agree” together, the vast majority of people in group “Audi” (96.9%) deemed the message embedded in this given Audi comparative commercial are very clear, whereas the percentage of people holding this viewpoint in group “BMW” decreased to 78.7%. The following Chisquare test (table 8.14.b) suggests that the differences between each pair of expected and actual numbers in this cross-tab are not due to random chance (p=0.026). People favoring Audi are more likely to think that the given Audi ad communicated a very clear message, in comparison with BMW supporters and the neutral. 8.2.2.10

Cross-tab with Chi-square test and one-way ANOVA analysis for

q7 and q17 Table 8.15.a: Cross-tab analysis for q7 and q17

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Table 8.15.b: Chi-square test for q7 and q17

Table 8.15.c: Frequency distribution of responses for q17, break down by q7

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Table 8.15.d: One-way ANOVA for q17, break down by q7

Table 8.15.e: Post Hoc test for q17, break down by q7

Figure 8.11: Distribution of responses for q17 crossing q7

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After performing cross-tab analysis with Chi-square test for q7 and q17, the measure of variable q17 will be specified as “scale” to conduct the one-way ANOVA analysis. As can be seen in table 8.15.a, Combining “agree” and “tend to agree” together, 92.2% Audi supporters generally think that the given Audi comparative ad let them know the product featured in this ad in a quite straightforward way. 68.1% BMW supporters also hold this viewpoint. Both of the following chi-square test (table 8.15.b), p=0.003<0.05, and the one-way ANOVA analysis (table 8.15.d) suggest that this difference is not due to random chance, and people’s existing brand preference is a significant factor to influence their response to q17, F(2, 219)=7.278, p=0.001<0.05. According to the LSD post hoc test (table 8.15.e), responses between Audi (M=1.70) supporters and BMW (M=2.20) supporters are significant different

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(p=0.000). That means Audi supporters are more likely to admit that the given Audi comparative ad is designed in a straightforward way, compared to BMW fans. 8.2.2.11 Cross-tab with Chi-square test and one-way ANOVA analysis for q7

and q18 Table 8.16.a: Cross-tab analysis for q7 and q18

Table 8.16.b: Chi-square test for q7 and q18

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Table 8.16.c: Frequency distribution of responses for q18, break down by q7

Table 8.16.d: One-way ANOVA for q18, break down by q7

Table 8.16.e: Post Hoc test for q18, break down by q7

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Figure 8.12: Distribution of responses for q18 crossing q7

After performing cross-tab analysis with Chi-square test for q7 and q18, the measure of variable q18 will be specified as â&#x20AC;&#x153;scaleâ&#x20AC;? to conduct the one-way ANOVA analysis.

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As seen in table 8.16.a, combining “agree” and “tend to agree” together, 71.0% Audi supporters claimed that they’ve been convinced by the given Audi comparative ad. This proportion is much smaller among BMW supporters, where 32.7% of them have the same experience. The following Chi-square test (table 8.16.b) suggests that the differences between each pair of expected and actual numbers in this cross-tab are not due to random chance (p=0.000). The one-way ANOVA analysis (table 8.16.d) also confirms this by showing a below-0.05 significant value, F (2, 217) = 19.917, p=0.000. That means the perceived persuasive power of the given Audi comparative ad is varied, depending on individual customer’s existing brand preference. In order to further examine the effect of people’s brand preference on q18, a LSD post hoc test was employed. As seen in table 8.16.e, Audi support’s average opinion (M=2.21) regarding q18 are significant different from those in group “BMW” (M=3.00) and “neutral” (M=2.89), p(Audi vs. BMW)= 0.000, p(Audi vs. Neutrals)= 0.000. That means people who favoring Audi are more likely to be convinced by the given Audi comparative ad, compared to BMW supporters or neutrals. 8.2.2.12

Cross-tab analysis with Chi-square test for q7 and q19 Table 8.17.a: Cross-tab analysis for q7 and q19

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Table 8.17.b: Chi-square test for q7 and q19

Figure 8.13: Distribution of responses for q19 crossing q7

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As seen from the cross-tab analysis (table 8.17.a), the distribution of responses in each group of people is following a similar proportion, “agree” and “tend to agree” dominate respondents’ answer toward q19. The following Chi-square test (table 8.17.b) makes it clear that all the differences between each pair of expected and actual numbers in the cross-tab are due to random chance (p=0.366>0.05), suggesting most respondents consider the given Audi comparative ad are quite aggressive in its nature, no matter whether they love this brand or not. 8.2.2.13

Cross-tab with Chi-square test and one-way ANOVA analysis for

q7 and q20 Table 8.18.a: Cross-tab analysis for q7 and q20

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Table 8.18.b: Chi-square test for q7 and q20

Table 8.18.c: Frequency distribution of responses for q20, break down by q7

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Table 8.18.d: One-way ANOVA analysis for q20, break down by q7

Table 8.18.e: Post Hoc tests for q20, break down by q7

Figure 8.14: Distribution of responses for q20 crossing q7

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After performing cross-tab analysis with Chi-square test for q7 and q20, the measure of variable q20 will be specified as “scale” to conduct the one-way ANOVA analysis. As seen in table 8.18.a, combined “tend to disagree” and “disagree” together, 80.5% “neutral” and 90.2% BMW supporters are not willing to purchase Audi cars in the future after seeing this given Audi comparative ad. However, there are 69.4% of Audi supporters still consider Audi as their preferred brand in the next purchase. Both Chi-square test (table 8.18.b) , p=0.000, and one-way ANOVA analysis (table 8.18.d) reveal that personal brand preference is a significant factor to determine people’s willingness to purchase for the brand initiating the comparative ad campaign in this Audi case, F (2, 217) = 40.812, p=0.000. A LSD post hoc test has been employed to further investigating the effect of

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people’s brand preference in this Audi case. As seen in table 8.18.e, Audi supporters’ average opinion (M=2.24) regarding q20 are significant different from those in group “BMW” (M=3.31) and “neutral” (M=3.14), p(Audi vs. BMW)= 0.000, p(Audi vs. neutral)=0.000. That means the given Audi comparative ad is generally harmful for raising customer’s desire to buy for Audi brand, this is exactly the case for people who don’t have a significant brand preference on Audi. However, when it comes to Audi supporters, more than half of them still insist on their favorite brand in the next purchase, given that the Audi comparative ad has been shown. 8.2.2.14

Cross-tab analysis with Chi-square test for q7 and q21 Table 8.19.a: Cross-tab analysis for q7 and q21

Table 8.19.b: Chi-square test for q7 and q21

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Figure 8.15: Distribution of responses for q21 crossing q7

According to the Chi-square test (table 8.19.b), q7 and q21 are mutual independent (p>0.05). Most people in all of the three groups believed that the given Audi comparative ad will have a negative impact on its brand credibility. 8.3

H3-related Findings

The second section in the questionnaire displayed two fictional BMW ads, the 96


Ad-1 is a non-comparative ad, and the Ad-2 is a comparative one. All questions asked in this section are aimed at investigating whether comparative advertising strategy is suitable for adopting by premium automotive brands. In this stage, our third hypothesis “Non-comparative ad is more appropriate for premium car brands” will be validated by doing descriptive analysis on q8, q9, q10, q11, q14, and q15. The measure of all these variables has been switched from “scale” to “nominal”. 8.3.1

Descriptive Analysis of q8 and q9

Table 8.20.a: Frequency distribution of respondents’ choice regarding q8 “Which ad communicate the clearest message that BMW brings you the excellent driving pleasure”

Table 8.20.b: Frequency distribution of respondents’ choice regarding q9 “Which ad do you like to choose as a formal BMW ad given that you are a senior manager of BMW AG marketing department”

Most people (82.6%, n=185) believe that the non-comparative BMW ad (Ad-1) communicated the message embedded in both ads more effectively compared to the comparative one (Ad-2). Similar result is also unveiled from

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the analysis of q9, where 87.1% (n=195) of respondents chose the Ad-1as their final ad proposal for BMW. 8.3.2

Descriptive Analysis of q10 and q11

Table 8.21.a: Frequency distribution of respondents’ answer regarding q10 “Ad-1 is too simple, it can be easily ignored by the audience”

Table 8.21.b: Frequency distribution of respondents’ answer regarding q11 “Ad-2 is more likely to be remembered by the audience”

45.1% (n=101) respondents put their votes into “disagree” for the statement “Ad-1 is too simple that can be easily ignored by the audience”. Combined with people who “tend to disagree” this statement, there are 74.1% (n=166) of respondents don’t think the Ad-1 is a rough works. In regard to the Ad-2, only 10.3% (n=23) respondents believe that the comparative BMW ad is more likely to be remembered than the non-comparative one; while most people (70.1%, n=157) do not stand for this viewpoint.

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8.3.3

Descriptive Analysis of q14 and q15

Table 8.22.a: Frequency distribution of respondents’ opinion regarding q14 “For an established brand, it’s stupid to mention competitors in ads as the Ad2 did”

Table 8.22.b: Frequency distribution of respondents’ opinion regarding q15 “Ad-2 will result in a decreased brand credibility of BMW in the audience’s eyes”

As seen in table 8.22.a, 51.8% (n=116) of respondents fully believe that comparative advertising is not a good idea for premium car manufacturers to market their products. Notably, only 4.0% (n=9) of respondents do not agree on this stand. When it comes to table 8.22.b, we can find that 74.6% (n=167) respondents generally agree on the statement “Ad-2 decreased BMW’s brand credibility”. In contrast, only a small number of respondents (8.0%, n=18) don't believe that the comparative BMW ad have a negative effect on this brand’s image. 99


Part â&#x2026;Ł

Conclusion

100


Chapter 9

Research Conclusion Two brands are selected as cases in the quantitative research phase for testing H1: Pepsi, a well-known beverage brand in FMCG industry; and Audi, famous for manufacturing premium vehicles. Both of them have ever used comparative advertising to challenge the market leaders in their respective categories. And both of their comparative ads attached on our questionnaires featuring products of the brand they intended to attack. However, peopleâ&#x20AC;&#x2122;s responses toward these two cases are seemingly not so identical. The Pepsi ad received more positive reviews in comparison with the other. Most respondents rated the given Pepsi comparative ads as interesting, creative, and well-designed as suggested in section 8.1.1. Importantly, it appears to convince more consumers, and also raises their purchase willingness more significantly compared to the Audi ad (section 8.1.2 and 8.1.3). We can confidently conclude that the result of using comparative advertising is different in FMCG and premium car market. H1 has been proved to be valid. In order to test H2-1, all respondents have been divided into three sub-groups according to their prior preference between Pepsi and Coca-Cola: Pepsi 101


supporters, Coca-Cola supporters, and neutrals. Regarding to the given Pepsi comparative ad, we found that it is being more recognized, and perceived to be more convinced by Pepsi supporters. More importantly, compared to people who love Coca-Cola, Pepsi people are significantly more willing to choose Pepsi brand in their next purchase after watching these ads, according to the analysis in section 8.2.1.1. In fact, in many of our testing variables, most negative responses toward the given Pepsi comparative ad are flowing from Coca-Cola supporters. All these results suggest that there is a strong link between customers’ prior brand preference and their attitudes toward this Pepsi comparative advertising. We’ve got plenty of evidence to validate the hypothesis that one’s prior brand experience is a significant factor in accessing comparative ads in the context of FMCG market. Moving onto the premium car market, a pair of fictive BMW ads was added to test H2-2. Similar to the method for testing H2-1, respondents are grouped into Audi supporters, BMW supporters, and neutrals according to their preference between Audi and BMW. Regarding comparative advertising itself, both of Audi and BMW supporters accepted the fact that this type of advertising is very aggressive in its nature; it could decrease a brand’s credibility, and increase consumer awareness of competitors’ brands (Levine, 1976; Diamond, 1978). However, compared to Audi supporters and neutrals, there are significant larger percentage of BMW supporters believed it is a stupid idea to use comparative advertising for BMW (section 8.2.2.7). As we discussed earlier, the principle of comparative advertising is perceived as persuading the consumer to buy (Hall, 2001). However, as can be seen in our analysis results, its actual effectiveness will be altered in accordance to the recipient’s prior preference and experience. For the vast majority of Audi supporters, neither do they think they’ve been 102


convinced by the given BMW comparative ad, nor are they willing to change their mind to buy a BMW in their next purchase because of the show of this ad. This is also the case for the neutrals. BMW supporters, on the other hand, significant distinguish themselves by their completely opposite attitudes. Nearly two third of them felt this BMW comparative ad is convincing, and more than half of them still consider BMW as their first choice when buying cars (section 8.2.2.5 and 8.2.2.6). When it comes to the Audi comparative advertising, most Audi supporters believed this ad is telling the truth, whereas a much smaller percentage of BMW supporters also believe so (section 8.2.2.11), suggesting the perceived persuasive power of comparative advertising is varied, depending on individual customer’s existing brand preference. Furthermore, after showing our selected Audi comparative ads, the vast majority of BMW supporters, as well as neutrals, stated they become less likely to buy Audi cars in the future. On the contrary, a lot of Audi supporters thought this kind of Audi ads further improved their willingness to buy for Audi (section 8.2.2.13). All of these findings make us realized that, individual’s brand preference must be taken into account when we evaluate the effectiveness of comparative advertising. The second hypothesis “one’s prior brand experience is a significant factor in accessing comparative ads” has been validated, in both the context of FMCG and premium car market. This research also provides insights for advertisers to choose between comparative and non-comparative advertising strategies for premium car brands. Most respondents, regardless of their brand preference, believed that adopting comparative advertising strategy is a stupid choice for premium car brands (section 8.2.2.7), because of its long-term threats to the brand credibility (section 8.2.2.8 and 8.2.2.14). More importantly, non-comparative advertising is considered to be capable of communicating clearer messages

103


than comparative advertising. Therefore, non-comparative advertising is perceived to be a more appropriate and effective way to enhancing a premium car brand’s image, according to section 8.3.1. Thus, our third hypothesis has been validated.

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Appendix Ⅰ Dataset Variable settings Name Q1

Label 1CA_before

Q2

2BrandPreference_PC

Q3

3DesignIdea_PC

Q4

4MessageConvincing_PC

Q5

5Choice_PC

Q6

6Summary_PC

Q7

7BrandPreference_BA

Q8

8MessageClarity_BMW

Q9

9FormalAd_BMW

Q10

10Ad1TooSimple_BMW

Values 1=“Yes” 2=“No” 3=“Not sure” 1=“Pepsi” 2=“Coca_Cola” 3=“Don’t care” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Interesting&funny” 2=“Annoying&pointless” 3=“Neutral” 1=“Audi” 2=“BMW” 3=“Neutral” 1=“Non-comparative ad” 2=“Comparative ad” 1=“Non-comparative ad” 2=“Comparative ad” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree”

1-1

Measure Nominal

Nominal

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal

Nominal

Nominal

Nominal

Nominal or Scale


Q11

11Ad2Memorable_BMW

Q12

12MessageConvincing_BMW

Q13

13Choice_BMW

Q14

14AggressiveDesign_BMW

Q15

15BrandDecrease_BMW

Q16

16MessageClarity_Audi

Q17

17StraightForward_Audi

Q18

18MessageConvincing_Audi

Q19

19AggressiveDesign_Audi

Q20

20Choice_Audi

1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree”

1-2

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal or Scale

Nominal or Scale


Q21

21BrandDecrease_Aud i

Age

Gender Education

Ethnicity Employment

1=“Agree” 2=“Tend to agree” 3=“Tend to disagree” 4=“Disagree” 1=“Less than 20” 2=“20-29” 3=“30-44” 4=“45-59” 5=“60 or older” 1=“Female” 2=“Male” 1=“Do not complete high school” 2=“High school” 3=“Some college” 4=“Bachelor degree” 5=“Postgraduate/phd” 1=“Full-time work” 2=“Part-time work” 3=“Student” 4=“Unemployed” 5=“Retired” 6=“Self-employed” 1=“Less than 10000” 2=“10001-20000” 3=“20001-40000” 4=“40001-60000” 5=“60001-80000” 6=“80001-100000” 7=“100001-150000” 8=“More than 150000” 1=“Can’t drive” 2=“Can drive but no car” 3=“Can drive and have car”

HouseholdIncom e

DrivingLicence

CarBrand

Nominal or Scale

Nominal

Nominal Nominal

Nominal Nominal

Nominal

Nominal

Nominal

1-3


Appendix Ⅱ Questionnaire Section One. What's comparative advertising? “I am awesome and you suck” This is the message that most comparative ads delivered. Let’s start with it! Question 1. Have you ever seen comparative ads before? Yes I have

No I haven’t

I’m not sure

Question 2. Which brand do you prefer between Pepsi and Coca-Cola? 

Pepsi

Coca-Cola

Don’t care

Watch these two print ads and answer the following questions:

Question 3. These two ads are well-designed, and their ideas are very creative 

Agree

Tend to agree

Tend to disagree

Disagree

Question 4. These two ads effectively convince you that “Pepsi tastes better and even more popular than Coca-Cola”

II-1


Agree

Tend to agree

Tend to disagree

Disagree

Question 5. After watching these ads, I would like to choose Pepsi sometime in the future 

Agree

Tend to agree

Tend to disagree

Disagree

Question 6. In general, my comments on these two Pepsi ads can be summarized as follow: 

They are interesting and funny

They are annoying and pointless

Nothing special I’m being neutral

Section Two. Comparative advertising and cars Surprisingly, automotive industry is another battlefield of comparative advertising, some big names such as Audi and BMW also get involved in this competition Question 7. To begin with, which brand do you prefer between Audi and BMW? 

Audi

BMW

I’m being neutral

We’ve designed two BMW print ads as shown; please have a look of both before answering these questions:

II-2


Question 8. In your opinion, which one communicates the clearest message that “BMW brings you the excellent driving pleasure?” 

Ad-1

Ad-2

Question 9. If you are the decision-maker of BMW marketing department, which one will you choose as a formal BMW advert? 

Ad-1

Ad-2

Question 10. Ad-1 is too simple, so it can easily be ignored by the audience 

Agree

Tend to agree

Tend to disagree

Disagree

Question 11. In contrast, Ad-2 is more likely to be remembered by the audience 

Agree

Tend to agree

Tend to disagree

Disagree

Question 12. I think BMW is telling the truth in Ad-2, I’ve been convinced that their products are better than those of Audi or Mercedes 

Agree

Tend to agree

Tend to disagree

Disagree

Question 13. I would like to buy a BMW car in the future, because it is better than Audi and Mercedes as they claimed in Ad-2 

Agree

Tend to agree

Tend to disagree

Disagree

Question 14. For an established premium brand like BMW, it’s a stupid idea to mention its competitors as Ad-2 did 

Agree

Tend to agree

Tend to disagree

Disagree

Disagree

Question 15. I believe Ad-2 will decrease BMW’s brand credibility 

Agree

Tend to agree

Tend to disagree

Section Three. Comparative advertising and cars

II-3


Audi has released several comparative advertising campaigns for the US market, where Lexus, BMW, and Mercedes dominate the premium segment. Here I list three screenshots from a TV commercial named “Audi A4, Progress is Beautiful”.

Question 16. The message embedded in this TV commercial is very clear, namely “the advantages of Audi A4” 

Agree

Tend to agree

II-4

Tend to disagree

Disagree


Question 17. This TV commercial let me know their product in a quite straightforward way

III-4


Agree

Tend to agree

Tend to disagree

Disagree

Question 18. I think Audi is telling the truth in this commercial, I’ve been convinced that their products are better than those of BMW and Mercedes 

Agree

Tend to agree

Tend to disagree

Disagree

Question 19. Audi is very aggressive in designing this commercial, because its competitors are even being appeared in the picture as can be seen in screenshots 

Agree

Tend to agree

Tend to disagree

Disagree

Question 10. I would like to buy an Audi in the future, because it is better than BMW and Mercedes as they claimed in this TV commercial 

Agree

Tend to agree

Tend to disagree

Disagree

Question 21. This commercial makes me doubt about Audi’s brand value, because it’s not the proper way to make advertising like this for a premium car brand 

Agree

Tend to agree

Tend to disagree

Disagree

Section Four. Personal Information Your questionnaire is nearly done! Let's end up with some basic questions about you How old are you? 

Less than 20

20-29

30-44

45-59

60 or older

Gender? 

Female

Male

Education level? 

Do not complete high school

High school

Some college

Bachelor degree

Postgraduate/phd

Ethnicity? 

Black or Black British

II-5


White

Asian or Asian British

Mixed

Other ethnic groups

What’s your employment status? 

Full-time work

Part-time work

Student

Unemployed

Retired

Self-employed

Household yearly income: 

Less than £10000

£10001-£20000

£20001-£40000

£40001-£60000

£60001-£80000

£80001-£100000

£100001-£150000

£More than £150000

Can you drive? 

No I can’t

Yes I can, but I don’t have car

Yes I can, and I have cars

II-6


Appendix â&#x2026;˘ List of sample sources in participant observation http://www.forbes.com/ http://www.wired.com/autopia/ http://www.autoevolution.com/ http://www.am-online.com/ http://autotraderblog.co.uk/ http://www.autospies.com/ http://adage.com/channel/mediaworks/1 http://www.bmwblog.com/ http://paultan.org/ http://www.egmcartech.com/ http://carscoop.blogspot.com/ http://www.autoblog.com/ http://www.youtube.com/ http://www.facebook.com/ http://www.worldcarfans.com/

III-1


Assessing the Effectiveness of Using Comparative Advertising in Premium Car Segment