FACULTÉ DES SCIENCES SOCIALES ET POLITIQUES/ SOLVAY BRUSSELS SCHOOL OF ECONOMICS AND MANAGEMENT

MEMOIRE  

 

Présen té  en  vue  de   l ' ob ten t ion  du  Maste r  en   I ngén ieu r  de  ges t ion ,  à   f i na l i t é   spéc i a l i sée  

  

Shifting advertising strategies and designs –  Consequences for brand perception 

 Par Michaël Perez‐Diaz 

  Directeur: Professeur Christian Bluemelhüber Commissaire: Professeur Kim Oosterlinck  

 

Année  académique  2008   ‐  2009  

   

Abstract  The purpose of this research is to determine to what extent the impact of the shift from provocative to more traditional advertising strategies for Benetton, Diesel, and Sisley on some affective and conative variables – attitude toward the ad (Aad), attitude toward the brand (Abr), and purchase intentions (PI) – is influenced solely by the effect of the change in the picture/content of the advertisements or also by the effect of the consumers’ perceptions of the product brands. Two main findings – (1) the provocative Benetton, Diesel, and Sisley ads show lower Aad and Abr scores than the more traditional ones and the provocative Benetton ad shows lower PI scores than the more traditional one ; (2) the Aad scores related to the Benetton ads and the provocative Diesel ad and the Abr and PI scores related to the Benetton, Diesel, and Sisley ads are based on an evaluation of the entire advertisements and are influenced in a positive way by brand names – demonstrate that the impact of the shift from provocative to more traditional advertising strategies on the Aad scores related to the Benetton and Diesel ads and on the Abr scores related to the Benetton and Sisley ads is not influenced solely by the change in the picture/content of the ads but also by the consumers’ perceptions of the product brands. It follows that Aad would be a predictor of brand attitudes whereas Abr would be a predictor of ad attitudes and that PI are generally not influenced by the brands’ advertising strategies considered but rather by the product brands considered. We finally find evidence that brands which used to rely for several years on provocation can change consumer perceptions more efficiently in terms of Aad and Abr scores by shifting to more traditional advertising strategies under the same brand names than under new ones.

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1. Introduction 

1.1. Provocation, it seems, does not sell like it used to While the Italian clothing firm Benetton seems to be the originator of provocative appeals1 in advertising in the latter half of the 1980’s (sex appeals, on the other hand, were first used in advertising as early as the 1850’s) – when it ceased to show in its advertisements the company’s products and featured, instead, images referring to racial issues, religion, death, disease, and war with the sole mention of the company slogan (United Colors of Benetton) –, similar advertising strategies were quickly adopted by many other clothing and fashion brands, and in other sectors as well. Consequently, provocation in advertising became such a commodity that the notion it could persuade us to purchase unrelated commodities became redundant. As advertisers searched for a way to draw attention to their messages, the use of sexual/provocative appeals indeed increased, became more explicit, and appeared in magazines with a broader audience over the years (Reichert, Lambiase, Morgan, Carstarphen, and Zavoina, 1999 ; Shapiro, 1993 ; Soley and Kurzbard, 1986 ; Soley and Reid, 1998). Nowadays, according to Manceau and Tissier-Desbordes (2005), provocation in advertising seems confronted to a double constraint. The first is to arouse interest in a polluted advertising environment2. While a look at the academic literature shows that the use of nudity and sexual stimuli (e.g., Ford and LaTour, 1993 ; Steadman, 1969) and/or other provocative stimuli (e.g., Aaker and Bruzzone, 1985 ; De Pelsmacker and Van Den Bergh, 1996 ; Vézina and Paul, 1997) in advertising has the effect of increasing attention to advertisements (Baker, 1961 ; Belch, Belch, and Villarreal, 1987 ; Bello et al., 1983 ; Chestnut, LaChance, and Lubitz, 1977 ; Dudley, 1999 ; Reichert, Heckler, and Jackson, 2001 ; Reid and Soley, 1983) – but typically without a corresponding advantage for brand information processing such as attention to the product or brand, brand name recall, and brand recognition (Alexander and Judd, 1978 and 1983 ; Belch, Belch, and Villarreal, 1987 ; Blair, Stephenson, Hill, and Green, 2006 ; Chestnut, LaChance, and Lubitz, 1977 ; Edell and Staelin, 1986 ; Grazer and Keesling, 1995 ; Horton, Lieb, and Hewitt, 1982 ; Reichert, Heckler, and Jackson, 2001 ; Reid and Soley, 1981 and 1983 ; Richmond and Hartman, 1982 ; Steadman, 1969) –, most Americans report being turned-off by sexy ads and less likely to purchase products that feature sexual imagery in ads (Fetto, 2001). A study produced by HeadlightVision, a U.K. unit of the world’s second-largest advertising company, WPP Group, and conducted in 14 cities indeed concludes that young urban consumers are tired of sexually explicit advertising. In the same perspective, Britain’s Chartered Institute of Marketing (CIM) found in a 2003 survey of 1,000 people above 15 that only 6% enjoyed or were influenced by sexual images in ads (in Lynn, 2004). Matthew Hirst, the editor of D_Code, a Headlight publication, accuses the quantity of sexual advertising ; a few years ago, as much as one-fifth of magazine and web advertisements and one-tenth of

1 Defined as the “connection between the product being advertised and some need or desire that the audience perceives” (Reichert and Lambiase, 2003, p.43). While logical or rational appeals try to induce a sale by focusing on utilitarian needs associated with the product or service, emotional appeals focus on the satisfaction that comes from purchasing the product and the fulfillment of the customer’s needs and desires. 2 As mentioned by Reichert and Lambiase (2003), “advertisements compete not only with each other, but also with the whole range of choices available to consumers, with other channels, not to mention other media.” (p.137)

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television commercials featured sexual appeals3 (Lin, 1998 ; Reichert, Lambiase, Morgan, Carstarphen, and Zavoina, 1999 ; Reichert, 2007 ; Walker, 2000). According to him, “We are dealing with a generation that has grown used to being surrounded by sexual imagery”, so “explicit imagery doesn’t have the same impact any more” (in Lynn, 2004). The second constraint provocation in advertising is facing today is to respond to the needs and wants of contemporary men and women more concerned with egalitarism and ethics. Although “Stratégies”4 magazine saw dead and sex as the double major trends in advertising in 2002, it seems that young people of today are more interested in traditional family values and wholesome ad messages than the flash of a nipple to sell a product. “People are looking for things that are more real, more wholesome, more pure”, says Paul Gostick of the CIM. Even agencies specialized in striking provocative themes, such as TBWA, which invented the controversial “FCUK” logo for U.K. retailer French Connection, a clothing brand, recognize that a saturation point has been reached. “There has been a shift. We went through an era where sex was a means of shocking consumers, and that doesn’t work any longer”, says Andrew McGuinness, the agency’s chief executive. As an illustration, French Connection’s profit and sales growth slowed about two weeks before the decision to drop its “FCUK” logo from its next ad campaign was taken in 2004 (Lynn, 2004). Because the campaign with death-sentenced prisoners received a lot of bad criticism in the USA and led to negative repercussions, Benetton is now focusing on peaceful and loving campaigns, as well as Diesel which has also changed its advertising strategy (Andersson, Hedelin, Nilsson, and Welander, 2004). Another example is U.S. retailer Abercrombie & Fitch which successfully used sex appeals in the 1990’s – increasing its revenues from $85 million to $1.35 billion over a nine-year period (Reichert, 2003) – but decided in December 2003 to stop publishing a quarterly catalogue that sparked complaints over photos of scantily clad models and led to a 13% sales decline at existing stores the month before the decision was taken (Lynn, 2004). However, whereas certain disliked shock advertisements (e.g., Benetton’s advertising campaign using death row inmates) did not provide tangible benefits (de Chenecey, 2000 ; Lippert, 2000), others (e.g., Calvin Klein’s 1995 child exploitive advertisements) participated in the brand’s subsequent profitability (Rees, 1995). Consequently, provocative imagery must now be handled with extreme caution and any marketer knows this perfectly well. Suggestions such as “provocation is likely to remain a viable option for any advertiser striving to reach consumers in an increasingly tight and saturated commercial environment” (Vézina and Paul, 1997, p.178) or “shocking pictures have become ‘the most effective way of selling commodities today’” (Giroux, 1994, p.4 in Andersson, Hedelin, Nilsson, and Welander, 2004) do not seem true anymore. “Instead, firms will have to find another way to promote their goods. Maybe they could just say what it is, what it does and how much it costs. Now, that really would be shocking.” (Lynn, 2004)

3 A few years ago, several analyses revealed that 26% of full-page or larger ads in high-circulation magazines contained sexual images of people (Reichert and Carpenter, 2004), that 12% of prime-time commercials featured a model in a state of undress and 8% of commercials contained sexual conduct or behaviour (Lin, 1998), and that sexual content was present in 17% of ads on news sites and 23% of ads on sports sites (Ramirez, 2006 in Reichert, 2007). 4 Stratégies (2002), “La mort leur va si bien” and “Montrez ce sexe”, N°1262, December 20, pp.8-10.

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1.2. Research purpose The research purpose is to determine whether the impact of the shift from provocative to more traditional advertising strategies recently operated by many brands on some affective and conative variables5 – attitude toward the ad, attitude toward the brand, and purchase intentions – is influenced solely by the effect of the change in the picture/content of the advertisements or also by the effect of the consumers’ perceptions of the product brands. After a review of the literature, Part 2 of the article will present the research methodology as

as t the research purpose. The art 3. Finally, the important discussed in Part 4.

well the hypotheses and research questions considered to meeresults of the experiment will then be presented and discussed in Pfacts, limitations, and recommendations for future research will be

2. The theoretical research 

2.1. Literature review

2.1.1. Rationale The research purpose has been driven by the view according to which “The values that are spread [by the ad and/or brand] and how they in turn effect the consumer are important for the future of the product (Hägg et al., 1972 [in Andersson, Hedelin, Nilsson, and Welander, 2004, p.103]).” As an illustration, the authors found that the attitudes toward a Benetton advertisement used in their research “were mostly feelings about their advertising campaigns through the years and not only the picture itself.” (ibid., p.107) Moreover, it is widely recognized that advertisers do not only use sexual appeals to grab attention to their ads, but to position their brands as sexual. If the same holds true for other provocative stimuli, then the question is whether brands which used to rely for several years on provocation – considered as an original and distinctive execution strategy (Vézina and Paul, 1997) – can easily change consumer perceptions by shifting to more traditional advertising strategies. Mitchell (1986) indeed asks whether the attitude toward the ad is based only on the effect of the picture used in the ad or on a general evaluation of the entire advertisement (including the brand name). If the latter appears to be true, then the attitude toward the ad would be a better predictor of brand attitudes than a measure of the subjects’ evaluation of the picture used in the advertisement. This is the rationale for the research purpose presented in section 1.2.

2.1.2. A definition of provocation in advertising The definition of provocation in advertising that will be adopted in this research6 is the one given by Vézina and Paul (1997) which is as follows : “a deliberate appeal, within the content 5 The principal measures of advertising effectiveness constitute of three steps typically ranging from the cognitive (awareness, knowledge), to the affective (liking, preference), to the conative (conviction, purchase) variables. Because awareness and knowledge of advertisements depend on various factors hardly measurable or controllable in the context of an experiment, these will not be assessed in this research. For instance, the advertising budgets, which determine the level of the ad’s exposure (repetitions), remain unknown and consumer awareness may result more from exposure to stores than from exposure to advertisements (Vézina and Paul, 1997). 6 The provocation considered in this research is associated with the advertising execution (Dahl et al., 2003 ; De Pelsmacker and Van Den Bergh, 1996 ; Vézina and Paul, 1997) and not with the product advertised (Fahy et al.,

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of an advertisement, to stimuli that are expected to shock at least a portion of the audience, both because they are associated with values, norms or taboos that are habitually not challenged or transgressed in advertising, and because of their distinctiveness and ambiguity.” (p.179) Equally, De Pelsmacker and Van Den Bergh (1996) recognize that provocation in advertising appears to operate through the three constructs highlighted by the previous authors – distinctiveness, ambiguity and transgression of a social or cultural taboo – and, drawing on the findings of Vézina and Paul (1997), Pope, Voges, and Brown (2004) note that “Transgression of a social or cultural taboo is perhaps the most crucial element in a provocative advertising effort” (p.70). This definition, coupled with the other main feature of provocative advertising, which is that the product is usually not a central element in the ad7 (Maclnnis and Stayman, 1993), will serve as a basis for selecting the provocative ads used in this research, with the more traditional ads being those that do not meet this definition.

2.1.3. Affective variables Implicit in studies analyzing advertisements for one form as opposed to another is the idea that consumer response to one is different from the response to the other. As argued by previous literature conducted in the field, such a difference in response would be found in respondents’ attitude8 toward the ad (Aad) and attitude toward the brand (Abr). Aad appears to be an important mediator within the persuasion process (Mitchell and Olson, 1981). However, contradictory results emerge as to the impact of sexual and/or other provocative stimuli in advertising on Aad. On the one hand, such appeals have been shown to result in a significantly less favorable Aad than ads that contain little or no such appeals (De Pelsmacker and Van Den Bergh, 1996 ; Henthorne and LaTour, 1994 ; LaTour, Pitts, and Snook-Luther, 1990 ; Reichert et al., 1999 ; Sanbonmatsu and Kardes, 1988 ; Smith et al., 1995), and to lead to more offensive evaluations of the ads (Belch et al., 1981). On the other hand, they have also been shown to create a more favorable Aad than ads that contain little or no such appeals (Pope, Voges, and Brown, 2004 ; Reichert, Heckler, and Jackson, 2001 ; Severn, Belch, and Belch, 1990), possibly resulting from an increase in attention (Lang, Schneider, and Deitz, 1999 ; Yoon et al., 1998). One plausible explanation for these contradictory findings of previous research is related to methodological aspects : “Most studies hardly isolate the consequences of the taboo presence from the other elements making up an ad.” (Manceau and Tissier-Desbordes, 2006, p.17) Besides the picture/content of the ad, other factors such as the product brand represented might have an influence on Aad, hence the interest of this research. Previous research findings concerning the impact of controversial stimuli in advertising on Abr seem to be more straightforward, several studies (e.g., Henthorne and LaTour, 1994 ; Lundstrom and Sciglimpaglia, 1977 ; Reichert et al., 1999) revealing that an ad that contains a strong overt sexual appeal results in a significantly less favorable Abr than an ad that contains 1995 ; Katsanis, 1994 ; Shao and Hill, 1994 ; Triff et al., 1987 ; Waller, 1999 ; Wilson and West, 1981) because, as Vézina and Paul (1997) suggested, “Advertisements for firearms or for certain contraceptive methods, for instance, could be perceived, in many countries, as highly provocative even if the copy were presented in a traditional format” (p.190). 7 Klinthage (1998 in Andersson, Hedelin, Nilsson, and Welander, 2004, p.100) indeed states that “Because of the way Diesel has chosen to create their advertising, it is not always easy to understand at first sight what the pictures really are advertisements for.” 8 Defined as “a general and enduring positive or negative feeling about some person, object, or issue” (Petty and Cacciopo, 1981, p.7), attitudes are often considered relatively stable over time, and should hence be useful predictors of consumers’ behaviour toward a product or service (Mitchell and Olson, 1981).

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little or no sexual appeal. Other authors go one step further by arguing that a strong overt sexual content, while increasing attention and interest, might lead to a denial of the ad and be harmful to the brand image (Aaker and Bruzzone, 1985 ; De Pelsmaker and Van Den Bergh, 1996 ; LaTour and Henthorne, 1995 ; Severn, Belch, and Belch, 1990 ; Vézina and Paul, 1997). Consequently, and similarly to the remark previously made for Aad, besides the product brand represented, other factors such as the picture/content of the ad seem to have an influence on Abr. The interest of this research therefore also appears here. We indeed know from the findings of Gardner (1985) and those of Mitchell and Olsen (1981) that Abr is formed from brand attribute information already held by the consumer, combined with attitude toward the picture/content of the ad. This relationship between both variables (Aad and Abr) may be bidirectional – the indirect effects model (Homer, 1990 ; MacKenzie, Lutz, and Belch, 1986) which states that preexisting Abr would translate and interact with Aad in the formation of new Aad and Abr – or direct and singular from Aad to Abr – the independent effects model (Biehal, Stephens, and Curlo, 1992) which states that Aad has a direct effect on brand choice and an indirect effect through Abr. “Each model appears to operate at different times and they may, in fact, work in conjunction.” (Pope, Voges, and Brown, 2004, p.71) A critical implication to bear in mind is that a negative Aad does not necessarily lead to a negative Abr (e.g., De Pelsmacker and Van Den Bergh, 1996) because “positive and preexisting feelings about a brand might moderate, or even remove, any negative impact of Aad on Abr.” (Pope, Voges, and Brown, 2004, p.71) On the other hand, the positive association model (like the ad, like the brand) will tend to hold in situations where there is a low motivation to process information (Petty and Cacioppo, 1981 ; Ray and Batra, 1983).

2.1.4. Conative variables As the use of sexual and/or other provocative stimuli in ads has been shown to create arousal (Belch et al., 1982 ; LaTour, 1990 ; Smith et al., 1995), such arousal may itself influence purchase intensions (PI), stimulate the consumer, and give a direction to his/her intentions (Reichert, 2002). However, while some studies demonstrate that the use of sexual appeals in ads may influence PI in a positive way (Dudley, 1999 ; Grazer and Keesling, 1995 ; Severn et al., 1990), others reveal that an ad which contains a strong overt sexual appeal results in a significantly less favorable level of PI than an ad that contains little or no sexual appeal (Henthorne and LaTour, 1994 ; Reichert et al., 1999). Yet, some authors argue that PI do not vary according to the degree of provocation of the ads ; the relation between both variables would be very weak (Bello et al., 1983 ; De Pelsmacker and Van Den Bergh, 1996). In this latter case, critical consumer attitudes toward a brand’s advertising strategy would translate into a minimal reduction in PI (Pollay and Lysonski, 1993), and criteria other than the content of the ad would therefore influence PI such as brand loyalty, brand recognition, and product (dis-)satisfaction. This research will allow to verify this hypothesis.

2.2. Research methodology

2.2.1. Experimental design and overall plan of analysis In order to meet the research purpose presented in section 1.2, the following experimental design, composed of four samples, and plan of analysis, composed of three steps, will be adopted. Respondents were randomly assigned to one of the four samples. In Sample 1, respondents answered questions about three different ads, each one associated with a different brand – the

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three ads include a provocative content and the brand names are shown (brand-test) – ; in Sample 2, respondents answered questions (the same as in Sample 1) about three different ads, each one associated with a different brand (the three brands are the same as in Sample 1) – the three ads include a more traditional content and the brand names are shown (brand-test) – ; the design of Sample 3 is the same as Sample 1 except that the brand names are hidden and renamed “I”, “J”, and “L”9 (blind-test) ; the design of Sample 4 is the same as Sample 2 except that the brand names are hidden and renamed “I”, “J”, and “L” (blind-test). The experimental design is illustrated in Figure 1. Figure 1 : Experimental design

Sample 1

Brand‐Test

Benetton Brand 

Provocative ad

Brand‐Test

Diesel Brand

Provocative ad

Brand‐Test

Sisley Brand

Provocative ad

Sample 2

Brand‐Test

Benetton Brand (renamed "I")

Non‐provocative ad

Brand‐Test

Diesel Brand (renamed "J")

Non‐provocative ad

Brand‐Test

Sisley Brand (renamed "L")

Non‐provocative ad

Sample 3

Blind‐Test

Benetton Brand 

Provocative ad

Blind‐Test

Diesel Brand

Provocative ad

Blind‐Test

Sisley Brand

Provocative ad

Sample 4

Blind‐Test

Benetton Brand (renamed "I")

Non‐provocative ad

Blind‐Test

Diesel Brand (renamed "J")

Non‐provocative ad

Blind‐Test

Sisley Brand (renamed "L")

Non‐provocative ad

The questionnaires were administered in French via the Internet. The blocks of questions pertaining to each ad, as well as the questions within each block, were randomized so that respondents did not all started to answer to the same questions pertaining to the same ad. An answer to every question, except to the socio-demographic ones (gender, age, and year of study), was required for the questionnaires to be submitted. Ad exposure was not limited : each ad was visible as long as an answer to every corresponding question was not given. “As argued by Calder and Sternthal (1980), showing the stimulus commercials again allows a direct comparison of reactions to the commercials across treatment conditions without distortion by subjects’ memory of the commercials.” (Batra and Ray, 1986, p.243) However, the conditions for ad processing were atypical for two main reasons : (1) ad exposure was forced, thus respondents were processing in a fairly high involvement state ; (2) ad exposure was isolated, but the environment surrounding respondents at the time they completed the questionnaires might have diverted processing. The first step of the analysis will be to determine whether the impact of the shift from provocative to more traditional advertising strategies recently operated by many brands on Aad (in the case of hypothesis 1), Abr (in the case of hypothesis 2), and PI (in the case of hypothesis 3) is significant for each of the three brands considered. The following methodology will be adopted. Aad (in the case of hypothesis 1) will be measured in the four samples for the three ads of each sample. If the shift from provocative to more traditional 9 To eliminate the influence of prior brand learning on the advertising content, fictitious brand names (the letters “I”, “J”, and “L”) were used in the blind-tests on the basis that individuals make relatively few associations with these letters (Mitchell and Olson, 1981). Similarly, this approach has been used previously by other authors (Peterson and Kerin, 1977 ; Simpson, Horton, and Brown, 1996 ; Stafford and Day, 1995).

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advertising strategies has an impact on Aad for a particular brand, the difference in Aad between Sample 1 and Sample 2 and/or between Sample 3 and Sample 4 should be significant for the brand considered. The same methodology will be adopted for Abr (in the case of hypothesis 2) and PI (in the case of hypothesis 3). The second step of the analysis will be to control for the change in the picture/content of the advertisements to determine whether the influence of the product brand on Aad (in the case of research question 1), Abr (in the case of research question 2), and PI (in the case of research question 3) is significant for each of the six ads considered. The following methodology will be adopted. Aad (in the case of research question 1) will be measured in the four samples for the three ads of each sample. If there is no influence of the product brand on Aad for a particular provocative ad, the difference in Aad between Sample 1 and Sample 3 should not be significant for the provocative ad considered. If there is no influence of the product brand on Aad for a particular more traditional ad, the difference in Aad between Sample 2 and Sample 4 should not be significant for the more traditional ad considered. If significant differences in Aad are observed between Sample 1 and Sample 3 for a particular provocative ad or between Sample 2 and Sample 4 for a particular more traditional ad, then this would provide strong evidence that Aad, for the ad considered, is based on an evaluation of the entire advertisement and hence that the brand name influence Aad. The same methodology will be adopted for Abr (in the case of research question 2) and PI (in the case of research question 3). The third step of the analysis will be to determine whether the impact of the shift from provocative to more traditional advertising strategies on Aad, Abr, and PI is influenced solely by the effect of the change in the picture/content of the advertisements or also by the effect of the consumers’ perceptions of the product brands. The following methodology will be adopted. Firstly, using the results from the first step, only the cases where the impact of the shift from provocative to more traditional advertising strategies on Aad, Abr, or PI is significant both in the brand- and blind-tests will be considered10, i.e. the cases where the difference in Aad, Abr, or PI between Sample 1 and Sample 2 and between Sample 3 and Sample 4 is significant. Secondly, using the results from the second step, if the impact of the shift from provocative to more traditional advertising strategies on Aad for a particular brand is influenced solely by the effect of the change in the picture/content of the advertisements, then the difference in Aad between Sample 1 and Sample 3 and between Sample 2 and Sample 4 should not be significant for the brand considered. If the difference in Aad between Sample 1 and Sample 3 and/or between Sample 2 and Sample 4 is significant for a particular brand, then this would provide strong evidence that the impact of the shift from provocative to more traditional advertising strategies on Aad for the brand considered is not influenced solely by the change in the picture/content of the advertisements but also by the consumers’ perceptions of the product brand. And similarly for Abr and PI.

2.2.2. Brand advertisements The advertisements used in this research were selected according to three main criteria. Firstly, the type of media : the ads used for the experiment are print ads appearing worldwide on posters, billboards, and in magazines11. Secondly, the sector : the ads used for the 10 Otherwise, no comparison is made possible between the impact of the shift from provocative to more traditional advertising strategies on Aad, Abr, and PI in the brand-tests and in the blind-tests. 11 Cosmopolitan, Elle, Elle Belgium, Elle UK, Gael, Glamour, Glamour Spain, Marie Claire, Marie Claire Spain, and Vogue Paris.

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experiment are ads for clothing and fashion brands. Due to the fact that the majority of the provocative ads found in the print media belong to brands in the clothing and fashion sector (Reichert, 2002), this particular product category was selected. This sector was also targeted by several studies on the use of nudity and provocation in advertising (e.g., Vézina and Paul, 1997). Thirdly, the execution strategy : the brands used for the experiment have been famous for their provocative advertising but have recently operated a shift toward more traditional advertisements. The provocative ads used for the experiment meet the definition of provocation in advertising adopted in this research (given in section 2.1.2) whereas the more traditional ads used for the experiment do not meet this definition. The three following brands and six following ads (two for each brand, one provocative and another more traditional) were selected12 : Benetton brand (provocative ad taken from the February 1992 campaign and more traditional ad taken from the August 2008 “Victims” campaign) ; Diesel brand (provocative ad taken from the 1997 campaign and more traditional ad taken from the Autumn/Winter 2008/2009 campaign) ; Sisley brand (provocative ad taken from the 2001 “Jamaica” campaign and more traditional ad taken from the Spring/Summer 2008 campaign). These three brands selected all offer clothes for men and women, are used and purchased by both males and females, and enjoy a more or less equivalent market coverage13. The three provocative ads used in this research embed different kinds of provocative appeals : the provocative Benetton ad relies on the theme of death, the provocative Diesel ad relies on the theme of violence, and the provocative Sisley ad relies on the theme of sex. Distinctiveness of the ad execution may indeed provide greater resistance to ad-specific, or related, information. As analyses are conducted one type of provocation or brand at a time, the purpose of the replication is not to draw conclusions based on one arbitrary example chosen to represent each type of provocation or brand, which is not reasonable, but to allow for explicit attention to the variability of the effect of the shift from provocative to more traditional advertising strategies from one type of provocation or brand to another (Jackson, O’ Keefe, and Brashers, 1994). However, because there is strong reason to expect that all types of provocation or brands share a common, invariant effect, we assume fixed effects (National Research Council, 1992).

2.2.3. Subjects The four samples are composed of students from first, second, and third study cycles between 17 and 28 years of age (the few respondents over 28 were not included in the final samples) randomly contacted by e-mail14 among students from the ULB and other universities and higher education schools in French-speaking Belgium. Although far from being representative of the greater population and despite the fact that the use of non-probabilistic samples can skew findings and threaten external validity (Abelman, 1996 ; Courtright, 1996 ; Potter et al., 1993), these consumer samples are similar in many respects to market segments regularly

12 The ads used in the experiment are presented in Appendix 1. 13 Yet, it was not possible to introduce a control for all the possible variables that might intervene within the advertisements selected (Vézina and Paul, 1997). For example, the ad characteristics were not held fixed : the ads differ from each other in terms of overall form/size and content (only the provocative Diesel ad includes text and they do not all contain a picture of the clothes in use). Nevertheless, “these limitations […] are inherent to any research using examples of real advertisements – as opposed to those created specifically for research purposes” (Vézina and Paul, 1997, p.183). 14 To test for non-response bias, extra incentives (cinema tickets) were used. Because selection error may have biased the results of the convenience samples – i.e., students interested in participating in a research study on advertising appeals may be different from non-participants in their attitudes toward provocative contents (Grazer and Keesling, 1995) –, the true research purpose was hidden to respondents.

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targeted by firms in the clothing and fashion business such as those considered in this research and are more familiar with, interested in, and open to the brands and ads used in this research than older people. Moreover, some have argued that randomization techniques can minimize or solve the non-probabilistic sampling issue (Basil, 1996 ; Lang, 1996) and, while being crucial in the case of surveys, the arguments against the use of convenience samples are less problematic in the case of experiments, which primary goal is to ensure internal validity and determine whether variables are causally related (Lang, 1996 ; Sparks, 1995). Furthermore, most studies concerning the use of nudity and provocation in advertising (e.g., Reichert, Heckler, and Jackson, 2001 ; Simpson, Horton, and Brown, 1996 ; Vézina and Paul, 1997) have used student samples driven by the assumption according to which students demonstrate similar attitudes toward advertising as those expressed by the population at large (Barnes, 1982 ; Zanot, 1984) and seem appropriate subjects for research on causal mechanisms (Kardes, 1996).

2.2.4. Construction of the samples The experiment took place from the 20th of March to the 6th of May 2009. Samples 1, 2, 3, and 4 were initially composed of respectively 172, 148, 232, and 217 observations. In the four samples, the questionnaires included a commercial recognition question (respondents were asked to mention whether they had already seen each of the three ads presented before the experiment) and, only in the blind-tests (Samples 3 and 4), a brand name recognition question (respondents were asked to mention whether they knew which brands were associated with each of the three ads presented). Because respondents’ prior exposure to the advertisements represents uncontrollable influences in any study involving materials from the real world (Richmond and Hartman, 1982), respondents of Samples 3 and 4 who mentioned that they knew which brand(s) was/were associated with at least one of the three ads presented – and who gave the corresponding brand name(s) – were deleted15 from the final samples (45 observations in Sample 3 and 21 observations in Sample 4)16, as well as respondents from each sample who mentioned that they had already seen at least one of the three ads presented before the experiment (17 observations in Sample 1, 9 observations in Sample 2, 5 observations in Sample 3, and 7 observations in Sample 4)17. After these treatments, Sample 1 has a final size of 155 observations, Sample 2 of 139 observations, Sample 3 of 182 observations, and Sample 4 of 189 observations. Figure 2 shows the distribution of samples according to the gender18 and product involvement19 of respondents. We observe that the percentage of women is higher than the percentage of men in each of the four samples (55% of women, except Sample 3 which is made of 63% of women). Concerning respondents’ product involvement, there is a higher number of respondents having a high level of involvement with respect to clothing in Samples 1, 2, and 3

15 These respondents were not compared with the rest of the sample to which they belonged to see whether there were statistically significant differences between the two groups for each sample because too many differences might have been found and should have been analyzed (in provocation, Aad, Abr, and PI scores for the provocative and more traditional ads, in the brand- and blind-tests). Therefore, responses of the respondents who recognized the brands and/or who had already seen the ads were not pooled with the other responses. 16 The corresponding statistics are given in Appendix 2. 17 The corresponding statistics are given in Appendix 3. 18 The corresponding statistics are given in Appendix 4. 19 Each sample was divided into two classes according to respondents’ product involvement scores : “High” (scores ≥ 4.5) and “Low” (scores < 4.5). The threshold of 4.5 was selected because the median of product involvement scores across the four samples varied from 4.2 to 4.8. The corresponding statistics are given in Appendix 5.

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(respectively 61%, 55%, and 64%) whereas, in Sample 4, the number of respondents having a high level of involvement with respect to clothing is lower (44%). Appendix 6 and Appendix 7 give the distribution of samples according respectively to the age and year of study of respondents. Figure 2 : Distribution of samples according to the gender and product involvement of respondents

2.3. Hypotheses and research questions

Based on the research purpose presented in section 1.2 and the theoretical developments discussed in section 2.1, the following hypotheses and research questions are proposed.

2.3.1. Hypotheses The first hypothesis (H.1) suggests that respondents’ reported attitude (Aad) and reaction toward an advertisement using a provocative content will be significantly less favorable than the attitude and reaction toward a different advertisement for the same brand using a more traditional content, as well in the brand-tests as in the blind-tests. Attitude toward the ad is measured by the mean of a six-item, seven-point semantic differential scale borrowed from the Madden, Allen, and Twible (1988) inventory with known psychometric properties and reused by Spears and Singh (2004). The adjectives are “unpleasant/pleasant”, “unlikable/likable”, “boring/interesting”, “tasteless/tasteful”, “artless/artful”, and “bad/good”. A higher mean score on these six scales indicates a more positive Aad. The adjective checklist methodology (Lavidge and Steiner, 1961 ; Mehrotra et al., 1981) is also used in order to gain further insight into the nature of consumer reaction toward provocative and more traditional ads. The questionnaires included an adjective checklist of 16 adjectives – “young”, “violent”, “cheerful”, “trite”, “peaceful”, “indecent”, “original”, “ugly”, “shocking”, “funny”, “too classic”, “sweet”, “sad”, “wise”, “disgusting”, and “tender” – borrowed from several item-analysis scales published (e.g., Leavitt, 1970 ; Wells, 1964) and adopted by Vézina and Paul (1997). The respondents were then asked to pick the adjective(s) which they felt best represented their opinion of each ad. The second hypothesis (H.2) suggests that respondents’ reported attitude toward a brand (Abr) associated with a provocative advertisement will be significantly less favorable than the

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attitude toward the same brand associated with a more traditional advertisement, as well in the brand-tests as in the blind-tests. Attitude toward the brand20 is measured by the mean of a five-item, seven-point semantic differential scale borrowed from Spears and Singh (2004) that exhibits adequate levels of internal consistency and discriminant validity. Moreover, comparative analyses have indicated the efficacy of these measures over competing ones. The adjectives are “unappealing/appealing”, “bad/good”, “unpleasant/pleasant”, “unfavorable/favorable”, and “unlikable/likable”. A higher mean score on these five scales indicates a more positive Abr. The third hypothesis (H.3) suggests that respondents’ reported level of purchase intentions (PI) associated with an advertisement using a provocative content will be significantly less favorable than the level of purchase intentions associated with a different advertisement for the same brand using a more traditional content, as well in the brand-tests as in the blind-tests. Respondents’ level of purchase intentions is measured by the mean of a five-item, seven-point semantic differential scale borrowed from Spears and Singh (2004) that exhibits adequate levels of internal consistency and discriminant validity. Moreover, comparative analyses have indicated the efficacy of these measures over competing ones. The adjectives are “never/definitely”, “definitely do not intend/definitely intend to buy”, “very low/high purchase interest”, “definitely not/definitely buy it”, and “probably not/probably buy it”. A higher mean score on these five scales indicates more positive PI.

2.3.2. Research questions The first research question (R.Q.1) asks whether respondents’ reported attitude toward an advertisement (Aad) using a provocative or a more traditional content will be significantly less favorable in the blind-tests than in the brand-tests. The second research question (R.Q.2) asks whether respondents’ reported attitude toward a brand (Abr) associated with a provocative advertisement or a more traditional advertisement will be significantly less favorable in the blind-tests than in the brand-tests. The third research question (R.Q.3) asks whether respondents’ reported level of purchase intentions (PI) associated with an advertisement using a provocative content or a more traditional content will be significantly less favorable in the blind-tests than in the brand-tests.

2.4. Manipulation checks Manipulation check is carried out to ensure the internal validity of the experiment. It has to be ensured that the provocative ads are perceived as significantly more provocative than the more traditional ads, both in the brand-tests and in the blind-tests. In each sample, respondents rated the degree to which they perceived the three ads they viewed as provocative on a single-item, seven-point semantic differential scale (1 = “not at all provocative” ; 7 =

20 Abr is measured following exposure to the ads as well in the brand-tests as in the blind-tests. In the latter case, the Abr is measured without revealing to the respondents the true brand names but, instead, by asking them to rate their attitude toward brands (named “I”, “J”, and “L”) that would use such ads in their advertising campaigns. Consequently, in the brand-tests, respondents base their Abr on their preexisting learning and experience of these brands but also on the picture/content of the ads whereas, in the blind-tests, respondents base their Abr only on the picture/content of the ads.

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“extremely provocative”) borrowed from Pope, Voges, and Brown (2004). A higher mean score on this scale indicates a higher degree of provocation.

2.5. Confound checks Although the factors discussed in this section are not of primary interest in this research, they are included as moderator variables that might interact with the hypotheses and research questions presented in section 2.3.

2.5.1. Are there any interactions between any of the hypotheses and/or research questions and the gender of respondents ?

Reichert (2007) reports that gender is an important determinant of evaluations and interpretations and that its impact is usually reflected in Aad and Abr. In addition, it is often argued that attitude toward advertising in general (Shavitt et al., 1998), the receptiveness of sex in advertising21 (Elliott et al., 1995), and ad processing22 (Ramirez and Reichert, 2000) vary according to the gender of respondents. As a result, women might be more offended than men by provocative ads, independent from the fact that they contain female depictions. Nevertheless, the findings of De Pelsmacker and Van Den Bergh (1996) seem to challenge this argument by showing that provocation in advertising is perceived equally by men and women.

2.5.2. Are there any interactions between any of the hypotheses and/or research questions and the product involvement of respondents ?

Depending on their level of product involvement, individual consumers differ in the extent of their decision process and their search for information (Laurent and Kapferer, 1985), ad processing (Pope, Voges, and Brown, 2004 ; Wright, 1975), Abr (Marks and Olson, 1981), and purchase process and use of products (Rothschild, 1977 ; Traylor, 1981 ; Tyebjee, 1977). Moreover, product involvement has been shown to influence the conative variables (Vézina and Paul, 1997) and the advertising impact (Petty et al., 1983). As a result, the product involvement of respondents appears to be relevant for setting advertising strategies (Ray, 1982 ; Rothschild, 1979 ; Traylor and Joseph, 1984 ; Vaughn, 1980). The product involvement of respondents with respect to clothing is assessed by six-items (“When other people see me wearing clothes, they form an opinion of me”, “You can tell a lot about a person by seeing what brand of clothes he/she wears”, “Clothes help me express who I am”, “Clothes are ‘me’”, “Seeing somebody else wearing clothes tells me a lot about that person”, and “When I wear clothes, others see me the way I want them to see me”) borrowed from Traylor and Joseph (1984) and scaled in a seven-point agree-disagree format. A higher mean score on these six scales indicates a higher level of product involvement.

21 Several studies report that the attitude of women toward the use of sex in advertising is more negative, even more hostile, than the attitude of males (e.g., Alexander and Judd, 1986 ; Fetto, 2001 ; Peterson and Kerin, 1977). In addition, despite contradictory results, previous research suggests that people react more favourably to advertisements depicting opposite-sex nudity as opposed to same-sex nudity (e.g., Baker and Churchill, 1977 ; Geuens and De Pelsmacker, 1998 ; LaTour, Pitts, and Snook-Luther, 1990). 22 Ramirez and Reichert (2000) show that 35% of the females respond to context compared to 20% of the males and 28% of the females respond to proxemics (references to physical distance or relative interaction between models) compared to 6% of the males. Moreover, female capacity for elaborative processing is greater than that of males (Meyers-Levy and Maheswaran, 1991 ; Meyers-Levy and Sternthal, 1991 ; Meyers-Levy, 1994).

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3. The empirical research 

3.1. Results Each ANOVA conducted in this research is a sample (2) x gender (2) x product involvement (2) factorial design with 8 groups (or cells) and consisting of seven significance tests : a test for each of the three main effects – sample (with two levels : the two samples from which the provocation, Aad, Abr, or PI scores that form the dependent variable are collected) ; gender (with two levels : men and women) ; product involvement (with two levels : high and low) –, a test for each of the three two-way interactions (sample*gender ; sample*product involvement ; gender*product involvement), and a test of the three-way interaction (sample*gender*product involvement). The results of the hypotheses (presented in section 3.1.2) and research questions (presented in section 3.1.3) all pertain to sample main effects. Because a main effect for gender and product involvement would indicate a difference between men and women or between highly and lowly involved respondents with respect to the provocation, Aad, Abr, or PI scores collected from two different samples (across two different treatment conditions), it is inconsequential from a theoretical point of view and has no impact on the analyses. Therefore, only when an interaction between sample and gender (presented in section 3.1.4) or between sample and product involvement (presented in section 3.1.5) is significant, significant gender and product involvement main effects will be reported and discussed.

3.1.1. Manipulation checks In order to ensure that the provocative ads are perceived as significantly more provocative than the more traditional ads, both in the brand-tests and in the blind-tests, six ANOVAs are performed :

- the first, second, and third ANOVAs have respectively the provocation scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 2 as the dependent variable and the sample, gender, and product involvement as independent variables ;

- the fourth, fifth, and sixth ANOVAs have respectively the provocation scores related to the Benetton, Diesel, and Sisley ads collected from Sample 3 and Sample 4 as the dependent variable and the sample, gender, and product involvement as independent variables.

The results23 show that, in the brand-tests (Sample 1 and Sample 2), the difference between the means of the provocation scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 2 is statistically significant – Benetton : 5.43 vs. 4.19, F=34.52, p<.0001 ; Diesel : 4.28 vs. 2.71, F=69.89, p<.0001 ; Sisley : 5.21 vs. 3.44, F=92.19, p<.0001 –, with the provocative ads (in Sample 1) having, on average, higher provocation scores than the more traditional ads (in Sample 2). Similar results24 are found in the blind-tests (Sample 3 and Sample 4) – Benetton : 5.43 vs. 4.20, F=50.95, p<.0001 ; Diesel : 4.25 vs. 2.74, F=79.55, p<.0001 ; Sisley : 5.41 vs. 3.73, F=108.43, p<.0001 –, therefore supporting the classification of the ads. 23 The corresponding tables of means and ANOVA summary tables are presented in Appendix 8. 24 The corresponding tables of means and ANOVA summary tables are presented in Appendix 9.

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In order to check whether significant differences are found between the blind-tests and the brand-tests with respect to respondents rating the ads in terms of provocation, six ANOVAs are performed :

- the first, second, and third ANOVAs have respectively the provocation scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 3 as the dependent variable and the sample, gender, and product involvement as independent variables ;

- the fourth, fifth, and sixth ANOVAs have respectively the provocation scores related to the Benetton, Diesel, and Sisley ads collected from Sample 2 and Sample 4 as the dependent variable and the sample, gender, and product involvement as independent variables.

The results25 show that, for the provocative ads (Sample 1 and Sample 3), the difference between the means of the provocation scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 3 is not statistically significant at a .05 level – Benetton : p=0.9861 ; Diesel : p=0.8866 ; Sisley : p=0.1712. Similar results26 are found for the more traditional ads (Sample 2 and Sample 4) – Benetton : p=0.9646 ; Diesel : p=0.8837 ; Sisley : p=0.1462. No significant differences are therefore found between the blind-tests and the brand-tests with respect to respondents rating the ads in terms of provocation, meaning that blind-tests do not change the perceived provocation of the ads considered.

3.1.2. Hypotheses In order to test for the hypotheses, and for possible interactions with the gender and the product involvement of respondents (presented in sections 3.1.4 and 3.1.5), six ANOVAs are performed for each hypothesis :

- the first, second, and third ANOVAs have respectively the Aad (in the case of H.1), Abr (in the case of H.2), and PI (in the case of H.3) scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 2 as the dependent variable and the sample, gender, and product involvement as independent variables ;

- the fourth, fifth, and sixth ANOVAs have respectively the Aad (in the case of H.1), Abr (in the case of H.2), and PI (in the case of H.3) scores related to the Benetton, Diesel, and Sisley ads collected from Sample 3 and Sample 4 as the dependent variable and the sample, gender, and product involvement as independent variables.

3.1.2.1. First hypothesis

The first part of H.1 argues that respondents’ reported attitude toward an advertisement (Aad) using a provocative content will be significantly less favorable than the attitude toward a different advertisement for the same brand using a more traditional content, as well in the brand-tests as in the blind-tests. The results27 show that, in the brand-tests (Sample 1 and Sample 2), the difference between the means of the Aad scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 2 is statistically significant – Benetton : 3.18 vs. 4.37, F=65.62, p<.0001 ; Diesel : 3.75 vs. 4.03, F=4.16, p<.05 ; Sisley : 3.20 vs. 4.10, F=43.86, p<.0001 –, with the provocative ads (in Sample 1) being, on average, associated with lower Aad scores 25 The corresponding tables of means and ANOVA summary tables are presented in Appendix 10. 26 The corresponding tables of means and ANOVA summary tables are presented in Appendix 11. 27 The corresponding tables of means and ANOVA summary tables are presented in Appendix 12.

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than the more traditional ads (in Sample 2). Similar results28 are found in the blind-tests (Sample 3 and Sample 4) – Benetton : 2.76 vs. 3.78, F=77.22, p<.0001 ; Diesel : 3.45 vs. 3.85, F=10.20, p<.002 ; Sisley : 3.02 vs. 3.85, F=46.84, p<.0001 –, therefore supporting the veracity of the first part of H.1 for the ads and brands considered. The second part of H.1 argues that respondents’ reported reaction toward an advertisement using a provocative content will be significantly less favorable than the reaction toward a different advertisement for the same brand using a more traditional content, as well in the brand-tests as in the blind-tests. The analysis of the responses obtained from the adjective checklist indicates the following results29. In the brand-tests (Sample 1 and Sample 2), the most frequently selected adjectives for the provocative Benetton ad (in Sample 1) are rather extreme and negative : “violent” (20.80%), “shocking” (20.80%), and “sad” (15.20%). The more traditional Benetton ad (in Sample 2) raises some controversy, but at a seemingly lower level than the provocative one : “peaceful” (21.70%) and “original” (20.80%) are the first two adjectives mentioned but are followed by a more negative adjective, “shocking” (10.10%). The Diesel ads show a mix of positive and negative adjectives, as well for the provocative ad (in Sample 1) – “original” (22.40%), “violent” (18%), and “young” (13.20%) – as for the more traditional ad (in Sample 2) – “young” (22.50%), “original” (19.50%), and “ugly” (12.60%) –, but one can argue that the adjective “violent” describes a less favorable reaction toward the provocative Diesel ad than the adjective “ugly” toward the more traditional Diesel ad. Similarly to Benetton, the most frequently selected adjectives for the provocative Sisley ad (in Sample 1) are rather extreme and negative : “indecent” (21.30%), “ugly” (15.20%), and “shocking” (14.30%). In contrast, the adjectives selected to describe the more traditional Sisley ad (in Sample 2) do not carry any negative connotation : “trite” (15.60%), “young” (15.30%), and “original” (13%). As the most frequently selected adjectives for the Benetton, Diesel, and Sisley ads in the blind-tests (Sample 3 and Sample 4) are similar to those in the brand-tests presented above, the veracity of the second part of H.1 is therefore also supported for the ads and brands considered. Aside from the specific adjectives selected, an analysis of the number of adjectives selected per respondent indicates that the provocative ads attract, on average, a wider range of adjectives than the more traditional ads, as well in the brand-tests as in the blind-tests, except for Diesel. For instance, in the brand-tests (Sample 1 and Sample 2), 3 adjectives per respondent are, on average, selected for the provocative Benetton ad (in Sample 1), while only 2.4 adjectives per respondent are selected for the more traditional Benetton ad (in Sample 2). “This factor can be interpreted in keeping with the previous discussion about the high degree of ambiguity in provocative ads, since more adjectives may indicate a wider range of interpretations.” (Vézina and Paul, 1997, p.186) Again, the numbers of adjectives selected per respondent for the Benetton, Diesel, and Sisley ads in the blind-tests (Sample 3 and Sample 4) are similar to those in the brand-tests.

3.1.2.2. Second hypothesis H.2 argues that respondents’ reported attitude toward a brand (Abr) associated with a provocative advertisement will be significantly less favorable than the attitude toward the

28 The corresponding tables of means and ANOVA summary tables are presented in Appendix 13. 29 The responses obtained from the adjective checklist are presented in Appendix 14.

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same brand associated with a more traditional advertisement, as well in the brand-tests as in the blind-tests. The results30 show that, in the brand-tests (Sample 1 and Sample 2), the difference between the means of the Abr scores related to the Benetton and Sisley ads collected from Sample 1 and Sample 2 is statistically significant – Benetton : 3.70 vs. 4.38, F=15.49, p<.0002 ; Sisley : 3.43 vs. 4.25, F=25.57, p<.0001 –, with the provocative ads (in Sample 1) being, on average, associated with lower Abr scores than the more traditional ads (in Sample 2). However, the difference between the means of the Abr scores related to the Diesel ads collected from Sample 1 and Sample 2 is not statistically significant at a .05 level (p=0.3392). In the blind-tests (Sample 3 and Sample 4), the results31 found that the difference between the means of the Abr scores related to the Benetton, Diesel, and Sisley ads collected from Sample 3 and Sample 4 is statistically significant – Benetton : 2.32 vs. 3.30, F=59.40, p<.0001 ; Diesel : 3.21 vs. 3.78, F=16.49, p<.0001 ; Sisley : 2.70 vs. 3.89, F=69.22, p<.0001 –, with the provocative ads (in Sample 3) being, on average, associated with lower Abr scores than the more traditional ads (in Sample 4). The veracity of H.2 is therefore supported for the ads and brands considered, except for Diesel in the brand-tests.

3.1.2.3. Third hypothesis H.3 argues that respondents’ reported level of purchase intentions (PI) associated with an advertisement using a provocative content will be significantly less favorable than the level of purchase intentions associated with a different advertisement for the same brand using a more traditional content, as well in the brand-tests as in the blind-tests. The results32 show that, in the brand-tests (Sample 1 and Sample 2), the difference between the means of the PI scores related to the Benetton ads collected from Sample 1 and Sample 2 is statistically significant (3.15 vs. 3.52, F=4.97, p<.03), with the provocative ad (in Sample 1) being, on average, associated with a lower PI score than the more traditional ad (in Sample 2). However, the difference between the means of the PI scores related to the Diesel and Sisley ads collected from Sample 1 and Sample 2 is not statistically significant at a .05 level – Diesel : p=0.2331 ; Sisley : p=0.4296. In the blind-tests (Sample 3 and Sample 4), the results33 found that the difference between the means of the PI scores related to the Benetton, Diesel, and Sisley ads collected from Sample 3 and Sample 4 is not statistically significant at a .05 level – Benetton : p=0.0612 ; Diesel : p=0.6848 ; Sisley : p=0.2223. The veracity of H.3 is therefore only supported for Benetton in the brand-tests.

3.1.3. Research questions In order to test for the research questions, and for possible interactions with the gender and the product involvement of respondents (presented in sections 3.1.4 and 3.1.5), six ANOVAs are performed for each research question :

- the first, second, and third ANOVAs have respectively the Aad (in the case of R.Q.1), Abr (in the case of R.Q.2), and PI (in the case of R.Q.3) scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 3 as the dependent variable and the sample, gender, and product involvement as independent variables ;

30 The corresponding tables of means and ANOVA summary tables are presented in Appendix 15. 31 The corresponding tables of means and ANOVA summary tables are presented in Appendix 16. 32 The corresponding tables of means and ANOVA summary tables are presented in Appendix 17. 33 The corresponding tables of means and ANOVA summary tables are presented in Appendix 18.

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- the fourth, fifth, and sixth ANOVAs have respectively the Aad (in the case of R.Q.1), Abr (in the case of R.Q.2), and PI (in the case of R.Q.3) scores related to the Benetton, Diesel, and Sisley ads collected from Sample 2 and Sample 4 as the dependent variable and the sample, gender, and product involvement as independent variables.

3.1.3.1. First research question

R.Q.1 asks whether respondents’ reported attitude toward an advertisement (Aad) using a provocative or a more traditional content will be significantly less favorable in the blind-tests than in the brand-tests. The results34 show that, for the provocative ads (Sample 1 and Sample 3), the difference between the means of the Aad scores related to the Benetton and Diesel ads collected from Sample 1 and Sample 3 is statistically significant – Benetton : 3.18 vs. 2.76, F=11.89, p<.0007 ; Diesel : 3.75 vs. 3.45, F=6.82, p<.01 –, with the ads being, on average, associated with higher Aad scores in the brand-test (Sample 1) than in the blind-test (Sample 3). However, the difference between the means of the Aad scores related to the Sisley ads collected from Sample 1 and Sample 3 is not statistically significant at a .05 level (p=0.1819). For the more traditional ads (Sample 2 and Sample 4), the results35 found that the difference between the means of the Aad scores related to the Benetton ads collected from Sample 2 and Sample 4 is statistically significant (4.37 vs. 3.78, F=18.09, p<.0001), with the ad being, on average, associated with a higher Aad score in the brand-test (Sample 2) than in the blind-test (Sample 4). However, the difference between the means of the Aad scores related to the Diesel and Sisley ads collected from Sample 2 and Sample 4 is not statistically significant at a .05 level – Diesel : p=0.2034 ; Sisley : p=0.0578. Respondents’ reported attitude (Aad) toward an advertisement using a provocative content is therefore significantly less favorable in the blind-tests than in the brand-tests only for Benetton and Diesel whereas respondents’ reported attitude (Aad) toward an advertisement using a more traditional content is significantly less favorable in the blind-tests than in the brand-tests only for Benetton.

3.1.3.2. Second research question R.Q.2 asks whether respondents’ reported attitude toward a brand (Abr) associated with a provocative advertisement or a more traditional advertisement will be significantly less favorable in the blind-tests than in the brand-tests. The results36 show that, for the provocative ads (Sample 1 and Sample 3), the difference between the means of the Abr scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 3 is statistically significant – Benetton : 3.70 vs. 2.32, F=89.12, p<.0001 ; Diesel : 4.23 vs. 3.21, F=48.96, p<.0001 ; Sisley : 3.43 vs. 2.70, F=21.75, p<.0001 –, with the ads being, on average, associated with higher Abr scores in the brand-test (Sample 1) than in the blind-test (Sample 3). Similar results37 are found for the more traditional ads (Sample 2 and Sample 4) – Benetton : 4.38 vs. 3.30, F=50.55, p<.0001 ; Diesel : 4.40 vs. 3.78, F=14.37, p<.0003 ; Sisley : 4.25 vs. 3.89, F=5.85, p<.02. Respondents’ reported attitude toward a brand (Abr) associated with a provocative advertisement or a more traditional

34 The corresponding tables of means and ANOVA summary tables are presented in Appendix 19. 35 The corresponding tables of means and ANOVA summary tables are presented in Appendix 20. 36 The corresponding tables of means and ANOVA summary tables are presented in Appendix 21. 37 The corresponding tables of means and ANOVA summary tables are presented in Appendix 22.

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advertisement is therefore significantly less favorable in the blind-tests than in the brand-tests for the ads and brands considered.

3.1.3.3. Third research question R.Q.3 asks whether respondents’ reported level of purchase intentions (PI) associated with an advertisement using a provocative content or a more traditional content will be significantly less favorable in the blind-tests than in the brand-tests. The results38 show that, for the provocative ads (Sample 1 and Sample 3), the difference between the means of the PI scores related to the Benetton, Diesel, and Sisley ads collected from Sample 1 and Sample 3 is statistically significant – Benetton : 3.15 vs. 2.14, F=52.50, p<.0001 ; Diesel : 3.66 vs. 2.77, F=35.35, p<.0001 ; Sisley : 2.78 vs. 2.42, F=6.02, p<.02 –, with the ads being, on average, associated with higher PI scores in the brand-test (Sample 1) than in the blind-test (Sample 3). Similar results39 are found for the more traditional ads (Sample 2 and Sample 4) – Benetton : 3.52 vs. 2.37, F=61.26, p<.0001 ; Diesel : 3.45 vs. 2.82, F=16.99, p<.0001 ; Sisley : 2.91 vs. 2.59, F=4.24, p<.05. Respondents’ reported level of purchase intentions (PI) associated with an advertisement using a provocative content or a more traditional content is therefore significantly less favorable in the blind-tests than in the brand-tests for the ads and brands considered.

3.1.4. Gender The results found several statistically significant interactions between the gender of respondents and H.1. There exists a statistically significant interaction effect between sample (1 and 2) and gender for the Aad scores related to the Diesel (F=5.10, p<.03) and Sisley (F=5.18, p<.03) ads, and between sample (3 and 4) and gender for the Aad scores related to the Benetton (F=6.98, p<.009), Diesel40 (F=9.24, p<.003), and Sisley (F=5.74, p<.02) ads, meaning that the sample effects depend on gender (see Figure 3 and Figure 4). However, the main effect of gender for the Aad scores collected from Samples 1 and 2 is not significant at a .05 level neither for Diesel (p=0.9324) nor for Sisley (p=0.0508), and the main effect of gender for the Aad scores collected from Samples 3 and 4 is significant for Sisley (F=22.74, p<.0001) but not for Benetton (p=0.5895) and Diesel (p=0.3651) at a .05 level. Concerning the interaction for Diesel in Samples 1 and 2 and for Diesel in Samples 3 and 4, even if the main effect of sample says that the means of the Aad scores are lower in Sample 1 than in Sample 2 and in Sample 3 than in Sample 4, the interaction says that this only holds true for women ; men indeed show higher Aad scores in Sample 1 and lower in Sample 2 and higher Aad scores in Sample 3 and lower in Sample 4. Thus, the interaction is what is important here. Concerning the interaction for Sisley in Samples 1 and 2 and for Benetton in Samples 3 and 4, even though the interaction (which says that the effect of sample is greater among women) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of gender (both men and women show, for Sisley, lower Aad scores in Sample 1 than in Sample 2 and, for Benetton, lower Aad scores in Sample 3 than in Sample 4). Concerning the interaction for Sisley in Samples 3 and 4, even if both men and women

38 The corresponding tables of means and ANOVA summary tables are presented in Appendix 23. 39 The corresponding tables of means and ANOVA summary tables are presented in Appendix 24. 40 A sample (3 and 4) x gender x product involvement interaction is also significant for the Aad scores related to the Diesel ads (F=4.31, p<.04). The gender x product involvement interaction is larger for Sample 4 than for Sample 3. For Sample 4, the difference between men and women is much smaller for highly involved respondents than for lowly involved respondents.

20

show lower Aad scores in Sample 3 than in Sample 4 (in line with the main effect of sample), men show higher Aad scores in both Sample 3 and Sample 4 than women. In this case, even though the interaction (which says that the effect of sample is greater among women) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of gender.

Figure 3 : Graph of means - Aad Diesel and Sisley - Samples 1 and 2

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The results also found several statistically significant interactions between the gender of respondents and H.2 and R.Q.2. There exists a statistically significant interaction effect between sample (3 and 4) and gender for the Abr scores related to the Diesel ads (F=9.66, p<.003), between sample (1 and 3) and gender for the Abr scores related to the Benetton (F=6.95, p<.009) and Sisley (F=5.96, p<.02) ads, and between sample (2 and 4) and gender for the Abr scores related to the Sisley ads (F=9.59, p<.003), meaning

that the sample effects depend on gender (see Figure 5, Figure 6, and Figure 7). However, the main effect of gender for the Abr scores collected from Samples 3 and 4 is not significant for Diesel at a .05 level (p=0.6665), the main effect of gender for the Abr scores collected from Samples 1 and 3 is significant for Sisley (F=8.69, p<.004) but not for Benetton at a .05 level (p=0.8878), and the main effect of gender for the Abr scores collected from Samples 2 and 4

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is not significant for Sisley at a .05 level (p=0.3371). Concerning the interaction for Diesel in Samples 3 and 4 and for Benetton in Samples 1 and 3, even though the interaction (which says that the effect of sample is greater among women) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of gender (both men and women show, for Diesel, lower Abr scores in Sample 3 than in Sample 4 and, for Benetton, higher Abr scores in Sample 1 than in Sample 3). Concerning the interaction for

Sisley in Samples 1 and 3, even if both men and women show higher Abr scores in Sample 1 than in Sample 3 (in line with the main effect of sample), men show higher Abr scores in both Sample 1 and Sample 3 than women. In this case, even though the interaction (which says that the effect of sample is greater among women) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of gender. Concerning the interaction for Sisley in Samples 2 and 4, even if the main effect of sample says that

the means of the Abr scores are higher in Sample 2 than in Sample 4, the interaction says that this only holds true for women ; men indeed show lower Abr scores in Sample 2 and higher in Sample 4. Thus, the interaction is what is important here.

Figure 5 : Graph of means - Abr Diesel - Samples 3 and 4

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3.1.5. Product involvement

The results found several statistically significant interactions between the product involvement of respondents and H.1 and R.Q.1. There exists a statistically significant interaction effect between sample (1 and 2) and product involvement for the Aad scores

Figure 7 : Graph of means - Abr Sisley - Samples 2 and 4

Figure 6 : Graph of means - Abr Benetton and Sisley - Samples 1 and 3

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related to the Diesel ads (F=6.83, p<.01), between sample (3 and 4) and product involvement for the Aad scores related to the Benetton (F=6.16, p<.02) and Sisley (F=4.32, p<.04) ads, and between sample (1 and 3) and product involvement for the Aad scores related to the Benetton ads (F=5.05, p<.03), meaning that sample effects depend on product involvement (see Figure 8, Figure 9, and Figure 10). However, the main effect of product involvement for the Aad scores collected from Samples 1 and 2 is significant for Diesel (F=7.15, p<.008), the main effect of product involvement for the Aad scores

collected from Samples 3 and 4 is significant for Sisley (F=5.68, p<.02) but not for Benetton at a .05 level (p=0.8881), and the main effect of product involvement for the Aad scores collected from Samples 1 and 3 is not significant for Benetton at a .05 level (p=0.5220). Concerning the interaction for Diesel in Samples 1 and 2, even if the main effect of sample says that the means of the Aad scores are lower in Sample 1 than in Sample 2, the interaction says that this only holds true for highly involved respondents ; lowly involved respondents indeed show higher Aad scores in Sample 1 and lower in Sample 2 (but lower than highly involved respondents for both Sample 1 and Sample 2). Thus, the interaction is what is

important here. Concerning the interaction for Benetton in Samples 3 and 4 and for Benetton in Samples 1 and 3, even though the interaction (which says that the effect of sample is greater among highly involved respondents) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of product involvement (both highly and lowly involved respondents show, for Benetton, lower Aad scores in Sample 3 than in Sample 4 and higher Aad scores in Sample 1 than in Sample 3). Concerning the interaction for

Figure 8 : Graph of means - Aad Diesel - Samples 1 and 2

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Figure 9 : Graph of means - Aad Benetton and Sisley - Samples 3 and 4

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Sisley in Samples 3 and 4, even if both highly and lowly involved respondents show lower Aad scores in Sample 3 than in Sample 4 (in line with the main effect of sample), highly involved respondents show higher Aad scores in both Sample 3 and Sample 4 than lowly involved respondents. In this case, even though the interaction (which says that the effect of sample is greater among highly involved respondents) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of product involvement. The results also found a statistically significant interaction between the product involvement of respondents and H.2. There exists a statistically significant interaction effect between sample (3 and 4) and product involvement for the Abr scores related to the Benetton (F=4.46, p<.04) and Sisley (F=4.89, p<.03) ads, meaning that sample effects depend on product involvement (see Figure 11). However, the main effect of product involvement for the Abr scores collected from Samples 3 and 4 is significant for Sisley (F=3.94, p<.05) but not for Benetton at a .05 level (p=0.9244). Concerning the interaction for Benetton in Samples 3 and 4, even though the interaction (which says that the effect of sample is greater among highly involved respondents) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of product involvement (both highly and lowly involved respondents show, for Benetton, lower Abr scores in Sample 3 than in Sample 4). Concerning the interaction for Sisley in Samples 3 and 4, even if both highly and lowly involved respondents show lower Abr scores in Sample 3 than in Sample 4 (in line with the main effect of sample), lowly involved respondents show higher Abr scores in Sample 3 and lower in Sample 4 than highly involved respondents. In this case, even though the interaction (which says that the effect of sample is greater among highly involved respondents) is significant, the main effect of sample is also worth paying attention to because it holds true at all levels of product involvement. Figure 11 : Graph of means - Abr Benetton and Sisley - Samples 3 and 4

3.2. Discussion of results

The first step of the analysis was to determine whether the impact of the shift from provocative to more traditional advertising strategies recently operated by many brands on Aad, Abr, and PI was significant for each of the three brands considered. The results of section 3.1.2 show that the shift from provocative to more traditional advertising strategies has an impact on the Aad scores related to the Benetton, Diesel, and Sisley ads, on the Abr scores related to the Benetton, Diesel (only in the blind-tests), and Sisley ads, and on the PI scores related to the Benetton ads (only in the brand-tests), with the provocative ads, for these brands, being associated with lower mean scores, for these variables, than the more traditional ads – the results found no impact of the shift from provocative to more traditional advertising

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strategies on the Abr scores related to the Diesel ads in the brand-tests, on the PI scores related to the Benetton ads in the blind-tests, on the PI scores related to the Diesel ads, and on the PI scores related to the Sisley ads. However, interactions between these results and the gender and product involvement of respondents show that the provocative Diesel ad is associated with lower Aad scores than the more traditional ad only for women and highly involved respondents in the brand-tests and only for women in the blind-tests, that the provocative Sisley ad is associated with lowly involved respondents showing higher Abr scores than highly involved respondents, that the more traditional Sisley ad is associated with lowly involved respondents showing lower Abr scores than highly involved respondents, and that both the provocative and the more traditional Sisley ads are associated with men and highly involved respondents showing higher Aad scores than women and lowly involved respondents. Moreover, in the brand-tests, the impact of the shift from provocative to more traditional advertising strategies is greater among women when it is on the Aad for Sisley. In the blind-tests, the impact of the shift from provocative to more traditional advertising strategies is greater among women when it is on the Aad for Benetton, on the Aad for Sisley, and on the Abr for Diesel, and greater among highly involved respondents when it is on the Aad for Benetton, on the Aad for Sisley, on the Abr for Benetton, and on the Abr for Sisley. The second step of the analysis was to control for the change in the picture/content of the advertisements to determine whether the influence of the product brand on Aad, Abr, and PI was significant for each of the six ads considered. The results of section 3.1.3 show that the Aad scores related to the Benetton and the provocative Diesel ads, the Abr scores related to the Benetton, Diesel, and Sisley ads, and the PI scores related to the Benetton, Diesel, and Sisley ads are based on an evaluation of the entire advertisements and are hence influenced by brand names, with the ads in the blind-tests, for theses brands, being associated with lower mean scores, for these variables, than the ads in the brand-tests – the results found no influence of the product brand on the Aad scores related to the more traditional Diesel ad and on the Aad scores related to the Sisley ads. However, interactions between these results and the gender and product involvement of respondents show that the provocative Sisley ad is associated with men showing higher Abr scores both in the brand- and blind-tests than women, and that the more traditional Sisley ad is associated with higher Abr scores in the brand-test than in the blind-test only for women. Moreover, the influence of the product brand is greater among women when it is on the Abr for the provocative Benetton ad and on the Abr for the provocative Sisley ad, and greater among highly involved respondents when it is on the Aad for the provocative Benetton ad. So far, the results of these two first steps allow to confirm the findings of authors such as De Pelsmacker and Van Den Bergh (1996), Henthorne and LaTour (1994), LaTour, Pitts, and Snook-Luther (1990), Reichert et al. (1999), Sanbonmatsu and Kardes (1988), and Smith et al. (1995) – who find that sexual and/or other provocative stimuli result in a significantly less favorable Aad than ads that contain little or no such appeals –, those of authors such as Bello et al. (1983) and De Pelsmacker and Van Den Bergh (1996) – according to which PI are generally not influenced by a brand’s advertising strategy but rather by brand loyalty, brand recognition, and product (dis-)satisfaction –, and to generalize the findings of authors such as Henthorne and LaTour (1994), Lundstrom and Sciglimpaglia (1977), and Reichert et al. (1999) – who find that an ad that contains a strong overt sexual appeal results in a significantly less favorable Abr than an ad that contains little or no sexual appeal – to other provocative stimuli.

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The third step of the analysis was to determine whether the impact of the shift from provocative to more traditional advertising strategies on Aad, Abr, and PI was influenced solely by the effect of the change in the picture/content of the advertisements or also by the effect of the consumers’ perceptions of the product brands. Considering only the cases where the impact of the shift from provocative to more traditional advertising strategies on Aad, Abr, or PI is significant both in the brand- and blind-tests41, the results show that the impact of the shift from provocative to more traditional advertising strategies on the Aad scores related to the Benetton and Diesel ads and on the Abr scores related to the Benetton and Sisley ads is not influenced solely by the change in the picture/content of the advertisements but also by the consumers’ perceptions of the product brands. However, such a finding for the Aad scores related to the Diesel ads is only due to the impact of the product brand on the Aad scores related to the provocative Diesel ad (because no impact of the product brand is found on the Aad scores related to the more traditional Diesel ad) and the results do not allow to conclude that the impact of the shift from provocative to more traditional advertising strategies on the Aad scores related to the Sisley ads is not influenced solely by the change in the picture/content of the advertisements but also by the consumers’ perceptions of the product brands. Figure 12 illustrates these findings.

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In other words, although the provocative Benetton and Diesel ads result in lower Aad scores than the more traditional ones and the provocative Benetton and Sisley ads result in lower Abr scores than the more traditional ones both in the brand- (Samples 1 and 2) and blind-tests (Samples 3 and 4), the impact of the shift from provocative to more traditional advertising strategies on the Aad scores related to the Benetton and Diesel ads and on the Abr scores related to the Benetton and Sisley ads in the brand-tests is different from the impact of the shift from provocative to more traditional advertising strategies on the Aad scores related to the Benetton and Diesel ads and on the Abr scores related to the Benetton and Sisley ads in the blind-tests, meaning that the impact of this shift on the Aad scores related to the Benetton and Diesel ads and on the Abr scores related to the Benetton and Sisley ads is not influenced solely by the change in the picture/content of the advertisements but also by the consumers’ perceptions of the product brands (such a finding for the Abr scores related to the Benetton 41 Because the impact of the shift from provocative to more traditional advertising strategies on the Abr scores related to the Diesel ads and on the PI scores related to the Benetton, Diesel, and Sisley ads was not significant in the brand-tests and/or in the blind-tests, it was not possible to test whether the impact of the shift from provocative to more traditional advertising strategies on these variables and for these ads and brands was influenced solely by the effect of the change in the picture/content of the advertisements or also by the effect of the consumers’ perceptions of the product brands.

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and Sisley ads could actually be expected from a measure of the attitude toward the brand). Moreover, the impact of the Benetton and Diesel brands on the Aad scores is positive, both for the provocative and the more traditional Benetton ads but only for the provocative Diesel ad – the Aad scores related to the provocative Benetton and Diesel ads in the brand-test (Sample 1) are higher than the Aad scores related to the provocative Benetton and Diesel ads in the blind-test (Sample 3) and the Aad scores related to the more traditional Benetton ad in the brand-test (Sample 2) are higher than the Aad scores related to the more traditional Benetton ad in the blind-test (Sample 4). In addition, the Abr scores related to the Benetton and Sisley ads are higher when the ads include the true brand names than when the Benetton and Sisley brand names are renamed respectively “I” and “L”, both for the provocative and the more traditional Benetton and Sisley ads – the Abr scores related to the provocative Benetton and Sisley ads in the brand-test (Sample 1) are higher than the Abr scores related to the provocative Benetton and Sisley ads in the blind-test (Sample 3) and the Abr scores related to the more traditional Benetton and Sisley ads in the brand-test (Sample 2) are higher than the Abr scores related to the more traditional Benetton and Sisley ads in the blind-test (Sample 4). The findings of the third step of the analysis for the Aad scores related to the Benetton and Diesel ads suggest that the attitude toward the ad is not only based on the effects of the pictures used in the ads but also on a general evaluation of the entire advertisements (including the brand names), as Mitchell (1986) suspected. The attitude toward the ad would therefore not only be a measure of the subjects’ evaluation of the pictures used in the advertisements but also a predictor of brand attitudes. Similarly, the findings of the third step of the analysis for the Abr scores related to the Benetton and Sisley ads suggest that the attitude toward the brand is not only based on a general evaluation of the brand names included in the advertisements but also on the effects of the pictures used in the ads. The attitude toward the brand would therefore not only be a measure of the subjects’ evaluation of the brands associated with the advertisements but also a predictor of ad attitudes. The Pearson correlation coefficients42 between the Aad and Abr scores related to the same Benetton, Diesel, and Sisley ad have been computed in each sample and all appear positive, statistically significant (p<.0001), and between 0.45 and 0.84, indicating a moderate to high degree of correlation between the Aad and Abr scores related to the same Benetton, Diesel, and Sisley ad. According to Franzblau (1958), “the relationship between the size of a correlation coefficient and its predictive value is not a directly proportional one. […] Coefficients below .40 do not yield a guess even 10% better than chance. To yield a prediction which is 25% better than a chance or random guess, the correlation must be at least .66 ; to be 50% better than chance, a correlation of at least .86 is needed ; to be 75% better than chance, the coefficient must rise as high as .97.” (p.88) The Aad scores related to a particular Benetton, Diesel, or Sisley ad would therefore predict the Abr scores related to the same ad, and conversely, with a 10 to 50% better than a chance or random guess.

42 The Pearson correlation coefficients are presented in Appendix 25, Appendix 26, Appendix 27, and Appendix 28. The results also show that the correlations between the Aad and PI scores and between the Abr and PI scores related to the same Benetton, Diesel, and Sisley ad collected from each sample are all positive, statistically significant (p<.0001), and between 0.43 and 0.70, indicating a moderate to marked degree of correlation between the Aad and PI scores and between the Abr and PI scores related to the same Benetton, Diesel, and Sisley ad. On the other hand, the correlations between product involvement and the Aad, Abr, and PI scores related to the Benetton, Diesel, and Sisley ads collected from each sample are not always statistically significant at a .05 level (but the significant correlations – p<.05 – are all positive) and are all lower than 0.42, indicating a low degree of correlation between these variables.

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In addition, the findings of the third step of the analysis for the Aad scores related to the Benetton ads and the Abr scores related to the Benetton and Sisley ads suggest that the better solution for these brands, which used to play with provocative advertising strategies, to improve their Aad/Abr scores was to switch to more traditional advertising strategies, such as those adopted recently by these brands, under the same brand names whereas the findings of the third step of the analysis for the Aad scores related to the Diesel ads suggest that the better solution for this brand, which also used to play with provocative advertising strategies, to improve its Aad scores was either to switch to more traditional advertising strategies, such as those adopted recently by the brand, under the same brand name or to launch these more traditional advertising campaigns under a new brand name (if we only consider the impact on the Aad scores, and not other strategic considerations a new brand name might imply). Actually, except for this latter case, the creation of a new brand name would have reduced the Aad/Abr scores in comparison with those related to a more traditional advertising strategy under the same brand name. The impact of the brand names on the Aad/Abr scores is indeed positive and confirms the view according to which “The values that are spread [by the ad and/or brand] and how they in turn effect the consumer are important for the future of the product (Hägg et al., 1972 [in Andersson, Hedelin, Nilsson, and Welander, 2004, p.103]).” At the same time, the positive impact of the brand names on the Aad/Abr scores related to more traditional advertising strategies (captured by higher Aad/Abr scores in Sample 2 than in Sample 4) is counterintuitive if we consider the fact that these brand names may remind consumers of the provocative images of previous advertising campaigns associated, if we refer to the results of this research, with lower Aad/Abr scores. One plausible explanation for this positive impact of the brand names on the Aad/Abr scores related to more traditional advertising strategies would therefore be that it does not only embed a negative effect associated with previous provocative advertising campaigns but also a positive effect associated with brand awareness, brand associations, brand knowledge/image, personal experiences/satisfactions the consumer had with the brand, the perceived quality associated

th g of the brand, the perceptions of the brand held in the nd assets that outweighs the negative effect of previous

with e brand, brand loyalty, learninmind of the consumer, and other braprovocative advertising campaigns.

4. Conclusions 

4.1. Important facts Three main conclusions appear from the results of this research. Firstly, the shift from provocative to more traditional advertising strategies has an impact on the Aad and Abr scores related to the Benetton, Diesel, and Sisley ads and on the PI scores related to the Benetton ads ; the provocative ads, for these brands, show lower mean scores, for these variables, than the more traditional ads. Secondly, the Aad scores related to the Benetton ads and the provocative Diesel ad and the Abr and PI scores related to the Benetton, Diesel, and Sisley ads are based on an evaluation of the entire advertisements and are influenced in a positive way by brand names. Consequently, whereas provocative ads result in significantly less favorable Aad and Abr scores than ads that contain little or no provocative appeals, PI are generally not influenced by a brand’s advertising strategy but rather probably by brand loyalty, brand recognition, and product (dis-)satisfaction. Thirdly, the impact of the shift from provocative to more traditional advertising strategies on the Aad scores related to the Benetton and Diesel

28

ads and on the Abr scores related to the Benetton and Sisley ads is not influenced solely by the change in the picture/content of the advertisements but also by the consumers’ perceptions of the product brands ; the impact of the Benetton and Diesel brands on the Aad scores is positive and the Abr scores related to the Benetton and Sisley ads are higher when the ads include the true brand names. These findings imply that brands which used to rely for several years on provocation can change consumer perceptions more efficiently in terms of Aad and Abr scores by shifting to more traditional advertising strategies under the same brand names than under new ones because the negative impact of the previous provocative campaigns on the Aad/Abr scores related to the more traditional advertising strategies seems to be outweighed by a more positive impact associated with the brands’ efforts to leverage brand equity.

4.2. Limitations and recommendations for future research A first limitation of this research is related to a time consistency problem. One would ask whether the more traditional ads that we see today are the consequence of a change in morals and ethics of society over time and/or of a change initiated by advertisers themselves. The fact is that, today, traditional values seem to be shared by both consumers and advertising, and this is maybe the explanation for positive Aad, Abr, and PI found toward such traditional ads. If the same experiment would have been performed a few years ago, when provocation was the “norm” in advertising, more favorable Aad, Abr, and PI would maybe have been found toward such provocative ads. Besides a time consistency problem, a space consistency problem also emerges. Previous studies indeed report geographical differences in the reaction of taboos themes in advertising (Manceau and Tissier-Desbordes, 1998). The importance of culture in the representation of sex in advertising and in the perceptions of the degree of transgression has been underlined by several researchers (e.g., Piron and Young, 1996). Moreover, with the exception of the Belgian study of De Pelsmacker and Van Den Bergh (1996), the results of previous studies we have referred to are mainly based on American respondents. However, it seems that nudity and sexual content is less depicted in US than in European advertising (Hoyer and MacInnis, 1997 ; Reid et al., 1984), that American women often assimilate nudity with pornography, which is far from being true in Europe (Stern, 1991), and that many ads considered indecent in the USA are not controversial in Europe (Herbig, 1998). In addition, US consumers would exhibit lower fashion involvement than, for example, Dutch consumers (Tigert, King, and Ring, 1980). Because “There is also evidence that responses to erotic communications are individualistic in nature rather than being uniform across audiences” (Morrison and Sherman, 1972 [in LaTour, Pitts, and Snook-Luther, 1990, p.52]), several authors (e.g., Kates and Shaw-Garlock, 1999 ; Usunier, 1996) recommend to look not only at comparisons between cultures but also at comparisons within cultures. Several socio-demographic variables such as age, social class, education, religion, family, marital status, nationality, ethnicity, race, income level, monthly expenditure, current occupation etc. indeed often influence advertising impact (LaTour et al., 1990), play an important role in regards to PI (Grazer, 1981), and could therefore account for differences in the reactions to provocative ads. For example, even if some contradictions appear between authors, it has been showed that younger people easily accept provocative advertisements than older people (Alwitt and Prabaker, 1994 ; De Pelsmaker and Van Den Bergh, 1996 ; LaTour and Henthorne, 1995 ; Manceau and Tissier-Desbordes, 1999) and are hence more likely to have favorable reactions toward the ad as well as the product (Severn,

29

Belch, and Belch, 1990 ; Vézina and Paul, 1997). The uniformity of age within the samples, however, does not allow to test the influence of age, among other variables, and forbids any conclusion on this matter. People also differ in their reactions to sex and provocation in advertising because of personality traits, attitudes, and values. Preliminary research indeed shows that several variables such as Erotophobia/Erotophilia – a person’s predisposition to respond to sexual stimuli – (e.g., Helweg-Larsen and Howell, 2000), consumers’ sexual liberalism (Mittal and Lassar, 2000), sexual preference, consumers’ ethical values (e.g., LaTour and Henthorne, 1994), consumer dogmatism, need for cognition, and levels of fantasy/imagination (Vézina and Paul, 1997), introversion/extroversion (Eynsenck, 1967), self-esteem (Schaninger and Sciglimpaglia, 1981) etc. may explain the differences in attitudes and therefore appear to be relevant factors for further analyses of consumer responses to provocative vs. more traditional advertising strategies. As the advertisements considered in this research are all ads for products in the clothing and fashion sector, two additional limitations emerge. Firstly, we could expect differences between an advertisement for a cause (social marketing) and an advertisement for a consumer product regarding consumers’ Aad and Abr (or corporate image in the case of social marketing), regardless of whether the ads are provocative or not. Nevertheless, Pope, Voges, and Brown (2004) show that “the use of provocation in the form of mild erotica in appeals for causes behaves in the same way that it does in advertising for consumer goods.” (p.79) Secondly, the viewer response to sexual stimuli in advertising has been found to differ across product types (Miller, 1992 ; Richmond and Hartman, 1982 ; Simpson, Horton, and Brown, 1996 ; Steadman, 1969), and the influence of the product category seems to be one of the major causes of consumer irritation in response to an advertisement rather than the provocation itself (Aaker and Bruzzone, 1985). Grazer (1981) and Grazer and Keesling (1995) showed that while PI are affected by the sexual intensity depicted in the ads, the effect varies according to the product type (in this case, jeans and liquor). Given the fact that these latter findings are intrinsically linked to the selected ads, brands, and product categories, caution must be taken attempting to generalize them (Severn, Belch, and Belch, 1990) and further research should assess the impact of various levels of provocation across a variety of product categories and specific brands where the congruence with provocation is less direct than with clothing and fashion brands. Another limitation of this research is the credibility gap caused by the difference between naturalistic and forced exposure to advertising. The results of this experiment are based on short-term reactions registered immediately following exposure to the ads. Even if it has been argued that “no lab testing situation can ever completely simulate a natural viewing situation (e.g., Ray, 1977 [in Batra and Ray, 1986, p.247])”, in real-life situations, consumers may view ads many times – and information about the brand can hence be learned over time. Vézina and Paul (1997) indeed hypothesized that possible negative attitudes expressed by consumers toward controversial ads may turn out to have positive effects in the longer term. Nevertheless, according to Aaker and Bruzzone (1981), a person can better perceive whether a commercial was exciting, fast-moving, and vigorous immediately after seeing it rather than after several days. Still a further limitation of this research is the absence of a measurement of pre-exposure attitude toward the given brands. Such a measurement was deleted from the research design to avoid contamination of the brand names in the blind-tests. A replication of this research might, however, improve the research design so that valid and reliable pre- and post-exposure measures can be compared, with the post-exposure measures eventually taking place several days after the experiment (Vézina and Paul, 1997).

30

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34

Appendices 

Appendix 1 : Provocative ads (on the left) and more traditional ads (on the right) used in the experiment

35

36

Appendix 2 : Number and percentage of respondents who knew which brands were associated with the ads

Do you know which brand is associated with this ad ? Answers Sample 3 Sample 4 Initial sample sizes 232 217 N % N %

Benetton No 191 82,3% 194 89,4% Yes 41 (38 gave the correct brand name) 17,7% 23 (20 gave the correct brand name) 10,6%

Diesel No 220 94,8% 207 95,4% Yes 12 (7 gave the correct brand name) 5,2% 10 (3 gave the correct brand name) 4,6%

Sisley No 216 93,1% 211 97,2% Yes 16 (6 gave the correct brand name) 6,9% 6 (0 gave the correct brand name) 2,8% Deleted observations 45 21 Interim sample sizes 187 196

Appendix 3 : Number and percentage of respondents who had already seen the ads

Have you already seen this ad before ? Answers Sample 1 Sample 2 Sample 3 Sample 4 Initial sample sizes 172 148 187 196 N % N % N % N %

Benetton Yes 4 2,3% 6 4,1% 1 0,5% 3 1,5% No 168 97,7% 142 95,9% 186 99,5% 193 98,5%

Diesel Yes 3 1,7% 2 1,4% 0 0 2 1% No 169 98,3% 146 98,6% 187 100% 194 99%

Sisley Yes 10 5,8% 2 1,4% 4 2,1% 2 1% No 162 94,2% 146 98,6% 183 97,9% 194 99% Deleted observations 17 9 5 7 Final sample sizes 155 139 182 189

Appendix 4 : Distribution of samples according to the gender of respondents

Sample 1 Sample 2 Sample 3 Sample 4 Total

N % N % N % N % N %

Women 85 54,84% 77 55,40% 115 63,19% 104 55,03% 381 57,29%

Men 70 45,16% 62 44,60% 67 36,81% 84 44,44% 283 42,56%

(N/A) 0 0 0 0 0 0 1 0,53% 1 0,15%

Total 155 100% 139 100% 182 100% 189 100% 665 100%

Appendix 5 : Distribution of samples according to the product involvement of respondents

Sample 1

Sample 2

Sample 3

Sample 4

Total

N % Mean Std Dev.

N % Mean Std Dev.

N % Mean Std Dev.

N % Mean Std Dev.

N % Mean Std Dev.

High 95 61,29% 5,27 0,61 77 55,40% 5,23 0,55 117 64,29% 5,25 0,54 84 44,44% 5,19 0,51 373 56,09% 5,24 0,55

Low 60 38,71% 3,56 0,72 62 44,60% 3,29 0,82 65 35,71% 3,50 0,76 105 55,56% 3,45 0,66 292 43,91% 3,45 0,73

Total 155 100% 4,61 1,06 139 100% 4,37 1,18 182 100% 4,63 1,05 189 100% 4,23 1,06 665 100% 4,45 1,09

Appendix 6 : Distribution of samples according to the age of respondents

17-18 19-20 N/A Total Mean 21-22 23-24 25-26 27-28 N % N % N % N % N % N % N % N % Sam1

32 31 20,00% 9% 16 10,32% 14 9,03% 2 5 100% 21,49 ple 27 17,42% 20,65% 33 1,2 2 1,29% 15

Sam le p2

14 10,07% 46 33,09% 47 33,81% 21 15,11% 5 3,60% 5 3,60% 1 0,72% 139 100% 20,94

Sam le 3

21 11,54% 64 6% 61 33,52% 23 12,64% 6 3,30% 0 0 18 ,94 p 35,1 7 3,85% 2 100% 20

Sam le p4

16 8,47% 29 15,34% 72 38,10% 39 20,63% 20 10,58% 11 5,82% 2 1,06% 189 100% 21,81

Tot 78 11,73% 171 1% 21 36 al 25,7 1 31,73% 116 17,44% 48 7,22% 5,41% 5 0,75% 665 100%

Appendix 7 : Distribution of samples according to the ye y ondents

BA

1

BA

2

BA

3

Ann

ée

oire

au

ar of stud of resp

prép

arat

Mas

ter

MA

M MA

MA

Mas

tco

mpl

émen

t

1

A2 3 4 er

aire

Doc

tora

t/Etu

des

de 3

e cyc

le

Oth

er

N/A

Tot

al s

Sample 1 N 63 1 1 0 30 50 1 4 3 0 1 1 155

% 65% 0 19, 32,26% 2,58% 0 5% 0,01% 100% 40,65% 0,65% 0, 35% 0,65% 1,94% 0,6

Sample 2 N 44 39 22 2 13 10 0 2 0 2 3 2 139

% ,65% 28,06% 15,83% 5 9 ,4 0,01% 100% 31 1,44% 9,3 % 7,1 % 0 1 4% 0 1,44% 2,16%

Sample 3 N 71 26 39 2 18 19 0 0 4 1 2 0 182

% ,01% 14,29% 21,43% 9 4 2, 0 100% 39 1,10% 9,8 % 10,4 % 0 0 20% 0,55% 1,10%

Sample 4 N 31 28 31 1 50 22 0 0 0 21 4 1 189

% ,40% 14,81% 16,40% 0 6 4 1 0,01% 100% 16 ,53% 26,4 % 11,6 % 0 0 0 1,11% 2,12%

Total N 209 94 93 5 111 101 1 6 7 24 10 4 665

% 31,43 14,14 13,98 0,75 16,69 ,19 0,15 0,90 1,05 3,61 1,50 0,60 100% 15

37

38

Appendix 8 : Tables of means & ANOVA summary tables - Samples 1 and 2 - Provocation Benetton (left), Provocation Diesel (middle), and Provocation Sisley (right)

Mean Std Dev. N

Sample 1 5,43 1,54 155

Women 5, 5245 1, 85

High 5,52 1,58 52

5, 45

7

Low 5,04 1,74 27

Sample 2 4,19 2,06 139

Women 77

Low 33 1, 33

Men 5,40 1,5 70

High 5,63 1,43 43

3,97 2,05

High 3 2 46

Low 4,19 1,94 31

4,45 2,06

High 4 2

4,65 2,03

Sample 1

57 1,51

,83 ,12

Men 62

,26 ,11 31

Low 31

5,43 1,54 155

High 5, 95

Women 5,52 1,58 52

Men 5,63 1,43 43

20 1,58

Women

5,04 1,74

Sample 2 4, 2,

High 4,00 2,12 77

Low 5, 60

5,33 1,45 33

Men 27

19 06 139

Women 3,83 2,12 46

Men 4,26 2,11 31

Low 4,42 1,98 62

Women 4,19 1,94 31

Men 4,65 2,03 31

Mean Std Dev. N

Sample 1 1,54,28 9 155

Women 4, 1,431 9 85

High 4,25 1,66 52

ow 4, 1,

1,7

Low 4,19 1,66 27

ple 2 2,71 1,59 139

69 0

L 39 20 33

Men 4,24 1 70

High 4,28 1,75 43

Sam

Women 2, 1,5 77

High 2,67 52

Low 2,71 1,49 31

n 2,7 1,7 62

ow 2,7 1,7 31

le 1,5 1

High 4,2 1,69 95

1, 46

Me 4 1

High 2,77 1,71 31

L 1 4

Samp 1 4,28 9 55

6

Women 4,25 1,66 52

Men 4,28 1,75 43

Low 4,3 1,42 60

1,2 33

, 1,6 27

le 2 139

High 2,71 1,59 77

0

Women 4,39 0

Men 4 19 6

Samp 2,71 1,59

Women 2,67 1,52 46

Men 2,77 1,71 31

Low 2,71 1,60 62

Women 2,71 1,49 31

Men 2,71 1,74 31

Mean Std Dev. N

Sam 1 ple 5,21 1,32 155

Women 5, 2 353 1, 85

High 5,50 1,16 52

ow 3 57

M 9 70

High 4,98 1,34 43

Low 5,26 1,23 27

Sa e 2 3,44 1,82 139

4 1, 77

L 5,0 1, 33

en 5,09 1,2

mpl

Women 3, 5 78

High

Lo

3,5 1 46

w 3,35 1,80 31

Men 3,42 1,88

Hig 2 1,

Low 61 1,93

m 2 1,

High 5,26 1,26

2 ,79

62

h 3, 3 84 31

3, 31

Sa ple 1 5, 1 32 155

95

Women 5,50 1,16 52

Men 4,98 1,34 43

Low 5,13 1,42

0 1,

M 26 1,23

mp 44 1,

High 3,40 1,80 77

60

Women 5, 3 57 33

en 5, 27

Sa le 2 3, 82 139

Women 3,52 1,79 46

Men 3,23 1,84 31

Low 3,48 1,85 62

Women 3,35 1,80 31

Men 3,61 1,93 31

Source DF Type I SS Mean Square F Value Pr > F A 1 112.4529297 112.4529297 34.52 <.0001 B 1 2.9293079 2.9293079 0.90 0.3438 C 1 0.0005780 0.0005780 0.00 0.9894 A*B 1 4.9968215 4.9968215 1.53 0.2166 A*C 1 9.8069765 9.8069765 3.01 0.0838 B*C 1 0.7069641 0.7069641 0.22 0.6417 A*B*C 1 0.7895763 0.7895763 0.24 0.6229 Model 7 131.683154 18.811879 5.77 <.0001 Error 286 931.803241 3.258053 Total 293 1063.486395

Source DF Type I SS Mean Square F Value Pr > F A 1 230.6391280 230.6391280 92.19 <.0001 B 1 1.4058337 1.4058337 0.56 0.4541 C 1 0.0330335 0.0330335 0.01 0.9086 A*B 1 0.7189424 0.7189424 0.29 0.5923 A*C 1 0.8240897 0.8240897 0.33 0.5665 B*C 1 7.5695909 7.5695909 3.03 0.0830 A*B*C 1 0.1720642 0.1720642 0.07 0.7933 Model 7 241.3626825 34.4803832 13.78 <.0001 Error 286 715.4808550 2.5016813 Total 293 956.8435374

Source DF Type I SS Mean Square F Value Pr > F A 1 179.5282590 179.5282590 69.89 <.0001 B 1 0.0045874 0.0045874 0.00 0.9663 C 1 0.0210523 0.0210523 0.01 0.9279 A*B 1 0.2400413 0.2400413 0.09 0.7601 A*C 1 0.0383782 0.0383782 0.01 0.9028 B*C 1 0.5169973 0.5169973 0.20 0.6540 A*B*C 1 0.0828510 0.0828510 0.03 0.8576 Model 7 180.4321666 25.7760238 10.03 <.0001 Error 286 734.6562688 2.5687282 Total 293 915.0884354

A = Sample B = Gender C = Product involvement

Appendix 9 : Tables of means & ANOVA summary tables - Samples 3 and 4 (due to missing values, only 370 observations can be used in these analyses) - Provocation Benetton (left), Provocation Diesel (middle), and Provocation Sisley (right)

Mean Std Dev. N

Sa 1mple 3 5,43 1,41 82

W 1omen 5,61 1,26 15

High 5,79 1,24 72

Low

M

Sa 1

W 1

5,30 1,24 43

en 5,12 1,60 67

High 5,33 1,46 45

Low 4,68 1,81 22

mple 4 4,20 1,88 88

omen 4,24 1,81 04

High 4,10 1,80 51

Low

M

Sa 1

H 1

4,38 1,82 53

en 4,14 1,98 84

High 4,16 2,17 32

Low 4,13 1,87 52

mple 3 5,43 1,41 82

igh 5,62 1,34 17

Women

n

L

n

Sa 1

Hi

5,79 1,24 72

Me 5,33 1,46 45

ow 5,09 1,48 65

Wome 5,30 1,24 43

Men 4,68 1,81 22

mple 4 4,20 1,88 88

gh 4,12 1,94 83

Women

n

L 1

n

Men 4,13 1,87 52

4,10 1,80 51

Me 4,16 2,17 32

ow 4,26 1,84 05

Wome 4,38 1,82 53

Mean Std Dev. N

Sample 3 4,25 1,56 182

Women 4,34 1,65 115

High 4,25 1,72 72

Low

M

Sa

W

4,49 1,55 43

en 4,10 1,39 67

High 4,22 1,46 45

Low 3,86 1,25 22

mple 4 2,74 1,69 188

omen 2,65 1,65 104

High 2,67 1,58 51

Low

M

Sa 1

Hi

2,64 1,72 53

en 2,85 1,74 84

High 2,59 1,54 32

Low 3,00 1,85 52

mple 3 4,25 1,56 82

gh 4,24 1,62 117

Women

Lo

n

Sa

Hi

4,25 1,72 72

Men 4,22 1,46 45

w 4,28 1,47 65

Wome 4,49 1,55 43

Men 3,86 1,25 22

mple 4 2,74 1,69 188

gh 2,64 1,56 83

Women

Lo

n

Men 3,00 1,85 52

2,67 1,58 51

Men 2,59 1,54 32

w 2,82 1,79 105

Wome 2,64 1,72 53

Mean Std Dev. N

Sample 3 5,41 1,39 182

W 1omen 5,69 1,20 15

High 5,81 1,04 72

Low

M

Sa 1

W 1

5,49 1,42 43

en 4,94 1,56 67

High 5,09 1,53 45

Low 4,64 1,59 22

mple 4 3,73 1,75 88

omen 3,85 1,71 04

High 3,84 1,54 51

Low

M

Sa 1

Hi 1

3,85 1,87 53

en 3,58 1,79 84

High 4,06 1,83 32

Low 3,29 1,72 52

mple 3 5,41 1,39 82

gh 5,53 1,30 17

Women

L

n

Sa 1

Hi

5,81 1,04 72

Men 5,09 1,53 45

ow 5,20 1,52 65

Wome 5,49 1,42 43

Men 4,64 1,59 22

mple 4 3,73 1,75 88

gh 3,93 1,65 83

Women

L 1

n

Men 3,29 1,72 52

3,84 1,54 51

Men 4,06 1,83 32

ow 3,57 1,81 05

Wome 3,85 1,87 53

Source DF Type I SS Mean Square F Value Pr > F A 1 140.3077836 140.3077836 50.95 <.0001 B 1 7.1773347 7.1773347 2.61 0.1073 C 1 2.4296347 2.4296347 0.88 0.3482 A*B 1 3.8850956 3.8850956 1.41 0.2357 A*C 1 10.5717965 10.5717965 3.84 0.0509 B*C 1 1.1696897 1.1696897 0.42 0.5150 A*B*C 1 0.0993913 0.0993913 0.04 0.8494 Model 7 165.640726 23.662961 8.59 <.0001 Error 362 996.956571 2.754024 Total 369 1162.597297

Source DF Type I SS Mean Square F Value Pr > F A 1 21 211.8003529 1.8003529 79.55 <.0001 B 1 0.0121903 0.0121903 0.00 0.9461 C 1 1.1304030 1.1304030 0.42 0.5151 A*B 1 3.7188263 3.7188263 1.40 0.2381 A*C 1 0.3954510 0.3954510 0.15 0.7002 B*C 1 0.0343877 0.0343877 0.01 0.9096 A*B*C 1 5.4574560 5.4574560 2.05 0.1531 Model 7 222.549067 31.792724 11.94 <.0001 Error 362 963.853635 2.662579 Total 369 1186.402703

Source DF Type I SS Mean Square F Value Pr > F A 1 262.0498079 262.0498079 108.43 <.0001 B 1 21.6256183 21.6256183 8.95 0.0030 C 1 9.3856364 9.3856364 3.88 0.0495 A*B 1 6.3659897 6.3659897 2.63 0.1055 A*C 1 0.0248069 0.0248069 0.01 0.9194 B*C 1 4.8689437 4.8689437 2.01 0.1566 A*B*C 1 2.1443600 2.1443600 0.89 0.3468 Model 7 306.465163 43.780738 18.12 <.0001 Error 362 874.842945 2.416693 Total 369 1181.308108

A = Sample B = Gender C = Product involvement

39

Appendix 10 : Tables of means & ANOVA summary tables - Samples 1 and 3 - Provocation Benetton (left), Provocation Diesel (middle), and Provocation Sisley (right)

Mean Std Dev. N

Sample 3

Mean Std Dev.

N

Sample 3 1

Mean Std Dev. N

Sample 3 5,43 1,41 182

Women 5,61 1,26 115

High 5,79 1,24 72

Low 5,30 1,24 43

M

h

Sam 1

en 5,12 1,60 67

Hig 5,33 1,46 45

Low 4,68 1,81 22

ple 1 5,43 1,54 55

Women 5,45 1,52 85

High 5,52 1,58 52

Low 5,33 1,45 33

M

h

Sam 1

en 5,40 1,57 70

Hig 5,63 1,43 43

Low 5,04 1,74 27

ple 3 5,43 1,41 82

High 5,62 1,34 117

Women

Lo

men

Sam 1

5,79 1,24 72

Men 5,33 1,46 45

w 5,09 1,48 65

Wo 5,30 1,24 43

Men 4,68 1,81 22

ple 1 5,43 1,54 55

High 5,57 1,51 95

Women

L

men

5,52 1,58 52

Men 5,63 1,43 43

ow 5,20 1,58 60

Wo 5,33 1,45 33

Men 5,04 1,74 27

4,25 1,56 82

Women 4,34 1,65 115

High 4,25 1,72 72

Low 4,

5,41 1,39 182

Women 5,69 1,20 115

High 5,81 1,04 72

Low 5,49 1,42 4349 1,55 43

M

Sam 1

en 4,10 1,39 67 M

h

Sam 1

en 4,94 1,56 67

Hig 5,09 1,53 45

Low 4,64 1,59 22

ple 1 5,21 1,32 55

Women 5,32 1,35 85

High 5,50 1,16 52

Low 5,03 1,57 33

High 4,22 1,46 45

Low 3,86 1,25 22

ple 1 4,28 1,59 55

Women 4,31 1,49 85

High 4,25 1,66 52

Low 4,39 1,20 33

M

h

Sam

en 4,24 1,71 70 M

h

Sam 1

en 5,09 1,29 70

Hig 4,28 1,75 43

Low 4,19 1,66 27

ple 3 4,25 1,56 182

High 4,24 1,62 117

Wo

Hig 4,98 1,34 43

Low 5,26 1,23 27

ple 3 5,41 1,39 82

High 5,53 1,30 117

men 4,

Lo

men 4,

Sam 1

25 1,72 72

Men 4,22 1,46 45

w 4,28 1,47 65

Wo 49 1,55 43

Men 3,86 1,25 22

ple 1 4,28 1,59 55

High 4,26 1,69 95

Wom

Women

Lo

men

Sam 1

5,81 1,04 72

Men 5,09 1,53 45

w 5,20 1,52 65

Wo 5,49 1,42 43

Men 4,64 1,59 22

ple 1 5,21 1,32 55

High 5,26 1,26 95

en

Lo

men

4,25 1,66 52

Men 4,28 1,75 43

w 4,30 1,42 60

Wo 4,39 1,20 33

Men 4,19 1,66 27

Women

L

men

5,50 1,16 52

Men 4,98 1,34 43

ow 5,13 1,42 60

Wo 5,03 1,57 33

Men 5,26 1,23 27

Source DF Type I SS Mean Square F Value Pr > F A 1 0.00063996 0.00063996 0.00 0.9861 B 1 6.28306987 6.28306987 2.97 0.0860 C 1 1 16.48067435 6.48067435 7.78 0.0056 A*B 1 4.29824073 4.29824073 2.03 0.1553 A*C 1 0.62095190 0.62095190 0.29 0.5886 B*C 1 1.46955349 1.46955349 0.69 0.4055 A*B*C 1 0.27464057 0.27464057 0.13 0.7190 Model 7 29.4277709 4.2039673 1.98 0.0566 Error 329 697.0410719 2.1186659 Total 336 726.4688427

Source DF Type I SS Mean Square F Value Pr > F A 1 0.05095485 0.05095485 0.02 0.8866 B 1 1.89051944 1.89051944 0.76 0.3853 C 1 0.08718877 0.08718877 0.03 0.8520 A*B 1 0.58342560 0.58342560 0.23 0.6295 A*C 1 0.00189334 0.00189334 0.00 0.9781 B*C 1 3.31379188 3.31379188 1.32 0.2506 A*B*C 1 0.60087743 0.60087743 0.24 0.6244 Model 7 6.5286513 0.9326645 0.37 0.9178 Error 329 822.9668977 2.5014191 Total 336 829.4955490

Source DF Type I SS Mean Square F Value Pr > F A 1 3.32112389 3.32112389 1.88 0.1712 B 1 20.33283667 20.33283667 11.52 0.0008 C 1 4.88141176 4.88141176 2.76 0.0973 A*B 1 5.56124320 5.56124320 3.15 0.0769 A*C 1 1.07645218 1.07645218 0.61 0.4355 B*C 1 1.65674429 1.65674429 0.94 0.3334 A*B*C 1 3.66996833 3.66996833 2.08 0.1503 Model 7 40.4997803 5.7856829 3.28 0.0022 Error 329 580.8889437 1.7656199 Total 336 621.3887240

A = Sample

involvement B = Gender C = Product

40

A = Sample r

tion Benetton (left), Provocation Diesel (middle), and Provocation Sisley (right)

B = GendeC = Product involvement

Appendix 11 : Tables of means & ANOVA summary tables - Samples 2 and 4 (due to missing values, only 327 observations can be used in these analyses) - Provoca

Mean Std Dev. N

Sample 4 4,20 1,88 188

W 1omen 4,24 1,81 04

High 4,10 1,80 51

Low

M

Sa 1

W

4,38 1,82 53

en 4,14 1,98 84

High 4,16 2,17 32

Low 4,13 1,87 52

mple 2 4,19 2,06 39

omen 3,97 2,05 77

High 3,83 2,12 46

Low

M

Sa

Hi

4,19 1,94 31

en 4,45 2,06 62

High 4,26 2,11 31

Low 4,65 2,03 31

mple 4 4,20 1,88 188

gh 4,12 1,94 83

Women

n

L 1

n

Sa 1

Hi

4,10 1,80 51

Me 4,16 2,17 32

ow 4,26 1,84 05

Wome 4,38 1,82 53

Men 4,13 1,87 52

mple 2 4,19 2,06 39

gh 4,00 2,12 77

Women

n

L

n

Men 4,65 2,03 31

3,83 2,12 46

Me 4,26 2,11 31

ow 4,42 1,98 62

Wome 4,19 1,94 31

Mean Std Dev. N

Sample 4 2,74 1,69 188

Women 2,65 1,65 104

High 2,67 1,58 51

Low

M

Sa

W

2,64 1,72 53

en 2,85 1,74 84

High 2,59 1,54 32

Low 3,00 1,85 52

mple 2 2,71 1,59 139

omen 2,69 1,50 77

High 2,67 1,52 46

Low

M

Sa

Hi

2,71 1,49 31

en 2,74 1,71 62

High 2,77 1,71 31

Low 2,71 1,74 31

mple 4 2,74 1,69 188

gh 2,64 1,56 83

Women

Lo

n

Sa

Hi

2,67 1,58 51

Men 2,59 1,54 32

w 2,82 1,79 105

Wome 2,64 1,72 53

Men 3,00 1,85 52

mple 2 2,71 1,59 139

gh 2,71 1,59 77

Women

Lo

n

Men 2,71 1,74 31

2,67 1,52 46

Men 2,77 1,71 31

w 2,71 1,60 62

Wome 2,71 1,49 31

Mean Std Dev. N

Sample 4 3,73 1,75 188

W 1omen 3,85 1,71 04

High 3,84 1,54 51

Low

M

Sa 1

W

3,85 1,87 53

en 3,58 1,79 84

High 4,06 1,83 32

Low 3,29 1,72 52

mple 2 3,44 1,82 39

omen 3,45 1,78 77

High 3,52 1,79 46

Low

M

Sa

Hi

3,35 1,80 31

en 3,42 1,88 62

High 3,23 1,84 31

Low 3,61 1,93 31

mple 4 3,73 1,75 188

gh 3,93 1,65 83

Women

L 1

n

Sa 1

Hi

3,84 1,54 51

Men 4,06 1,83 32

ow 3,57 1,81 05

Wome 3,85 1,87 53

Men 3,29 1,72 52

mple 2 3,44 1,82 39

gh 3,40 1,80 77

Women 3,

Lo

en 3,

Men 3,61 1,93 31

52 1,79 46

Men 3,23 1,84 31

w 3,48 1,85 62

Wom 35 1,80 31

Source DF Type I SS Mean Square F Value Pr > F A 1 0.00760957 0.00760957 0.00 0.9646 B 1 1.74376703 1.74376703 0.45 0.5021 C 1 4.76351846 4.76351846 1.23 0.2675 A*B 1 6.59918004 6.59918004 1.71 0.1920 A*C 1 1.00814309 1.00814309 0.26 0.6097 B*C 1 0.52604232 0.52604232 0.14 0.7123 A*B*C 1 0.49538500 0.49538500 0.13 0.7204 Model 7 15.143646 2.163378 0.56 0.7880 Error 319 1231.718740 3.861187 Total 326 1246.862385

Source DF Type I SS Mean Square F Value Pr > F A 1 6.71498230 6.71498230 2.12 0.1462 B 1 2.22901069 2.22901069 0.70 0.4019 C 1 1.90288638 1.90288638 0.60 0.4386 A*B 1 1.00669225 1.00669225 0.32 0.5731 A*C 1 3.39341751 3.39341751 1.07 0.3012 B*C 1 0.85140546 0.85140546 0.27 0.6043 A*B*C 1 8.57684075 8.57684075 2.71 0.1007 Model 7 24.675235 3.525034 1.11 0.3538 Error 319 1009.434856 3.164373 Total 326 1034.110092

Source DF Type I SS Mean Square F Value Pr > F A 1 0.05882637 0.05882637 0.02 0.8837 B 1 1.42609506 1.42609506 0.52 0.4715 C 1 0.62954447 0.62954447 0.23 0.6323 A*B 1 0.36905441 0.36905441 0.13 0.7141 A*C 1 0.57320871 0.57320871 0.21 0.6480 B*C 1 0.81445449 0.81445449 0.30 0.5863 A*B*C 1 1.36256827 1.36256827 0.50 0.4816 Model 7 5.2337518 0.7476788 0.27 0.9643 Error 319 875.5430066 2.7446489 Total 326 880.7767584

41

Appendix 12 : Tables of means & ANOVA summary tables - Samples 1 and 2 - Aad Benetton (left), Aad Diesel (middle), and Aad Sisley (right)

Mean Std Dev. N

Sample 1

Mean Std Dev. N

Sample 1

Mean Std Dev. N

Sample 1 1 3,20 1,19 155

Women

3,18 1,18 155

Women 3,14 1,12 85

High 3,17 1,13 52

Low 3,08 1,11 33

3,75 1,04 55

Women

M

h

Sam 1

en 3,24 1,27 70

Hig 3,39 1,30 43

Low 3,01 1,20 27

ple 2 4,37 1,35 39

Women 4,45 1,27 77

High 4,62 1,26 46

Low 4,19 1,25 31

M

h

Sam 1

en 4,27 1,44 62

Hig 4,69 1,20 31

Low 3,86 1,56 31

ple 1 3,18 1,18 55

High 3,27 1,21 95

Women

L

men

Sam 1

3,17 1,13 52

Men 3,39 1,30 43

ow 3,05 1,14 60

Wo 3,08 1,11 33

Men 3,01 1,20 27

ple 2 4,37 1,35 39

High 4,65 1,23 77

Women

L

men

4,62 1,26 46

Men 4,69 1,20 31

ow 4,02 1,41 62

Wo 4,19 1,25 31

Men 3,86 1,56 31

3,61 0,91 85

High 3,55 0,90 52

Low 3,70 0,93 33

2,94 1,08 85

High 2,97 1,16 52

Low 2,88 0,96 33

M

h

Sam 1

en 3,51 1,25 70

Hig 3,48 1,27 43

Low 3,56 1,25 27

ple 2 4,10 1,17 39

Women 4,13 1,07 77

High 4,28 1,00 46

Low 3,91 1,16 31

M

h

Sam

en 3,93 1,16 70

Hig 4,00 1,13 43

Low 3,81 1,20 27

ple 2 4,03 1,35 139

Women 4,18 1,34 77

High 4,44 1,42 46

Low 3,79 1,11 31

M

h

Sam 1

en 4,06 1,30 62

Hig 4,35 1,18 31

Low 3,76 1,36 31

ple 1 3,20 1,19 55

High 3,20 1,23 95

Wom

M

h

Sam

en 3,85 1,34 62

Hig 4,26 1,14 31

Low 3,44 1,42 31

ple 1 3,75 1,04 155

High 3,76 1,03 95

Wom en

L

men

Sam 1

2,97 1,16 52

Men 3,48 1,27 43

ow 3,19 1,14 60

Wo 2,88 0,96 33

Men 3,56 1,25 27

ple 2 4,10 1,17 39

High 4,31 1,07 77

Wom

en

Lo

men

Sam

3,55 0,90 52

Men 4,00 1,13 43

w 3,75 1,06 60

Wo 3,70 0,93 33

Men 3,81 1,20 27

ple 2 4,03 1,35 139

High 4,37 1,31 77

Wom en

L

men

4,28 1,00 46

Men 4,35 1,18 31

ow 3,83 1,26 62

Wo 3,91 1,16 31

Men 3,76 1,36 31

en

Lo

men

4,44 1,42 46

Men 4,26 1,14 31

w 3,61 1,28 62

Wo 3,79 1,11 31

Men 3,44 1,42 31

Source DF Type I SS Mean Square F Value Pr > F A 1 1 102.8264754 02.8264754 65.62 <.0001 B 1 0.0495370 0.0495370 0.03 0.8590 C 1 12.2350410 12.2350410 7.81 0.0056 A*B 1 1.0386974 1.0386974 0.66 0.4162 A*C 1 2.7591554 2.7591554 1.76 0.1856 B*C 1 2.0860467 2.0860467 1.33 0.2495 A*B*C 1 0.0399264 0.0399264 0.03 0.8733 Model 7 121.0348793 17.2906970 11.03 <.0001 Error 286 448.1514132 1.5669630 Total 293 569.1862925

Source DF Type I SS Mean Square F Value Pr > F A 1 5.64161523 5.64161523 4.16 0.0424 B 1 0.00979072 0.00979072 0.01 0.9324 C 1 9.71000369 9.71000369 7.15 0.0079 A*B 1 6.92676358 6.92676358 5.10 0.0246 A*C 1 9.27198885 9.27198885 6.83 0.0094 B*C 1 1.17496016 1.17496016 0.87 0.3530 A*B*C 1 0.12985062 0.12985062 0.10 0.7573 Model 7 32.8649729 4.6949961 3.46 0.0014 Error 286 388.2621360 1.3575599 Total 293 421.1271088

Source DF Type I SS Mean Square F Value Pr > F A 1 5 59.57499264 9.57499264 43.86 <.0001 B 1 5.22514351 5.22514351 3.85 0.0508 C 1 4.37497280 4.37497280 3.22 0.0738 A*B 1 7.03410523 7.03410523 5.18 0.0236 A*C 1 3.77833486 3.77833486 2.78 0.0964 B*C 1 0.00609429 0.00609429 0.00 0.9466 A*B*C 1 0.63542677 0.63542677 0.47 0.4945 Model 7 80.6290701 11.5184386 8.48 <.0001 Error 286 388.4716102 1.3582923 Total 293 469.1006803

A B C

= Sample = Gender = Product involvement

42

Appendix 13 : Tables of means & ANOVA summary tables - Samples 3 and 4 (due to missing values, only 370 observations can be used in these analyses) - Aad Benetton (left), Aad Diesel (middle), and Aad Sisley (right)

Mean Std Dev. N

Sample 4 3,85 1,17 188

Women 3,72 1,23 104

High 3,99 1,10 51

Low 3,46 1,31 53

Men 4,01 1,09 84

High 4,32 1,00 32

Low 3,82 1,10 52

Sample 3 3,02 1,25 182

Women 2,68 1,02 115

High 2,68 1,07 72

Low 2,69 0,93 43

Men 3,61 1,40 67

High 3,61 1,39 45

Low 3,60 1,46 22

Sample 4 3,85 1,17 188

High 4,12 1,07 83

Women 3,99 1,10 51

Men 4,32 1,00 32

Low 3,64 1,22 1

1

05

Women 3,46 1,31 53

Men 3,82 1,10 52

Sample 3 3,02 1,25 182

High 3,04 1,28 17

Women 2,68 1,07 72

Men 3,61 1,39 45

Low 3,00 1,21 65

Women 2,69 0,93 43

Men 3,60 1,46 22

Mean Std Dev. N

Sample 4 3,78 1,17 188

Women 3,89 1,12 104

High 4,04 0,95 51

Low 3,74 1,25 53

Men 3,65 1,22 84

High 3,76 1,20 32

Low 3,59 1,25 52

Sample 3 2,76 1,09 182

Women 2,62 1,02 115

High 2,46 0,92 72

Low 2,88 1,14 43

Men 3,01 1,16 67

High 2,93 1,15 45

Low 3,17 1,19 22

Sample 4 3,78 1,17 188

High 3,93 1,05 83

Women 4,04 0,95 51

Men 3,76 1,20 32

Low 3,67 1,24 1

1

05

Women 3,74 1,25 53

Men 3,59 1,25 52

Sample 3 2,76 1,09 182

High 2,64 1,03 17

Women 2,46 0,92 72

Men 2,93 1,15 45

Low 2,98 1,16 65

Women 2,88 1,14 43

Men 3,17 22

Mean Std Dev. N

Sample 4 3,85 1,31 188

Women 4,06 1,30 104

High 3,94 1,41 51

Low 4,18 1,19 53

Men 3,58 1,28 84

High 3,85 1,22 32

Low 3,42 1,30 52

Sample 3 3,45 1,11 182

Women 3,34 1,13 115

High 3,33 1,15 72

Low 3,36 1,11 43

Men 3,63 1,05 67

High 3,48 0,89 45

Low 3,94 1,28 22

Sample 4 3,85 1,31 188

High 3,91 1,33 83

Women 3,94 1,41 51

Men 3,85 1,22 32

Low 3,80 1,30 105

Women 4,18 1,19 53

Men 3,42 1,30 52

Sample 3 3,45 1,11 182

High 3,39 1,06 117

Women 3,33 1,15 72

Men 3,48 0,89 45

Low 3,56 1,20 65

Women 3,36 1,11 43

Men 3,941,19 1,28 22

Source DF Type I SS Mean Square F Value Pr > F A 1 63.39515321 63.39515321 46.84 <.0001 B 1 30.78165595 30.78165595 22.74 <.0001 C 1 7.68611035 7.68611035 5.68 0.0177 A*B 1 7.76721458 7.76721458 5.74 0.0171 A*C 1 5.84710563 5.84710563 4.32 0.0384 B*C 1 0.00147101 0.00147101 0.00 0.9737 A*B*C 1 0.00706534 0.00706534 0.01 0.9424 Model 7 115.4857761 16.4979680 12.19 <.0001 Error 362 489.9273050 1.3533903 Total 369 605.4130811

Source DF Type I SS Mean Square F Value Pr > F A 1 96.48690355 96.48690355 77.22 <.0001 B 1 0.36435230 0.36435230 0.29 0.5895 C 1 0.02476862 0.02476862 0.02 0.8881 A*B 1 8.72382333 8.72382333 6.98 0.0086 A*C 1 7.70115047 7.70115047 6.16 0.0135 B*C 1 0.00643707 0.00643707 0.01 0.9428 A*B*C 1 0.43666256 0.43666256 0.35 0.5548 Model 7 113.7440979 16.2491568 13.00 <.0001 Error 362 452.3279021 1.2495246 Total 369 566.0720000

Source DF Type I SS Mean Square F Value Pr > F A 1 14.68087389 14.68087389 10.20 0.0015 B 1 1.18377853 1.18377853 0.82 0.3651 C 1 0.07768834 0.07768834 0.05 0.8164 A*B 1 13.30101397 13.30101397 9.24 0.0025 A*C 1 1.22507749 1.22507749 0.85 0.3569 B*C 1 0.53613975 0.53613975 0.37 0.5421 A*B*C 1 6.19976106 6.19976106 4.31 0.0387 Model 7 37.2043330 5.3149047 3.69 0.0007 Error 362 521.1399913 1.4396132 Total 369 558.3443243

A = Sample B = Gender C = Product involvement

43

44

Appendix 14 : Responses obtained from the adjective checklist

You

ng

l ecen

t

gina

l

Ugl

y

c

Funn

y

Swee

t

d se

sgus

ting

Vio

ent

Che

erfu

l

Tri

te

Peac

eful

Ind

Ori

Sho

king

Too

cla

ssic

Sa Wi

Di T

ende

r

Tot

al

N/r

espo

nden

t

Sam

ple

1

Ben

etto

n

N 1 97 1 7 3 51 49 29 97 4 3 1 71 1 50 2 467 3,0

% 0,20% ,80% % 0,60% 10,90% 0% 6,20 20,80% 0,60% 0,20% 15,20% 20% 10,7 40% 20 0,20% 1,50 10,5 % 0,90% 0, 0% 0, 100%

Die

sel

N 42 57 4 24 1 23 71 14 40 8 6 0 21 2 4 0 317 2,0

% 13,20% ,00% % 0,30% 7,30 0% 4,40 12,60% 1,90% 0 6,60 60% 1,30 0 18 1,30% 7,60 % 22,4 % 2,50% % 0, % 100%

Sisl

ey

N 47 32 3 11 3 91 39 65 61 10 1 1 8 0 52 3 427 2,8

% 11,00% 50% % 0,70% 10% 15,2 14,30% 20% 0,20% 0 12,2 70% 7, 0,70% 2,60 21,30% 9, 0% 2,30% 0, 1,90% 0% 0, 100%

Sam

ple

2

Ben

etto

n

N 10 18 0 10 71 13 68 5 33 6 6 21 24 28 2 12 327 2,4

% 3,10% 50% 0 3, % 21,70% 4,00% ,80% 1,50 10,10% % 1,80% 6,40% 7,30% 60% 0,60 3,70% 5, 10 20 % 1,80 8, % 100%

Die

sel

N 66 31 12 24 3 4 57 37 9 11 5 1 20 6 4 3 293 2,1

% 22,50% ,60% % 1,00% 1,40 0% 12,6 3,10% 1,70% 0,30% 6,80 00% 1,40 00% 10 4,10% 8,20 % 19,5 0% 3,80% % 2, % 1, 100%

Sisl

ey

N 47 3 3 48 10 22 40 18 10 1 31 26 13 11 4 20 307 2,2

% 15,30% 00% 3,30% 0% 5,90 3,30% ,10% 8,50% 60% 1,30 50% 1, 1,00% 15,60% 7,20% 13,0 % 0,30% 10 4,20% 3, % 6, 100%

Sam

ple

3

Ben

etto

n

N 1 117 0 3 3 49 38 49 127 1 4 2 91 6 73 0 564 3,1

% 0,20% ,70% % 0,50% 8,70 70 22,50% 0,70% 0,40% 16,10% 12,9 0 20 0 0,50 % 6,70% 8, % 0,20% 1,10% 0% 100%

Die

sel

N 33 88 1 20 1 28 56 17 63 5 12 1 36 0 5 0 366 2,0

% 9,00% ,00% % 0,30% 7, 15,30% 4,60 17,20% 30% 0,30% 9, 0 1,40 0 24 0,30% 5,50 70% % 1,40% 3, 80% % 100%

Sisl

ey

N 60 42 5 9 3 100 37 84 93 9 4 1 16 0 66 4 533 2,9

% 11,30% 90% 1, % 0,60% 90% 15,80% 17,40% % 0,80% 0,20% 3, 0 12,40% 0,80% 7, 0,90% 70 18,80% 6, 1,70 00% 100%

Sam

ple

4

Ben

etto

n

N 17 17 0 27 79 27 50 21 47 3 12 18 39 42 5 9 413 2,2

% 4,10% 10% % 19,10% 6,50 10 11,40% 2,90% 4,40% 9,40 20 20% 4, 0 6,50 % 12,10% 5, % 0,70% % 10,20% 1, % 2, 100%

Die

sel

N 84 40 14 42 4 3 85 37 10 13 11 2 24 5 5 1 380 2,0

% 22,10% ,50% 1,10% 0, 22,40% 9,70 2,60% 2,90% 0,50% 6, 1,30% 1,30 30% 10 3,70% 11,10% 80% % 3,40% 30% % 0, 100%

Sisl

ey

N 56 5 7 67 11 37 45 33 15 2 48 36 14 12 4 22 414 2,2

% 13,50% 20% 2,70% 8,90 0% 8,00 3,60% ,60% 8,70% 3,40 90% 1,00 30% 1, 1,70% 16,20% % 10,9 % 0,50% 11 % 2, % 5, 100%

45

A = Sample B = Gender C = Product involvement

- Samples 1 and 2 - Abr Benetton (left), Abr Diesel (middle), and Abr Sisley (right)

Appendix 15 : Tables of means & ANOVA summary tables

Mean Std Dev. N

Sample 1 3,70 155 1,54

Women 3,87 1,57 85

High 3,99 1,64 52

3,68 1, 33

Men 3,48 1,4 70

h 4 1 4

Low 3,53 1,5 27

Sam 2 ,38 1 139

Women 4,48 1,41 77

Low 45

8

Hig 3, 5 ,48 3

2

ple 4 ,42

High 4,61 1,42 46

Low 4,27 1,39 31

Me 25 1,44 62

High 4,48 1,36 31

Low 4,03 1,50 31

Sam 1 70 1 1

High 3,75 1,5 95

n 4,

ple 3, ,54 55

8

Wom 9 1,6 5

Men 3,45 1,48 43

Lo 62 1, 60

Women 3,68 1,45 33

n 3,53 1,52 27

Sample 2 4,38 1,42 139

Hi 56 1,39 77

en 3, 9 4 2

w 3, 47

Me

gh 4,

Wome 61 1,42 46

Men 48 1,3 31

Lo 1 1,

Wom 27 1,3 31

n ,03 1 3

n 4,

4, 6

w 4, 5 44 62

en 4, 9

Me 4 ,50 1

Mean Std Dev. N

ple 4,23 1, 15Sam 1 41 5

Women 4,16 1,41 85

High 4 14 1,52 52

ow 19 1, 33

n 33 1,41 70

g 42 1, 43

ow 18 1,46 27

Sa le 2 40 1, 139

Women 4,61 1,51 77

,

L 4, 24

Me 4,

Hi h 4, 39

L 4,

mp 4, 51

High 4,96 1,40 46

Low 4,10 1,54 31

Men 4,13 1,49 62

gh 4 45 1, 31

ow 81 1,50 31

S e 23 1, 15

27 1,46 95

Hi , 44

L 3,

ampl 1 4, 41 5

High 4,

Wom 14 1, 52

42 1,39 43

w 4,18 1, 60

Women 4,19 1,24 33

Men 4,18 1,46 27

Sample 2 4,40 1,51 139

Hi 4,75 1,43 77

en 4, 52

Men 4,

Lo 33

gh

Wo 96 1, 46

en 45 1,44 31

95 1, 62

ome 10 1,54 31

81 1, 31

men 4, 40

M 4,

Low 3, 51

W n 4,

Men 3, 50

Mean Std Dev. N

55Sample 1 3,43 1 1,45

Women 3,40 1,50 85

High 3 51 1,54 5

ow 3,24 1, 33

7 1,

igh 2 1 43

ow 3 1,

Sa le 2 25 1, 139

Women 4,42 1,34 77

, 2

L 45

Men 3,4 39 70

H 3,4 ,48

L 3,5 26 27

mp 4, 31

High 4,56 1,15 46

Low 4,21 1,57 31

Men 4,04 1,24 62

gh 4 32 1, 31

ow 5 1,

S e 1 1 155

7 1,

Hi , 21

L 3,7 23 31

ampl 3,43 ,45

High 3,4 51 95

Wom 1 1, 52

42 1,48 4

w 3,37 1, 60

Women 3,24 1,45 33

Men 3,53 1,26 27

Sample 2 4,25 1,31 139

Hi 4,46 1,1 77

en 3,5 54

Men 3, 3

Lo 37

gh 7

Wo 6 1, 46

en 2 1,

8 1, 62

ome 1 1,

75 1, 31

men 4,5 15

M 4,3 21 31

Low 3,9 42

W n 4,2 57 31

Men 3, 23

Source DF Type I SS Mean Square F Value Pr > F A 1 34.03485757 34.03485757 15.49 0.0001 B 1 6.93357740 6.93357740 3.16 0.0767 C 1 4.41347034 4.41347034 2.01 0.1574 A*B 1 0.67107697 0.67107697 0.31 0.5809 A*C 1 1.18932910 1.18932910 0.54 0.4625 B*C 1 0.39813801 0.39813801 0.18 0.6706 A*B*C 1 1.04665443 1.04665443 0.48 0.4906 Model 7 48.6871038 6.9553005 3.17 0.0031 Error 286 628.2609234 2.1967165 Total 293 676.9480272

Source DF Type I SS Mean Square F Value Pr > F A 1 48.70269883 48.70269883 25.57 <.0001 B 1 1.60426547 1.60426547 0.84 0.3595 C 1 5.63408962 5.63408962 2.96 0.0865 A*B 1 3.13824424 3.13824424 1.65 0.2003 A*C 1 2.20369965 2.20369965 1.16 0.2830 B*C 1 0.15582621 0.15582621 0.08 0.7751 A*B*C 1 1.60313064 1.60313064 0.84 0.3597 Model 7 63.0419547 9.0059935 4.73 <.0001 Error 286 544.7060725 1.9045667 Total 293 607.7480272

Source DF Type I SS Mean Square F Value Pr > F A 1 1.89588903 1.89588903 0.92 0.3392 B 1 1.47883678 1.47883678 0.71 0.3985 C 1 12.81580191 12.81580191 6.20 0.0134 A*B 1 6.77190707 6.77190707 3.27 0.0714 A*C 1 8.11867048 8.11867048 3.92 0.0485 B*C 1 0.02840820 0.02840820 0.01 0.9068 A*B*C 1 1.14707255 1.14707255 0.55 0.4571 Model 7 32.2565860 4.6080837 2.23 0.0322 Error 286 591.6085840 2.0685615 Total 293 623.8651701

Appendix 16 : Tables of means & ANOVA summary tables - Samples 3 and 4 (due to missing values, only 370 observations can be used in these anAppendix 16 : Tables of means & ANOVA summary tables - Samples 3 and 4 (due to missing values, only 370 observations can be used in these analyses) - Abr Benetton (left), Abr Diesel (middle), and Abr Sisley (right)

alyses) - Abr Benetton (left), Abr Diesel (middle), and Abr Sisley (right)

Mean Std Dev. N

Sample 3 2,32 1,15 182

Women 2,18 1,14 115

High 2,07 1,06 72

Low 2,35 1,27 43

Men 2,57 1,12 67

High 2,47 1,11 45

Low 2,77 1,16 22

Sample 4 3,30 1,30 188

Women 3,30 1,30

A = Sample B = Gender ender C = Product involvement C = Product involvement

104

High 3,51 1,22 51

Low 3,09 1,35 53

Men 3,30 1,31 84

High 3,34 1,22 32

Low 3,28 1,38 52

Sample 3 2,32 1,15 182

High 2,22 1,09 117

Women 2,07 1,06 72

Men 2,47 1,11 45

Low 2,50 1,24 65

Women 2,35 1,27 43

Men 2,77 1,16 22

Sample 4 3,30 1,30 188

High 3,44 1,22 83

Women 3,51 1,22 51

Men 3,34 1,22 32

Low 3,19 1,36 105

Women 3,09 1,35 53

Men 3,28 1,38 52

Mean Std Dev. N

Sample 3 3,21 1,28 182

Women 3,06 1,37 115

High 3,13 1,36 72

Low 2,93 1,40 43

Men 3,47 1,06 67

High 3,37 1,02 45

Low 3,69 1,15 22

Sample 4 3,78 1,45 188

Women 4,01 1,47 104

High 4,02 1,55 51

Low 3,99 1,41 53

Men 3,51 1,39 84

High 3,79 1,20 32

Low 3,33 1,47 52

Sample 3 3,21 1,28 182

High 3,22 1,24 117

Women 3,13 1,36 72

Men 3,37 1,02 45

Low 3,19 1,36 65

Women 2,93 1,40 43

Men 3,69 1,15 22

Sample 4 3,78 1,45 188

High 3,93 1,42 83

Women 4,02 1,55 51

Men 3,79 1,20 32

Low 3,66 1,47 105

Women 3,99 1,41 53

Men 3,33 1,47 52

Mean Std Dev. N

Sample 3 2,70 1,47 182

Women 2,39 1,28 115

High 2,42 1,21 72

Low 2,33 1,42 43

Men 3,23 1,61 67

High 3,12 1,60 45

Low 3,45 1,64 22

Sample 4 3,89 1,38 188

Women 3,66 1,45 104

High 3,98 1,33 51

Low 3,34 1,50 53

Men 4,18 1,25 84

High 4,51 1,20 32

Low 3,98 1,25 52

Sample 3 2,70 1,47 182

High 2,69 1,41 117

Women 2,42 1,21 72

Men 3,12 1,60 45

Low 2,71 1,58 65

Women 2,33 1,42 43

Men 3,45 1,64 22

Sample 4 3,89 1,38 188

High 4,19 1,30 83

Women 3,98 1,33 51

Men 4,51 1,20 32

Low 3,66 1,41 105

Women 3,34 1,50 53

Men 3,98 1,25 52

Source DF Type I SS Mean Square F Value Pr > F A 1 88.85347906 88.85347906 59.40 <.0001 B 1 3.24471569 3.24471569 2.17 0.1417 C 1 0.01347391 0.01347391 0.01 0.9244 A*B 1 3.23503908 3.23503908 2.16 0.1423 A*C 1 6.66570656 6.66570656 4.46 0.0355 B*C 1 0.82013043 0.82013043 0.55 0.4595 A*B*C 1 0.55027824 0.55027824 0.37 0.5445 Model 7 103.3828230 14.7689747 9.87 <.0001 Error 362 541.4994473 1.4958548 Total 369 644.8822703

Source DF Type I SS Mean Square F Value Pr > F A 1 131.2828062 131.2828062 69.22 <.0001 B 1 40.8299630 40.8299630 21.53 <.0001 C 1 7.4719516 7.4719516 3.94 0.0479 A*B 1 1.6314100 1.6314100 0.86 0.3543 A*C 1 9.2799641 9.2799641 4.89 0.0276 B*C 1 1.3854132 1.3854132 0.73 0.3933 A*B*C 1 0.4472199 0.4472199 0.24 0.6275 Model 7 192.3287280 27.4755326 14.49 <.0001 Error 362 686.5604612 1.8965759 Total 369 878.8891892

Source DF Type I SS Mean Square F Value Pr > F A 1 30.25547313 30.25547313 16.49 <.0001 B 1 0.34144340 0.34144340 0.19 0.6665 C 1 2.14187706 2.14187706 1.17 0.2807 A*B 1 17.72085203 17.72085203 9.66 0.0020 A*C 1 0.94252546 0.94252546 0.51 0.4740 B*C 1 0.00076384 0.00076384 0.00 0.9837 A*B*C 1 4.61652216 4.61652216 2.52 0.1136 Model 7 56.0194571 8.0027796 4.36 0.0001 Error 362 664.2395699 1.8349159 Total 369 720.2590270

46

Appendix 17 : Tables of means & ANOVA summary tables - Samples 1 and 2 - PI Benetton (left), PI Diesel (middle), and PI Sisley (right)

Mean Std Dev. N

Sample 1 3,15 1,43 155

Women 3,33 1,44 85

High 3,34 1,34 52

Low 3,31 1,61 33

Men 2,94 1,38 70

High 2,82 1,42 43

Low 3,13 1,33 27

Sample 2 3,52 1,41 139

Women 3,58 1,48 77

High 3,73 1,49 46

Low 3,35 1,45 31

Men 3,45 1,34 62

High 3,46 1,44 31

Low 3,45 1,25 31

Sample 1 3,15 1,43 155

High 3,11 1,39 95

Women 3,34 1,34 52

Men 2,82 1,42 43

Low 3,23 1,48 60

Women 3,31 1,61 33

Men 3,13 1,33 27

Sample 2 3,52 1,41 139

High 3,62 1,47 77

Women 3,73 1,49 46

Men 3,46 1,44 31

Low 3,40 1,34 62

Women 3,35 1,45 31

Men 3,45 31

Mean Std Dev. N

Sample 1 3,66 1,44 155

Women 3,54 1,43 85

High 3,56 1,50 52

Low 3,52 1,33 33

Men 3,79 1,46 70

High 3,92 1,49 43

1,25

Low 3,59 1,42 27

Sample 2 3,45 1,52 139

Women 3,50 1,53 77

High 3,73 1,52 46

Low 3,15 1,51 31

Men 3,39 1,50 62

High 3,51 1,64 31

Low 3,27 1,36 31

Sample 1 3,66 1,44 155

High 3,72 1,50 95

Women 3,56 1,50 52

Men 3,92 1,49 43

Low 3,55 1,36 60

Women 3,52 1,33 33

Men 3,59 1,42 27

Sample 2 3,45 1,52 139

High 3,64 1,56 77

Women 3,73 1,52 46

Men 3,51 1,64 31

Low 3,21 1,43 62

Women 3,15 1,51 31

Men 3,27 1,36 31

Mean Std Dev. N

Sample 1 2,78 1,33 155

Women 2,79 1,39 85

High 2,77 1,45 52

Low 2,83 1,30 33

Men 2,76 1,28 70

High 2,63 1,24 43

Low 2,97 1,33 27

Sample 2 2,91 1,58 139

Women 3,03 1,55 77

High 3,07 1,57 46

Low 2,96 1,55 31

Men 2,77 1,61 62

High 3,17 1,79 31

Low 2,37 1,31 31

Sample 1 2,78 1,33 155

High 2,71 1,35 95

Women 2,77 1,45 52

Men 2,63 1,24 43

Low 2,89 1,30 60

Women 2,83 1,30 33

Men 2,97 1,33 27

Sample 2 2,91 1,58 139

High 3,11 1,65 77

Women 3,07 1,57 46

Men 3,17 1,79 31

Low 2,67 1,45 62

Women 2,96 1,55 31

Men 2,37 1,31 31

Source DF Type I SS Mean Square F Value Pr > F A 1 10.04279694 10.04279694 4.97 0.0266 B 1 4.97402580 4.97402580 2.46 0.1179 C 1 0.07040042 0.07040042 0.03 0.8521 A*B 1 1.25671028 1.25671028 0.62 0.4312 A*C 1 2.00707988 2.00707988 0.99 0.3200 B*C 1 2.11875039 2.11875039 1.05 0.3069 A*B*C 1 0.00123503 0.00123503 0.00 0.9803 Model 7 20.4709987 2.9244284 1.45 0.1867 Error 286 578.3890013 2.0223392 Total 293 598.8600000

Source DF Type I SS Mean Square F Value Pr > F A 1 3.12682996 3.12682996 1.43 0.2331 B 1 0.47585529 0.47585529 0.22 0.6414 C 1 6.34729883 6.34729883 2.90 0.0897 A*B 1 1.90538608 1.90538608 0.87 0.3517 A*C 1 1.08934994 1.08934994 0.50 0.4812 B*C 1 0.00037430 0.00037430 0.00 0.9896 A*B*C 1 1.74816335 1.74816335 0.80 0.3723 Model 7 14.6932578 2.0990368 0.96 0.4618 Error 286 626.2237490 2.1895935 Total 293 640.9170068

Source DF Type I SS Mean Square F Value Pr > F A 1 1.31911351 1.31911351 0.63 0.4296 B 1 1.32660501 1.32660501 0.63 0.4283 C 1 0.85796107 0.85796107 0.41 0.5240 A*B 1 0.85016307 0.85016307 0.40 0.5259 A*C 1 6.54325856 6.54325856 3.10 0.0792 B*C 1 0.61980815 0.61980815 0.29 0.5881 A*B*C 1 4.02069148 4.02069148 1.91 0.1684 Model 7 15.5376009 2.2196573 1.05 0.3944 Error 286 602.9561406 2.1082383 Total 293 618.4937415

A =B =C =

Sample Gender Product involvement

47

A = Sample

nt

sed in these analyses) - PI Benetton (left), PI Diesel (middle), and PI Sisley (right)

B = Gender C = Product involveme

Appendix 18 : Tables of means & ANOVA summary tables - Samples 3 and 4 (due to missing values, only 370 observations can be u

Mean Std Dev. N

Sample 3 2,14 1,14 182

Women 2,16 1,18 115

High 2,06 1,15 72

Low 2,33 1,22 43

Men 2,11 1,06 67

High 2,05 1,07 45

Low 2,23 1,07 22

Sample 4 2,37 1,23 188

Women 2,34 1,24 104

High 2,47 1,28 51

Low 2,21 1,19 53

Men 2,42 1,22 84

High 2,28 1,20 32

Low 2,51 1,23 52

Sample 3 2,14 1,14 182

High 2,06 1,12 117

Women 2,06 1,15 72

Men 2,05 1,07 45

Low 2,30 1,17 65

Women 2,33 1,22 43

Men 2,23 1,07 22

Sample 4 2,37 1,23 188

High 2,40 1,25 83

Women 2,47 1,28 51

Men 2,28 1,20 32

Low 2,36 1,21 105

Women 2,21 1,19 53

Men 2,51 52

Mean Std Dev. N

Sample 3 2,77 1,28 182

Women

1,23

2,71 1,23 115

High 2,76 1,17 72

Low 2,64 1,33 43

Men 2,87 1,37 67

High 2,78 1,38 45

Low 3,05 1,36 22

Sample 4 2,82 1,26 188

Women 3,12 1,22 104

High 3,20 1,24 51

Low 3,04 1,21 53

Men 2,46 1,23 84

High 2,43 1,20 32

Low 2,48 1,25 52

Sample 3 2,77 1,28 182

High 2,77 1,25 117

Women 2,76 1,17 72

Men 2,78 1,38 45

Low 2,78 1,34 65

Women 2,64 1,33 43

Men 3,05 1,36 22

Sample 4 2,82 1,26 188

High 2,90 1,28 83

Women 3,20 1,24 51

Men 2,43 1,20 32

Low 2,76 1,26 105

Women 3,04 1,21 53

Men 2,48 1,25 52

Mean Std Dev. N

Sample 3 2,42 1,31 182

Women 2,40 1,27 115

High 2,38 1,28 72

Low 2,43 1,26 43

Men 2,46 1,37 67

High 2,40 1,40 45

Low 2,58 1,35 22

Sample 4 2,59 1,30 188

Women 2,68 1,31 104

High 2,93 1,37 51

Low 2,43 1,21 53

Men 2,48 1,28 84

High 2,68 1,35 32

Low 2,35 1,23 52

Sample 3 2,42 1,31 182

High 2,39 1,32 117

Women 2,38 1,28 72

Men 2,40 1,40 45

Low 2,48 1,29 65

Women 2,43 1,26 43

Men 2,58 1,35 22

Sample 4 2,59 1,30 188

High 2,84 1,36 83

Women 2,93 1,37 51

Men 2,68 1,35 32

Low 2,39 1,21 105

Women 2,43 1,21 53

Men 2,35 1,23 52

Source DF Type I SS Mean Square F Value Pr > F A 1 4.96223325 4.96223325 3.53 0.0612 B 1 0.02657599 0.02657599 0.02 0.8908 C 1 0.74967570 0.74967570 0.53 0.4659 A*B 1 0.33435787 0.33435787 0.24 0.6262 A*C 1 1.78022407 1.78022407 1.27 0.2614 B*C 1 1.06618885 1.06618885 0.76 0.3846 A*B*C 1 1.77496000 1.77496000 1.26 0.2621 Model 7 10.6942157 1.5277451 1.09 0.3716 Error 362 509.2776762 1.4068444 Total 369 519.9718919

Source DF Type I SS Mean Square F Value Pr > F A 1 2.52546930 2.52546930 1.49 0.2223 B 1 0.52073031 0.52073031 0.31 0.5791 C 1 3.07265049 3.07265049 1.82 0.1783 A*B 1 1.19420970 1.19420970 0.71 0.4011 A*C 1 6.05722492 6.05722492 3.58 0.0591 B*C 1 0.48379159 0.48379159 0.29 0.5929 A*B*C 1 0.00913750 0.00913750 0.01 0.9414 Model 7 13.8632138 1.9804591 1.17 0.3179 Error 362 611.6637051 1.6896787 Total 369 625.5269189

Source DF Type I SS Mean Square F Value Pr > F A 1 0.26049580 0.26049580 0.17 0.6848 B 1 6.47438759 6.47438759 4.10 0.0436 C 1 0.31628101 0.31628101 0.20 0.6547 A*B 1 14.41080314 14.41080314 9.13 0.0027 A*C 1 0.15049500 0.15049500 0.10 0.7576 B*C 1 1.80099103 1.80099103 1.14 0.2861 A*B*C 1 0.14275785 0.14275785 0.09 0.7638 Model 7 23.5562114 3.3651731 2.13 0.0397 Error 362 571.2810859 1.5781245 Total 369 594.8372973

48

Appendix 19 : Tables of means & ANOVA summary tables - Samples 1 and 3 - Aad Benetton (left), Aad Diesel (middle), and Aad Sisley (right)

Mean Std Dev. N

Sample 1 3,18 1,18 155

Women 3,14 1,12 85

High 3,17 1,13 52

Low 3,08 1,11 33

Men 3,24 1,27 70

High 3,39 1,30 43

Low 3,01 1,20 27

Sample 3 2,76 1,09 182

Women 2,62 1,02 115

High 2,46 0,92 72

Low 2,88 1,14 43

Men 3,01 1,16 67

High 2,93 1,15 45

Low 3,17 1,19 22

Sample 1 3,18 1,18 155

High 3,27 1,21 95

Women 3,17 1,13 52

Men 3,39 1,30 43

Low 3,05 1,14 60

Women 3,08 1,11 33

Men 3,01 1,20 27

Sample 3 2,76 1,09 182

High 2,64 1,03

117

Women 2,46 0,92 72

Men 2,93 1,15 45

Low 2,98 1,16 65

Women 2,88 1,14 43

Men 3,17 1,19 22

Mean Std Dev. N

Sample 1 3,75 1,04 155

Women 3,61 0,91 85

High 3,55 0,90 52

Low 3,70 0,93 33

Men 3,93 1,16 70

High 4,00 1,13 43

Low 3,81 1,20 27

Sample 3 3,45 1,11 182

Women 3,34 1,13 115

High 3,33 1,15 72

Low 3,36 1,11 43

Men 3,63 1,05 67

High 3,48 0,89 45

Low 3,94 1,28 22

Sample 1 3,75 1,04 155

High 3,76 1,03 95

Women 3,55 0,90 52

Men 4,00 1,13 43

Low 3,75 1,06 60

Women 3,70 0,93 33

Men 3,81 1,20 27

Sample 3 3,45 1,11 182

High 3,39 1,06 117

Women 3,33 1,15 72

Men 3,48 0,89 45

Low 3,56 1,20 65

Women 3,36 1,11 43

Men 3,94 1,28 22

Mean Std Dev. N

Sample 1 3,20 1,19 155

Women 2,94 1,08 85

High 2,97 1,16 52

Low 2,88 0,96 33

Men 3,51 1,25 70

High 3,48 1,27 43

Low 3,56 1,25 27

Sample 3 3,02 1,25 182

Women 2,68 1,02 115

High 2,68 1,07 72

Low 2,69 0,93 43

Men 3,61 1,40 67

High 3,61 1,39 45

Low 3,60 1,46 22

Sample 1 3,20 1,19 155

High 3,20 1,23 95

Women 2,97 1,16 52

Men 3,48 1,27 43

Low 3,19 1,14 60

Women 2,88 0,96 33

Men 3,56 1,25 27

Sample 3 3,02 1,25 182

High 3,04 1,28 117

Women 2,68 1,07 72

Men 3,61 1,39 45

Low 3,00 1,21 65

Women 2,69 0,93 43

Men 3,60 1,46 22

Source DF Type I SS Mean Square F Value Pr > F A 1 1 15.01535593 5.01535593 11.89 0.0006 B 1 5.25581686 5.25581686 4.16 0.0421 C 1 0.51871875 0.51871875 0.41 0.5220 A*B 1 1.66117862 1.66117862 1.32 0.2523 A*C 1 6.38097057 6.38097057 5.05 0.0253 B*C 1 1.03393539 1.03393539 0.82 0.3662 A*B*C 1 0.07158353 0.07158353 0.06 0.8120 Model 7 29.9375597 4.2767942 3.39 0.0017 Error 329 415.4936570 1.2628987 Total 336 445.4312166

Source DF Type I SS Mean Square F Value Pr > F A 1 7.80198861 7.80198861 6.82 0.0094 B 1 7.39360740 7.39360740 6.46 0.0115 C 1 0.71319003 0.71319003 0.62 0.4303 A*B 1 0.01826589 0.01826589 0.02 0.8995 A*C 1 0.70564220 0.70564220 0.62 0.4328 B*C 1 0.05509091 0.05509091 0.05 0.8264 A*B*C 1 2.79026137 2.79026137 2.44 0.1193 Model 7 19.4780464 2.7825781 2.43 0.0192 Error 329 376.3034966 1.1437796 Total 336 395.7815430

Source DF Type I SS Mean Square F Value Pr > F A 1 2.47235114 2.47235114 1.79 0.1819 B 1 46.14646306 46.14646306 33.41 <.0001 C 1 0.00685124 0.00685124 0.00 0.9439 A*B 1 2.43492815 2.43492815 1.76 0.1852 A*C 1 0.00149927 0.00149927 0.00 0.9737 B*C 1 0.10329396 0.10329396 0.07 0.7847 A*B*C 1 0.14459583 0.14459583 0.10 0.7465 Model 7 51.3099826 7.3299975 5.31 <.0001 Error 329 454.4776138 1.3813909 Total 336 505.7875964

A =B =C =

Sample Gender Product involvement

49

Appendix 20 : Tables of means & ANOVA summary tables - Samples 2 and 4 (due to missing values, only 327 observations can be used in these analyses) - Aad Benetton (left), Aad Diesel (middle), and Aad Sisley (right)

Mean Std Dev. N

Sample 2 4,37 1,35 139

Women 4,45 1,27 77

High 4,62 1,26 46

Low 4,19 1,25 31

Men 4,27 1,44 62

High 4,69 1,20 31

Low 3,86 1,56 31

Sample 4 3,78 1,17 188

Women 3,89 1,12 104

High 4,04 0,95 51

Low 3,74 1,25 53

Men 3,65 1,22 84

High 3,76 1,20 32

Low 3,59 1,25 52

Sample 2 4,37 1,35 139

High 4,65 1,23 77

Women 4,62 1,26 46

Men 4,69 1,20 31

Low 4,02 1,41 62

Women 4,19 1,25 31

Men 3,86 1,56 31

Sample 4 3,78 1,17 188

High 3,93 1,05 83

Women 4,04 0,95 51

Men 3,76 1,20 32

Low 3,67 1,24 105

Women 3,74 1,25 53

Men 3,59 1,25 52

Mean Std Dev. N

Sample 2 4,03 1,35 139

Women 4,18 1,34 77

High 4,44 1,42 46

Low 3,79 1,11 31

Men 3,85 1,34 62

High 4,26 1,14 31

Low 3,44 1,42 31

Sample 4 3,85 1,31 188

Women 4,06 1,30 104

High 3,94 1,41 51

Low 4,18 1,19 53

Men 3,58 1,28 84

High 3,85 1,22 32

Low 3,42 1,30 52

Sample 2 4,03 1,35 139

High 4,37 1,31 77

Women 4,44 1,42 46

Men 4,26 1,14 31

Low 3,61 1,28 62

Women 3,79 1,11 31

Men 3,44 1,42 31

Sample 4 3,85 1,31 188

High 3,91 1,33 83

Women 3,94 1,41 51

Men 3,85 1,22 32

Low 3,80 1,30 105

Women 4,18 1,19 53

Men 3,42 1,30 52

Mean Std Dev. N

Sample 2 4,10 1,17 139

Women 4,13 1,07 77

High 4,28 1,00 46

Low 3,91 1,16 31

Men 4,06 1,30 62

High 4,35 1,18 31

Low 3,76 1,36 31

Sample 4 3,85 1,17 188

Women 3,72 1,23 104

High 3,99 1,10 51

Low 3,46 1,31 53

Men 4,01 1,09 84

High 4,32 1,00 32

Low 3,82 1,10 52

Sample 2 4,10 1,17 139

High 4,31 1,07 77

Women 4,28 1,00 46

Men 4,35 1,18 31

Low 3,83 1,26 62

Women 3,91 1,16 31

Men 3,76 1,36 31

Sample 4 3,85 1,17 188

High 4,12 1,07 83

Women 3,99 1,10 51

Men 4,32 1,00 32

Low 3,64 1,22 105

Women 3,46 1,31 53

Men 3,82 1,10 52

Source DF Type I SS Mean Square F Value Pr > F A 1 27.50018259 27.50018259 18.09 <.0001 B 1 3.49562798 3.49562798 2.30 0.1304 C 1 1 12.81693769 2.81693769 8.43 0.0039 A*B 1 0.05753396 0.05753396 0.04 0.8459 A*C 1 2.70974105 2.70974105 1.78 0.1828 B*C 1 0.20827328 0.20827328 0.14 0.7115 A*B*C 1 1.25528057 1.25528057 0.83 0.3642 Model 7 48.0435771 6.8633682 4.51 <.0001 Error 319 484.9856584 1.5203312 Total 326 533.0292355

Source DF Type I SS Mean Square F Value Pr > F A 1 2.71483055 2.71483055 1.62 0.2034 B 1 14.16956051 14.16956051 8.48 0.0038 C 1 9.33908784 9.33908784 5.59 0.0187 A*B 1 0.40774911 0.40774911 0.24 0.6217 A*C 1 8.95900219 8.95900219 5.36 0.0212 B*C 1 4.01737931 4.01737931 2.40 0.1220 A*B*C 1 1.17798000 1.17798000 0.70 0.4018 Model 7 40.7855895 5.8265128 3.49 0.0013 Error 319 533.0986307 1.6711556 Total 326 573.8842202

Source DF Type I SS Mean Square F Value Pr > F A 1 4.81750136 4.81750136 3.63 0.0578 B 1 1.42849546 1.42849546 1.07 0.3006 C 1 19.80471028 19.80471028 14.90 0.0001 A*B 1 2.62961698 2.62961698 1.98 0.1605 A*C 1 0.04207847 0.04207847 0.03 0.8589 B*C 1 0.12049947 0.12049947 0.09 0.7635 A*B*C 1 0.28166814 0.28166814 0.21 0.6456 Model 7 29.1245702 4.1606529 3.13 0.0033 Error 319 423.9213014 1.3289069 Total 326 453.0458716

A = Sample B = Gender C = Product involvement

50

Appendix 21 : Tables of means & ANOVA summary tables - Samples 1 and 3 - Abr Benetton (left), Abr Diesel (middle), and Abr Sisley (right)

Mean Std Dev. N

Sample 3 2,32 1,15 182

Women 2,18 1,14 115

High 2,07 1,06 72

Low 2,35 1,27 43

Men 2,57 1,12 67

High 2,47 1,11 45

Low 2,77 1,16 22

Sample 1 3,70 1,54 155

Women 3,87 1,57 85

High 3,99 1,64 52

Low 3,68 1,45 33

Men 3,48 1,48 70

High 3,45 1,48 43

Low 3,53 1,52 27

Sample 3 2,32 1,15 182

High 2,22 1,09 117

Women 2,07 1,06 72

Men 2,47 1,11 45

Low 2,50 1,24 65

Women 2,35 1,27 43

Men 2,77 1,16 22

Sample 1 3,70 1,54 155

High 3,75 1,58 95

Women 3,99 1,64 52

Men 3,45 1,48 43

Low 3,62 1,47 60

Women 3,68 1,45 33

Men 3,53 27

Mean Std Dev. N

Sample 3 3,21 1,28 182

Women

1,52

3,06 1,37 115

High 3,13 1,36 72

Low 2,93 1,40 43

Men 3,47 1,06 67

High 3,37 1,02 45

Low 3,69 1,15 22

Sample 1 4,23 1,41 155

Women 4,16 1,41 85

High 4,14 1,52 52

Low 4,19 1,24 33

Men 4,33 1,41 70

High 4,42 1,39 43

Low 4,18 1,46 27

Sample 3 3,21 1,28 182

High 3,22 1,24 117

Women 3,13 1,36 72

Men 3,37 1,02 45

Low 3,19 1,36 65

Women 2,93 1,40 43

Men 3,69 1,15 22

Sample 1 4,23 1,41 155

High 4,27 1,46 95

Women 4,14 1,52 52

Men 4,42 1,39 43

Low 4,18 1,33 60

Women 4,19 1,24 33

Men 4,18 1,46 27

Mean Std Dev. N

Sample 3 2,70 1,47 182

Women 2,39 1,28 115

High 2,42 1,21 72

Low 2,33 1,42 43

Men 3,23 1,61 67

High 3,12 1,60 45

Low 3,45 1,64 22

Sample 1 3,43 1,45 155

Women 3,40 1,50 85

High 3,51 1,54 52

Low 3,24 1,45 33

Men 3,47 1,39 70

High 3,42 1,48 43

Low 3,53 1,26 27

Sample 3 2,70 1,47 182

High 2,69 1,41 117

Women 2,42 1,21 72

Men 3,12 1,60 45

Low 2,71 1,58 65

Women 2,33 1,42 43

Men 3,45 1,64 22

Sample 1 3,43 1,45 155

High 3,47 1,51 95

Women 3,51 1,54 52

Men 3,42 1,48 43

Low 3,37 1,37 60

Women 3,24 1,45 33

Men 3,53 1,26 27

Source DF Type I SS Mean Square F Value Pr > F A 1 158.4247262 158.4247262 89.12 <.0001 B 1 0.0354176 0.0354176 0.02 0.8878 C 1 0.5765147 0.5765147 0.32 0.5694 A*B 1 12.3465677 12.3465677 6.95 0.0088 A*C 1 3.4710453 3.4710453 1.95 0.1633 B*C 1 0.7432702 0.7432702 0.42 0.5183 A*B*C 1 0.6164805 0.6164805 0.35 0.5563 Model 7 176.2140222 25.1734317 14.16 <.0001 Error 329 584.8663339 1.7777092 Total 336 761.0803561

Source DF Type I SS Mean Square F Value Pr > F A 1 87.74969162 87.74969162 48.96 <.0001 B 1 7.15046743 7.15046743 3.99 0.0466 C 1 0.18410331 0.18410331 0.10 0.7488 A*B 1 1.25320605 1.25320605 0.70 0.4037 A*C 1 0.09955608 0.09955608 0.06 0.8138 B*C 1 0.29143494 0.29143494 0.16 0.6870 A*B*C 1 3.01218913 3.01218913 1.68 0.1958 Model 7 99.7406486 14.2486641 7.95 <.0001 Error 329 589.6789360 1.7923372 Total 336 689.4195846

Source DF Type I SS Mean Square F Value Pr > F A 1 4 44.88502919 4.88502919 21.75 <.0001 B 1 17.92800185 17.92800185 8.69 0.0034 C 1 0.04506691 0.04506691 0.02 0.8826 A*B 1 12.29302028 12.29302028 5.96 0.0152 A*C 1 0.51285871 0.51285871 0.25 0.6185 B*C 1 3.00897518 3.00897518 1.46 0.2282 A*B*C 1 0.00482657 0.00482657 0.00 0.9615 Model 7 78.6777787 11.2396827 5.45 <.0001 Error 329 679.1059602 2.0641519 Total 336 757.7837389

A = Sample B = Gender C = Product involvement

51

Appendix 22 : Tables of means & ANOVA summary tables - Samples 2 and 4 (due to missing values, only 327 observations can be used in these analyses) - Abr Benetton (left), Abr Diesel (middle), and Abr Sisley (right)

A = Sample B = Gender C = Product involvement

Mean Std Dev. N

Sample 2 4,38 1,42 139

Women 4,48 1,41 77

High 4,61 1,42 46

Low 4,27 1,39 31

Men 4,25 1,44 62

High 4,48 1,36 31

Low 4,03 1,50 31

Sample 4 3,30 1,30 188

Women 3,30 1,30 104

High 3,51 1,22 51

Low 3,09 1,35 53

Men 3,30 1,31 84

High 3,34 1,22 32

Low 3,28 1,38 52

Sample 2 4,38 1,42 139

High 4,56 1,39 77

Women 4,61 1,42 46

Men 4,48 1,36 31

Low 4,15 1,44 62

Women 4,27 1,39 31

Men 4,03 1,50 31

Sample 4 3,30 1,30 188

High 3,44 1,22 83

Women 3,51 1,22 51

Men 3,34 1,22 32

Low 3,19 1,36 105

Women 3,09 1,35 53

Men 3,28 52

Mean Std Dev. N

Sample 2 4,40 1,51 139

Women

1,38

4,61 1,51 77

High 4,96 1,40 46

Low 4,10 1,54 31

Men 4,13 1,49 62

High 4,45 1,44 31

Low 3,81 1,50 31

Sample 4 3,78 1,45 188

Women 4,01 1,47 104

High 4,02 1,55 51

Low 3,99 1,41 53

Men 3,51 1,39 84

High 3,79 1,20 32

Low 3,33 1,47 52

Sample 2 4,40 1,51 139

High 4,75 1,43 77

Women 4,96 1,40 46

Men 4,45 1,44 31

Low 3,95 1,51 62

Women 4,10 1,54 31

Men 3,81 1,50 31

Sample 4 3,78 1,45 188

High 3,93 1,42 83

Women 4,02 1,55 51

Men 3,79 1,20 32

Low 3,66 1,47 105

Women 3,99 1,41 53

Men 3,33 52

Mean Std Dev. N

Sample 2 4,25 1,31 139

Women 4,42 1,34 77

High 4,56 1,15 46

Low 4,21 1,57 31

Men 4,04 1,24 62

High 4,32 1,21 31

Low 3,75 1,23 31

Sample 4 3,89 1,38 188

Women 3,66 1,45 104

High 3,98 1,33 51

Low 3,34 1,50 53

Men 4,18 1,25 84

High 4,51 1,20 32

Low 3,98 1,25 52

Sample 2 4,25 1,31 139

High 4,46 1,17 77

Women 4,56 1,15 46

Men 4,32 1,21 31

Low 3,98 1,42 62

Women 4,21 1,57 31

Men 3,75 1,23 31

Sample 4 3,89 1,38 188

High 4,19 1,30 83

Women 3,98 1,33 51

Men 4,51 1,20 32

Low 3,66 1,41 105

Women 3,34 1,50 53

Men 3,98 1,25 521,47

Source DF Type I SS Mean Square F Value Pr > F A 1 92.69128374 92.69128374 50.55 <.0001 B 1 0.63661562 0.63661562 0.35 0.5561 C 1 7.90802191 7.90802191 4.31 0.0386 A*B 1 1.07107631 1.07107631 0.58 0.4453 A*C 1 0.32112989 0.32112989 0.18 0.6759 B*C 1 0.47224507 0.47224507 0.26 0.6122 A*B*C 1 0.98320535 0.98320535 0.54 0.4645 Model 7 104.0835779 14.8690826 8.11 <.0001 Error 319 584.8940368 1.8335236 Total 326 688.9776147

Source DF Type I SS Mean Square F Value Pr > F A 1 10.12760994 10.12760994 5.85 0.0161 B 1 1.59998002 1.59998002 0.92 0.3371 C 1 22.45461998 22.45461998 12.97 0.0004 A*B 1 16.59412594 16.59412594 9.59 0.0021 A*C 1 0.36591400 0.36591400 0.21 0.6460 B*C 1 0.01127785 0.01127785 0.01 0.9357 A*B*C 1 0.56651036 0.56651036 0.33 0.5677 Model 7 51.7200381 7.3885769 4.27 0.0002 Error 319 552.1605735 1.7309109 Total 326 603.8806116

Source DF Type I SS Mean Square F Value Pr > F A 1 30.00042193 30.00042193 14.37 0.0002 B 1 19.70237936 19.70237936 9.43 0.0023 C 1 16.22030691 16.22030691 7.77 0.0056 A*B 1 0.00071645 0.00071645 0.00 0.9852 A*C 1 5.72117859 5.72117859 2.74 0.0989 B*C 1 0.43060970 0.43060970 0.21 0.6501 A*B*C 1 2.05853298 2.05853298 0.99 0.3215 Model 7 74.1341459 10.5905923 5.07 <.0001 Error 319 666.1692180 2.0883048 Total 326 740.3033639

52

Appendix 23 : Tables of means & ANOVA summary tables - Samples 1 and 3 - PI Benetton (left), PI Diesel (middle), and PI Sisley (right)

Mean Std Dev. N

Sample 3 2,14 1,14 182

Women 2,16 1,18 115

High 2,06 1,15 72

Low 2,33 1,22 43

Men 2,11 1,06 67

High 2,05 1,07 45

Low 2,23 1,07 22

Sample 1 3,15 1,43 155

Women 3,33 1,44 85

High 3,34 1,34 52

Low 3,31 1,61 33

Men 2,94 1,38 70

High 2,82 1,42 43

Low 3,13 1,33 27

Sample 3 2,14 1,14 182

High 2,06 1,12 117

Women 2,06 1,15 72

Men 2,05 1,07 45

Low 2,30 1,17 65

Women 2,33 1,22 43

Men 2,23 1,07 22

Sample 1 3,15 1,43 155

High 3,11 1,39 95

Women 3,34 1,34 52

Men 2,82 1,42 43

Low 3,23 1,48 60

Women 3,31 1,61 33

Men 3,13 1,33 27

Mean Std Dev. N

Sample 3 2,77 1,28 182

Women 2,71 1,23 115

High 2,76 1,17 72

Low 2,64 1,33 43

Men 2,87 1,37 67

High 2,78 1,38 45

Low 3,05 1,36 22

Sample 1 3,66 1,44 155

Women 3,54 1,43 85

High 3,56 1,50 52

Low 3,52 1,33 33

Men 3,79 1,46 70

High 3,92 1,49 43

Low 3,59 1,42 27

Sample 3 2,77 1,28 182

High 2,77 1,25 117

Women 2,76 1,17 72

Men 2,78 1,38 45

Low 2,78 1,34 65

Women 2,64 1,33 43

Men 3,05 1,36 22

Sample 1 3,66 1,44 155

High 3,72 1,50 95

Women 3,56 1,50 52

Men 3,92 1,49 43

Low 3,55 1,36 60

Women 3,52 1,33 33

Men 3,59 1,42 27

Mean Std Dev. N

Sample 3 2,42 1,31 182

Women 2,40 1,27 115

High 2,38 1,28 72

Low 2,43 1,26 43

Men 2,46 1,37 67

High 2,40 1,40 45

Low 2,58 1,35 22

Sample 1 2,78 1,33 155

Women 2,79 1,39 85

High 2,77 1,45 52

Low 2,83 1,30 33

Men 2,76 1,28 70

High 2,63 1,24 43

Low 2,97 1,33 27

Sample 3 2,42 1,31 182

High 2,39 1,32 117

Women 2,38 1,28 72

Men 2,40 1,40 45

Low 2,48 1,29 65

Women 2,43 1,26 43

Men 2,58 1,35 22

Sample 1 2,78 1,33 155

High 2,71 1,35 95

Women 2,77 1,45 52

Men 2,63 1,24 43

Low 2,89 1,30 60

Women 2,83 1,30 33

Men 2,97 1,33 27

Source DF Type I SS Mean Square F Value Pr > F A 1 85.69472226 85.69472226 52.50 <.0001 B 1 3.59965843 3.59965843 2.21 0.1385 C 1 2.54854991 2.54854991 1.56 0.2124 A*B 1 2.29671372 2.29671372 1.41 0.2364 A*C 1 0.25058042 0.25058042 0.15 0.6955 B*C 1 0.26554561 0.26554561 0.16 0.6870 A*B*C 1 0.86215423 0.86215423 0.53 0.4679 Model 7 95.5179246 13.6454178 8.36 <.0001 Error 329 537.0249834 1.6322948 Total 336 632.5429080

Source DF Type I SS Mean Square F Value Pr > F A 1 65.58598641 65.58598641 35.35 <.0001 B 1 3.21274621 3.21274621 1.73 0.1891 C 1 0.39893158 0.39893158 0.22 0.6432 A*B 1 0.18313569 0.18313569 0.10 0.7536 A*C 1 0.67989683 0.67989683 0.37 0.5454 B*C 1 0.04758049 0.04758049 0.03 0.8729 A*B*C 1 2.17722831 2.17722831 1.17 0.2795 Model 7 72.2855055 10.3265008 5.57 <.0001 Error 329 610.4230998 1.8553894 Total 336 682.7086053

Source DF Type I SS Mean Square F Value Pr > F A 1 10.61412478 10.61412478 6.02 0.0147 B 1 0.02651365 0.02651365 0.02 0.9025 C 1 1.52007282 1.52007282 0.86 0.3539 A*B 1 0.17578617 0.17578617 0.10 0.7524 A*C 1 0.15825936 0.15825936 0.09 0.7647 B*C 1 0.74347564 0.74347564 0.42 0.5166 A*B*C 1 0.09537179 0.09537179 0.05 0.8163 Model 7 13.3336042 1.9048006 1.08 0.3758 Error 329 580.2780278 1.7637630 Total 336 593.6116320

A = Sample B = Gender C = Product involvement

53

Appendix 24 : Tables of means & ANOVA summary tables - Samples 2 and 4 (due to missing values, only 327 observations can be used in these analyses) - PI Benetton (left), PI Diesel (middle), and PI Sisley (right)

Mean Std Dev. N

Sample 4 2,37 1,23 188

Women 2,34 1,24 104

High 2,47 1,28 51

Low 2,21 1,19 53

Men 2,42 1,22 84

High 2,28 1,20 32

Low 2,51 1,23 52

Sample 2 3,52 1,41 139

Women 3,58 1,48 77

High 3,73 1,49 46

Low 3,35 1,45 31

Men 3,45 1,34 62

High 3,46 1,44 31

Low 3,45 1,25 31

Sample 4 2,37 1,23 188

High 2,40 1,25 83

Women 2,47 1,28 51

Men 2,28 1,20 32

Low 2,36 1,21 105

Women 2,21 1,19 53

Men 2,51 1,23 52

Sample 2 3,52 1,41 139

High 3,62 1,47 77

Women 3,73 1,49 46

Men 3,46 1,44 31

Low 3,40 1,34 62

Women 3,35 1,45 31

Men 3,45 1,25 31

Mean Std Dev. N

Sample 4 2,82 1,26 188

Women 3,12 1,22 104

High 3,20 1,24 51

Low 3,04 1,21 53

Men 2,46 1,23 84

High 2,43 1,20 32

Low 2,48 1,25 52

Sample 2 3,45 1,52 139

Women 3,50 1,53 77

High 3,73 1,52 46

Low 3,15 1,51 31

Men 3,39 1,50 62

High 3,51 1,64 31

Low 3,27 1,36 31

Sample 4 2,82 1,26 188

High 2,90 1,28 83

Women 3,20 1,24 51

Men 2,43 1,20 32

Low 2,76 1,26 105

Women 3,04 1,21 53

Men 2,48 1,25 52

Sample 2 3,45 1,52 139

High 3,64 1,56 77

Women 3,73 1,52 46

Men 3,51 1,64 31

Low 3,21 1,43 62

Women 3,15 1,51 31

Men 3,27 1,36 31

Mean Std Dev. N

Sample 4 2,59 1,30 188

Women 2,68 1,31 104

High 2,93 1,37 51

Low 2,43 1,21 53

Men 2,48 1,28 84

High 2,68 1,35 32

Low 2,35 1,23 52

Sample 2 2,91 1,58 139

Women 3,03 1,55 77

High 3,07 1,57 46

Low 2,96 1,55 31

Men 2,77 1,61 62

High 3,17 1,79 31

Low 2,37 1,31 31

Sample 4 2,59 1,30 188

High 2,84 1,36 83

Women 2,93 1,37 51

Men 2,68 1,35 32

Low 2,39 1,21 105

Women 2,43 1,21 53

Men 2,35 1,23 52

Sample 2 2,91 1,58 139

High 3,11 1,65 77

Women 3,07 1,57 46

Men 3,17 1,79 31

Low 2,67 1,45 62

Women 2,96 1,55 31

Men 2,37 1,31 31

Source DF Type I SS Mean Square F Value Pr > F A 1 105.7486635 105.7486635 61.26 <.0001 B 1 0.0023728 0.0023728 0.00 0.9704 C 1 1.1149127 1.1149127 0.65 0.4222 A*B 1 0.8570122 0.8570122 0.50 0.4816 A*C 1 0.5292498 0.5292498 0.31 0.5802 B*C 1 3.7396470 3.7396470 2.17 0.1420 A*B*C 1 0.0937874 0.0937874 0.05 0.8158 Model 7 112.0856455 16.0122351 9.28 <.0001 Error 319 550.6416940 1.7261495 Total 326 662.7273394

Source DF Type I SS Mean Square F Value Pr > F A 1 31.26817882 31.26817882 16.99 <.0001 B 1 14.47253747 14.47253747 7.86 0.0054 C 1 3.84669988 3.84669988 2.09 0.1492 A*B 1 5.96034480 5.96034480 3.24 0.0729 A*C 1 2.41556441 2.41556441 1.31 0.2528 B*C 1 1.40428089 1.40428089 0.76 0.3830 A*B*C 1 0.06319683 0.06319683 0.03 0.8531 Model 7 59.4308031 8.4901147 4.61 <.0001 Error 319 587.0817351 1.8403816 Total 326 646.5125382

Source DF Type I SS Mean Square F Value Pr > F A 1 8.44075688 8.44075688 4.24 0.0402 B 1 4.04760764 4.04760764 2.04 0.1546 C 1 14.42356675 14.42356675 7.25 0.0075 A*B 1 0.06965326 0.06965326 0.04 0.8517 A*C 1 0.00134349 0.00134349 0.00 0.9793 B*C 1 0.75316458 0.75316458 0.38 0.5387 A*B*C 1 3.54141671 3.54141671 1.78 0.1830 Model 7 31.2775093 4.4682156 2.25 0.0304 Error 319 634.3418179 1.9885323 Total 326 665.6193272

A = Sample B = Gender C = Product involvement

54

55

Appendix 25 : Pearson correlation coefficients for Sample 1 and Prob > |r| under H0 : ρ=0

Aad Sisley

Abr Sisley

PI Sisley

Product involvement

Aad Sisley

00

1.000 0.60177<.

0. 810001

4576<.000

-0.018090.8232

Abr Sisley

0.60177<.0001

1.00000

0. 35444<.0001

0.047090.5607

PI Sisley

81

0.4576<.000

0.54443<.

1. 0 0001

0000 0.062690.4384

Product involvement

- 090.0180.8232

0.047090. 5607

0. 906260. 4384

1.00000

Ap Pearson l n coefficients ample d Pr | nder H0 : ρ=0

pendix 26 : corre atio for S 2 an ob > r| u

Aad Sisley

Abr Sisley

PI Sisley

Product involvement

Aad Sisley

1.00000

0.67022<.

0. 2< 1 0001 4533.000

0.34240<.0001

Abr Sisley

0.67022<.0001

1.00000

0. 76117<. 0001

0.319100.0001

PI Sisley

0.45332 <.0001

0.61177<.

1. 0 0001

0000 0.200830.0178

Product involvement

0.34240<.0001

0.319100.0001

0.200830 8 .017

1.00000

Appendix 27 : Pearson correlation coefficients for Sample 3 and Prob > |r| under H0 : ρ=0

Aad Sisley

Abr Sisley

PI Sisley

Product involvement

Aad Sisley

1.00000

0.83794<.00

4301 01 <.00

0.578 0.037690.6135

Abr Sisley

0.83794<.0001

1.00000

0.66771<.0001

-0.050670.4970

PI Sisley

0.57843<.0001

0.66771<.000

00 1

1.000 -0.013500.8564

Product involvement

0.037690.6135

-0.050670.4970

-0.013500. 64 85

1.00000

Aad Benetton

Abr Benetton

PI Benetton

Product involvement

Aad Benetton

1.00000

0.56 818<.

0 .00010001

0.5633<

0.052080.5198

Abr Benetton

0. 8 5681<.0001

1.0000 0

0.60958 <.0001

0.026460.7438

PI Benetto

0 n

0.5633<.0001

0.60958 <.0001

1.00000

0.030970.7021

Product involvement

0.05208 0.5198

0.02646 0.7438

0.03097 0.7021

1.00000

Aad Diesel

Abr Diesel

PI Diesel

Product involvement

Aad Di

1.00000 esel

0.45709 <.0001

0.4<.0

3891 001

0.093160.2489

Abr Diesel

0.45709<.0001

1.00000

0.64937 <.0001

0.104920.1939

PI Diesel

0.43891<.0001

0. 64937<.

1.000001

000

0.209440.0089

Product involvement

0.093160.2489

0. 104920.1939

0.20944 0.0089

1.00000

Aad Benetton

Abr Benetton

PI Benetton

Product involvement

Aad Benetton

0

1.0000 0.67949 <.0001

0.51159 <.0001

0.241930.0041

Abr Benetton

0.67949 <.0001

1.00000

0.69692 <.0001

0.129010.1301

PI Benetton

0. 9 1

5115<.000

0.6969 2<.

1.00000 0001

0.116710.1712

Product inv t olvemen

0.24193 0.0041

0.12901 0.1301

0.11671 0.1712

1.00000

Aad Diesel

Abr Diesel

PI Diesel

Product involvement

Aad Diesel

1.00000

0.70378 <.0001

0.53<.0001

455

0.36885<.0001

Abr Diesel

0.70378<.0001

1.00000

0.69385 <.0001

0.41286<.0001

PI Di

0.53455<.0001 esel

0. 5 6938<.0001

1.00000

0.288860.0006

Product involvement

0.36885<.0001

0.41286 <.0001

0.28886 0.0006

1.00000

Aad Benetton

Abr Benetton

PI Benetton

Product inv nt olveme

Aad Benetton

1.00000

0.73592 <.

58530000001 <.

0. 1 1

-0.095930.1976

Abr Benetton

0.73592 <.0001

1.00000

0.64573 <.0001

-0.114390.1241

PI Benetton

0.58531 <.0001

0.64573 <.

0000 0001

1. 0 -0.128810. 31 08

Product involvement

-0.09593 0.1976

-0.11439 0.1241

-0.12881 0.0831

1.00000

Aad Diesel

Abr Diesel

PI Diesel

Product involvement

Aad Diesel

1.00000

0.79751 <.0

74 01 001 <.00

0.645 -0.024730.7403

Abr Diesel

0.79751<.0001

1.00000

0.58973 <.0001

0.042590.5681

PI Diesel

0.64574<.0001

0.58973 <.00

00 01

1.000 0.053190.4758

Product involvement

-0.024730.7403

0.04259 0.5681

0.05319 0.4758

1.00000

Appendix 28 : Pearson correlation coefficients for Sample 4 and Prob > |r| under H0 : ρ=0

Aad Diesel

Abr Diesel

PI Diesel

Product involvement

Aad Diesel

1.00000

0.80394 <.0001

0.58415 <.0001

0.057110.4350

Abr Diesel

0.80394<.0001

1.00000

0.64190 <.0001

0.086170.2384

PI Diesel

0.58415<.0001

0.64190 <.0001

1.00000

0.032540.6567

Product involvement

0.057110.4350

0.08617 0.2384

0.03254 0.6567

1.00000

Aad Benetton

Abr Benetton

PI Benetton

Product involvement

Aad Benetton

1.00000

0.77155 <.0001

0.47173 <.0001

0.143100.0495

Abr Benetton

0.77155 <.0001

1.00000

0.55622 <.0001

0.130290.0739

PI Benetton

0.47173 <.0001

0.55622 <.0001

1.00000

0.011230.8781

Product involvement

0.14310 0.0495

0.13029 0.0739

0.01123 0.8781

1.00000

Aad Sisley

Abr Sisley

PI Sisley

Product involvement

Aad Sisley

1.00000

0.81731<.0001

0.59167<.0001

0.155310.0329

Abr Sisley

0.81731<.0001

1.00000

0.63059<.0001

0.162890.0251

PI Sisley

0.59167<.0001

0.63059<.0001

1.00000

0.161760.0262

Product involvement

0.155310.0329

0.162890.0251

0.161760.0262

1.00000

56