Master thesis
The impact of disclosure presence and salience on women’s brand attitude and purchase intentions in the context of digitally-edited advertisements.
by Sarah LABELLE Student ID number: 11709960
Graduate School of Communication Master’s program of Communication Science
Name of the supervisor: Ivana BUŠLJETA BANKS
Date of completion: June 26th 2019
1 Abstract
Prior research has demonstrated various effects of exposure to digitally-edited advertising images on consumers’ overall product evaluations (e.g. Kahle & Homer, 1985; Till & Busler, 2000; Häfner & Tramp, 2009; Wright, 2016). However, as societal concerns grew regarding misleading advertising and exaggerated product claims, several countries started to
implement mandatory disclosure policies on digitally enhanced advertising. This paper investigates the impact of disclosure presence and salience in the context of
digitally-retouched advertisements on female consumer behaviour. A single factor experimental design testing 3 different disclosure levels (no disclosure vs. discreet disclosure vs. salient
disclosure) on brand attitude and purchase intentions was conducted. Perceived
advertisement honesty was hypothesized to moderate this relationship. The results of the analysis showed that disclosure presence and salience had no effect on women’s brand attitude and purchase intentions. Moreover, perceived ad honesty did not affect the relationship between disclosure presence or salience on the consumers’ response to advertisement. The implications for marketers and policy makers are further discussed.
2
Introduction
Beauty standards have substantially evolved over time. But in today’s Western society, the conception of beauty is usually bound intrinsically to women’s physical attractiveness, and especially women of younger age with thin silhouettes (Cook, 2017; Bovet, 2018; Schirmer, Schwaiger, Taylor & Costello, 2018). This stereotypical
representation of beauty has become increasingly present in the 21st century with the rise of the digital age and the extensive use of imagery by the media (Queen Victoria Women’s Centre Trust, 2008; Cook, 2017). The average western consumer is exposed to somewhere from 4 000 up to 10 000 advertisements per day (Marshall, 2015). Nowadays, models who appear in advertisement are highly attractive and convey an idealized physical beauty (Semaan, Kocher & Gould, 2018; Schirmer, et al., 2018). The visual bombardment doesn't stop here: in addition to advertisements, images found in the media (especially content that targets women) repetitively promote thinness as the ideal, and weight loss as the ultimate goal (Queen Victoria Women’s Centre Trust, 2008; Cook, 2017).
The beauty standards presented to today’s consumers are more unrealistic and unattainable than ever before (Queen Victoria Women’s Centre Trust, 2008). Due to the increased use of digital image-altering software such as Photoshop© or GIMP© , digitally-modified pictures have become the norm in our daily environment, from magazines to advertising, social media, and the internet in general (Borges, 2011; Queen Victoria
Women’s Centre Trust, 2008; Cook, 2017). Nowadays, both male and female models, on top of being highly attractive themselves, are frequently “photoshopped” to fit with our ideal representation of beauty (Borges, 2011; Schirmer, et al., 2018; Semaan, Kocher & Gould, 2018). Resorting to digital image-altering software is a common advertising tactic (Schirmer, et al., 2018). Today’s graphic designers are able to slim silhouettes, modify body proportions, alter skin texture and color, remove many details like wrinkles and blemishes through a series
3 of clicks on a computer software (Cook, 2017). The task of retouching commercial images has been pushed to such extreme that alterations appear seamless and nearly impossible to detect to an untrained eye, thus giving the consumers a hard time figuring out what is real and what is not (Queen Victoria Women’s Centre Trust, 2008; Cook, 2017).
However, this image editing trend isn’t risk-free: studies show that repetitive
portrayal of idealized models can expose the consumers to an array of negative consequences (Richins, 1991; Grabe, Ward & Hyde, 2008; Borges, 2011; Cook, 2017). The list of these detrimental effects is substantial, ranging from physical to mental illnesses. Indeed, research has linked the recurrent exposure to idealized images with unhappiness (i.e. moodiness, guilt, low self-esteem, decreased self-evaluation), decreased body satisfaction, eating disorders and unhealthy eating patterns (i.e. extreme dieting, binge eating, eating a restricted range of foods, excessive weight swings, anorexia nervosa), anxiety, self-destructive and obsessive behaviours, depression, and suicidal thoughts and behaviours (Richins 1991; Grabe, Ward & Hyde 2008; Borges 2011; Queen Victoria Women’s Centre Trust, 2008; Cook, 2017). This phenomenon can be understood in the light of the social comparison theory: according to Festinger (1954), the recurrent portrayal of idealized lifestyles, such as found in
advertisements or today’s media, leads people to explicitly or implicitly compare themselves with these ideals.
Moreover, digitally- modified images used to portray these ideals of beauty nowadays can be even more challenging because people who compare themselves to these pictures are not fully aware of the amount of alterations that has been made to achieve such results (Queen Victoria Women’s Centre Trust, 2008). In that sense, the visual bombardment of photoshopped images witnessed in today’s society is, indeed, problematic since the representation of such ideals can hardly be reached via natural or healthy means. Women, especially the younger generations, are more vulnerable to the detrimental effects caused by
4 the excessive use of digitally-edited images than men (Richins, 1991; Borges, 2011;
Schirmer, et al., 2018). This is so because female audiences are endlessly targeted by fashion-related advertisement, a sector which is known to often resort to image-altering software to produce content (Richins, 1991; Borges, 2011; Schirmer, et al., 2018). Although men are also affected by a recurrent exposure to digitally-edited male models in advertising (Borges, 2011), the present study will specifically focus on female models and the effects that
digitally-edited advertisement has on women; consequently the conclusions further drawn in this paper only apply to women.
Recently, the extensive use of digitally-altered advertisement has been strongly questioned and criticized by consumers, as well as some famous companies: pictures of models were mocked for their unnatural appearances and obvious alterations (Horwath, 2019). Getty Images recently decided to ban every image that shows models whose body have been altered in order to make them appear bigger or slimmer (Horwath, 2019). Moreover, companies like Dove and American Eagle Outfitters joined in the movement by adopting an explicit “body-positive” message in their ads, substantially reducing the use of digital editing software or cutting it out completely (Schirmer, et al., 2018; Horwath, 2019). The success of these campaigns proves that consumers can also appreciate advertising when it is less photoshopped, or even not at all (Horwath, 2019).
Together with public calls aiming to reduce digital alteratio ns in advertising, policy makers have also acknowledged the issue by implementing diverse regulations (Schirmer, et al., 2018). Indeed, several countries have passed laws restricting commercial photo editing, along with requiring disclosures in ads where the models have been retouched (Borges 2011; Schirmer, et al., 2018; Horwath, 2019). In France, for instance, digitally-altered images where a model's appearance has been manipulated now need to be marked with the label “photographie retouchée” (translated by “retouched photograph”) and failing to do so could
5 lead to a fine for the company (Borges, 2011; Horwath, 2019). This law targets any
photograph published in advertising, the media, on the internet, and in catalogues. A very similar law is also currently in place in Israel (Horwath, 2019). The United Kingdom and the United States also have implemented laws that aim to regulate or reduce excessively altered advertising images (Schirmer, et al., 2018; Horwath, 2019).
Given that governments around the world are currently implementing such laws to protect the people from being misled by advertisements (Schirmer, et al., 2018; Horwath, 2019), further investigation is needed on the topic of consumer response to photoshopped advertising images. At this point in time, little is known regarding the effects of warning labels used when the model has been digitally-altered for an ad. By exploring the use of these advertising disclosures, this study aims to explore solutions that could help people distance advertisement from reality, thus avoiding the detrimental effects brought by unrealistic beauty standards. Additionally, a gap of knowledge exists regarding how disclosure salience can influence the consumer’s response to advertisement. Therefore, this study aims to thoroughly investigate the impact of disclosure presence and salience on the consumer’s brand attitude and purchase intentions.
Theoretical framework
Social comparison theory & gender-based differences
In order to counteract the detrimental effects of repetitive exposure to digitally-edited advertisements, it seems important to first understand the mechanism underlying the social comparison process. As Festinger (1954) theorised, social comparison occurs when
individuals, consciously or unconsciously, regularly compare themselves to their peers, so that they can assess their own abilities and/or opinions. Social comparison can lead to polarized outcomes: either this comparison results in positive feelings and motivation to
6 improve oneself, or this comparison negatively impacts one’s self-esteem due to a great dissatisfaction with their current situation (Borges, 2011).
Advertising and the media have been found to play a substantial part in the process of social comparisons (Richins, 1991; Borges, 2011; Queen Victoria Women’s Centre Trust, 2008). Indeed, the idealized lifestyles portrayed in the media, or unattainable beauty standards showed in advertising alter the standards with which individuals compare themselves, thus resulting in decreased self-perceptions and satisfaction (Richins, 1991). Moreover, several studies highlight the influence of gender when it comes to assessing the negative
consequences of exposure to unrealistic beauty standards (Borges, 2011; Schirmer, et al., 2018). Several studies suggested that women (and especially young girls) were more vulnerable to the detrimental consequences brought by recurrent exposure to digitally enhanced advertisements in comparison to men (Richins, 1991; Borges, 2011; Schirmer, et al., 2018).
Marketing and advertising researchers have shown a great deal of concern regarding how gender differences affect consumer responses to advertising (Kempf, Palan & Laczniak, 1997). Studies show that males and females process information in advertisements differently (Darley & Smith, 1995; Kempf, Palan & Laczniak, 1997). These gender-based differences can be understood in the light of the “selectivity model” (Darley & Smith, 1995). According to this theory, female consumers are considered as comprehensive information processors: they take into account both subjective and objective product attributes while also
acknowledge subtle cues (Darley & Smith, 1995; Kempf, Palan, & Laczniak, 1997). On the other hand, male consumers are considered as selective information processors: they are more likely to use heuristics processing and tend to miss subtle cues (Darley & Smith, 1995; Kempf, Palan, & Laczniak, 1997). Additionally, gender-based differences were also investigated in the context of role model types. A study by Brown, Novick, Lord and
7 Richards (1992) suggests the existence of gender‐based differences regarding the type of media icons that consumers are most influenced by. Unlike men, women often look up to the idealized physical beauty conveyed by female fashion models (Richins, 1991). In response to all the arguments aforementioned, the present study will focus on advertisements targeting women and female consumer responses only.
Digitally-altered images in advertisement
Previous research investigating the use of digita lly-altered advertising images has produced mixed results: on the one hand, a great number of studies found the presence of either a correlation or a spillover effect of the model’s beauty on product evaluations (Kahle & Homer, 1985; Till & Busler, 2000; Häfner & Tramp, 2009; Weisbuch & Mackie, 2009; Wright, 2016). These findings imply that digitally-altered models who appear in
advertisements, because of increased aesthetics, have a greater positive impact on how the consumer perceives the product in comparison with editing- free advertisements. On the other hand, studies by Borges (2011) and Cornelis and Peter (2017) showed that consumers have more favourable attitudes toward advertisements labelled as retouch‐free than those labelled as retouched. Moreover, a growing number of brands are intentionally producing
advertisement were the models are left “unretouched”. In 2014 for instance, the American Eagle Outfitters lingerie sub-brand launched a retouch-free campaign called “Real Aerie”. This brand initiative was very successful: in the following year, Aerie’s sales went up 20% (Horwath, 2019). Similarly, Dove’s Real Beauty campaign launched in 2004 was also a success after the brand adopted a body positivity message in their ads (Schirmer, et al., 2018; Horwath, 2019). This tendency to reduce photo editing of the models in advertising seems to resonate with the consumers who are looking for more realistic beauty standards and “next-door” models.
8 A potential explanation to the mixed results found in literature may lie in the presence or absence of a disclosure. Indeed, little attention has been given to disclosures in the context of digitally-edited advertisements and how they may affect brand attitude and purchase intentions. To our knowledge, no research investigating the format of these disclosures and how it could also affect brand attitude and purchase intentions has yet been found.
Disclosures
According to the definition of advertising disclosures by Hoy and Andrews (2004), a disclosure comes in the form of labels or visual cues and is generally intended to provide information that prevents consumers from being deceived, thus allowing them to make more informed decisions. In the case of digitally enhanced advertisement, a disclosure indicates that the model’s appearance might not be exactly like it is shown in the ad (Schirmer, et al., 2018). The purpose of a disclosure is to “remind the consumer that the model has been digitally enhanced and thus highlights potentially exaggerated advertising claims” (Schirmer, et al., 2018, p. 133). Any additional piece of information that helps the consumer distance the commercial content from reality can fit the definition of a disclosure.
Previous studies have focused on the effects of disclosures regarding sponsor content, product placement, and native advertisements (Boerman, Van Reijmersdal & Neijens, 2013; Wojdynski & Evans, 2016). Recently, several countries passed laws aiming to reduce or restrict photo editing in response to several studies linking the repetitive exposure to idealized models with severe repercussions on the consumer’s mental and physical health (Richins 1991; Grabe, Ward & Hyde 2008; Borges 2011; Horwath, 2019). Mandatory disclosure policies have emerged in the last years to counteract the detrimental effects of retouched advertisements. However, research on the topic of disclosure effects in advertising appears rather inconclusive due to mixed results. Authors Semaan, Kocher, and Gould (2018)
9 demonstrated that disclosure presence in the context of retouched advertisements led to more favourable brand attitude, but these findings are in contrast with the majority of studies which examined the effects of disclosures. Studies by Boerman, Van Reijmersdal, and Neijens (2013), Wojdynski and Evans (2016), as well as Schirmer, et al. (2018) all have consistent findings. According to these studies, disclosure presence leads to greater negative brand attitude and weaker purchase intentions.
Besides the contradicting findings aforementioned, very little is known about the role played by disclosure characteristics and how these characteristics might also affect the consumer’s brand attitude and purchase intentions. To our knowledge, no law has yet
codified the format under which these mandatory disclosures should appear. When observing how disclosures are formatted in existing digitally-edited advertisements, they tend to be rather discreet: usually placed at the bottom corner of the ad, written in a very small- font text, of neutral colour to seamlessly blend in with the advertisement (see examples in Appendix D). Unsurprisingly, several studies investigating disclosures in various contexts found that disclosures went often unnoticed by the participants (Boerman, Van Reijmersdal & Neijens, 2012; Wojdynski & Evans, 2016; Boerman, Willemsen & Van Der Aa, 2017). If disclosures aim to help consumers make sound decisions, it seems legitimate that such disclosures should be made salient enough to be noticed by the consumers. Perhaps certain criteria and standards in terms of disclosure font size, position on the ad, and text and background colour, among other characteristics, could ensure a disclosure’s noticeability and, therefore, effectiveness. In response to this problem, the present paper aims to investigate the effect of disclosures in the context of digitally-edited advertising images, and, more precisely, how disclosure presence and salience can affect brand attitude and purchase intentions.
10 Brand attitude & purchase intentions
Brand attitude and purchase intentions are standard concepts that have been recurrently used in academic research and reports in the field of marketing and advertising (Spears & Singh, 2004). Spears & Singh (2004) defined the concept of brand attitude by merging former definitions as: “a relatively enduring, unidimensional summary evaluation of the brand that presumably energizes behavior” (Spears & Singh, 2004, p. 55). The same authors also defined the concept of purchase intentions. According to Spears and Singh (2004), purchase intentions are comprised of: “an individual’s conscious plan to make an effort to purchase a brand or a product” (Spears & Singh, 2004, p. 56).
Brand attitude and purchase intentions are often investigated as a pair. Studies show that the two concepts are correlated in such way that higher brand attitude usually lead to increased purchase intentions (Mitchell & Olson, 1981; Batra & Ray, 1986; Spears & Singh, 2004). However, in the context of context of digitally- modified advertisement and
disclosures, papers measuring brand attitude and purchase intentions produced inconsistent findings. A study by Schirmer, et al., (2018) for example found that when exposed to an ad accompanied by a disclosure, consumers had significantly greater purchase intentions, but weaker brand attitude, and when exposed to an ad without disclosure, consumers had greater brand attitude but lower purchase intentions. Interestingly, the Schirmer, et al., (2018) study does not support any correlation between brand attitude and purchase intentions which has been suggested by previous authors Mitchell and Olson (1981), Batra and Ray (1986), and Spears and Singh (2004).
With respect to purchase intentions alone, a study conducted by Borges (2011) supported opposite findings: in this paper, consumers who were exposed to disclosed ads had significantly lower purchase intentions than those who were exposed to disclose-free ads.
11 Regarding brand attitude alone, Semaan, Kocher and Gould (2018) suggests disclosure
presence led to higher, more positive brand attitude whereas Boerman, Van Reijmersdal and Neijens (2013), Wojdynski and Evans (2016) and Schirmer, et al., (2018) all have findings supporting the opposite, that disclosure presence leads to weaker brand attitude.
In response to the different findings aforementioned, the present paper intends to further explore the relationship between brand attitude and purchase intentions in the context of digitally-enhanced advertisements. To our knowledge, no study has yet investigated the effects of disclosure presence together with salience on brand attitude together with purchase intentions. In response to this gap in the literature, this current study will investigate the relationship between disclosure presence and salience, brand attitude and purchase intentions all together. Our first hypotheses are as follows:
H1: Exposure to a digitally-edited advertisement containing a salient disclosure will lead to (a) lower brand attitude and (b) lower purchase intentions than exposure to a digitally-edited advertisement containing a discrete disclosure or no disclosure.
H2: Exposure to a digitally-edited advertisement containing a discreet disclosure will lead to (a) lower brand attitude and (b) lower purchase intentions than exposure to a digitally-edited advertisement containing no disclosure.
Perceived advertisement honesty
The concept of perceived advertisement honesty has hardly been investigated until recently, and even less so in the context of digitally enhanced images and photoshop
disclosures. According to authors Frenkel and Lurie (2001) perceived advertisement honesty can be defined as whether consumers sense that the advertisement provides accurate
12 information and full disclosure of facts. In the case of photoshopped advertising images, it seems logical that a disclosure stating that digital alterations have been made on the advertisement would increase how honest the ad is perceived to be by the consumer, and supposedly have an influence on the consumer’s behaviour.
Regarding empirical findings, previous research on the topic of perceived ad honesty in the context of digitally enhanced images is scarce. Nevertheless, several papers suggest that perceived advertisement honesty influences brand attitude (Semaan, Kocher & Gould, 2018), overall brand evaluations (Pechmann, 1992) and purchase intentions (Schirmer, et al., 2018). Moreover, comparable findings were identified in different studies investigating similar concepts such as ad skepticism, source credibility, and advertising truthfulness (Aguirre, Mahr, Grewal, de Ruyter & Wetzels, 2015; Zarouali, Ponnet, Walrave & Poels, 2017). To our knowledge however, no study has yet investigated the concept of perceived ad honesty
together with digital image alteration disclosures. Based on previous findings, our last hypothesis is as follows:
H3: Perceived ad honesty will moderate the effects of disclosure presence and
salience on brand attitude and purchase intentions in a way that the higher the level of perceived ad honesty, the higher the levels of (a) brand attitude and (b) purchase intentions.
Lastly, the present paper aims to test different levels of disclosure salience to best grasp how disclosures can affect brand attitude and purchase intentions. Since the concept of perceived ad honesty was not thoroughly investigated in the previous literature, this paper also aims to answer the following complementary research question: to what extent does perceived ad honesty influence brand attitude and purchase intentions in the context of
13 digitally-edited advertisement, and more precisely how can different levels of disclosure salience affect this relationship?
A conceptual model summarizing the all the above can be found below:
Figure 1 - Conceptual model
Methods
Research design
This paper aims to investigate the effect of disclosures in the context of digitally-edited advertising images, and more precisely how disclosure presence and salience can affect brand attitude and purchase intentions. In order to test our hypotheses, a single-factor between-subjects experiment was conducted. The experiment was administered by the means of an online survey (i.e. Qualtrics). All participants were randomly assigned to view one of the three conditions (no disclosure, discrete disclosure, or salient disclosure). After exposure to the stimuli, the participants proceeded to complete the questions regarding perceived ad honesty, purchase intentions, brand attitude as well as demographics.
14 Stimulus material
For this research, a mock advertisement involving a fictitious brand of cosmetic called “ABCosmetics” was created (see Appendix A). The mock ad displayed the picture of a female model next to a cosmetic product, a red lipstick, and was accompanied by the simple description: “The ultimate red for irresistible lips”. No further product information or claim was made available in the mock ad. The model’s face, hair and body had been substantially altered through a digital altering image software. The brand logo and description were created from scratch, but the model and product pictures were designed by “benzoix” and obtained from an online image bank, Freepik (www.freepik.com).
The disclosure that appeared in the mock ad was inspired by different versions of existing disclosed ads (see Appendix D). Disclosure salience was manipulated through the use of different typographies, font sizes, frames and colours: the discreet disclosure appeared in a smaller-font, discrete colour and italicized wording whereas the salient disclosure
appeared in larger, bolder font and was framed in red. Disclosure wording and positioning remained constant across conditions, simply stating: “this image has been digitally edited” and was placed at the bottom left of the ad.
A pretest regarding disclosure salience was conducted beforehand to ensure that the disclosures differed sufficiently, meaning each one was either perceived as discreet or noticeable. Another pretest assesing brand familiarity was also conducted to make sure that mock brand was not taken for an existing brand (see Appendix B).
Participants
A total of 162 participants took part in this experiment. Participants were recruited by the researcher through personal email invitations, WhatsApp messages, Facebook messages, and Facebook survey exchange groups. However, 38 participants were excluded from the
15 analysis because they didn't fulfil the basic requirements (i.e. underage, male respondents, speeders or those who did not finish). The valid number of respondents was N=124.
In response to the arguments mentioned in the theoretical framework regarding
gender-based differences, all respondents recruited for this study were female. The age of the participants ranged from 18 to 72 years old (M = 29.77; SD = 12.57). Participants varied in level of education (8.1% high school degree; 12.1% professional degree, 35.5% bachelor degree, 41.9% master degree and 2.4% doctorates) and occupation (49.2% were students, 11.3% worked part-time, 33.5% worked full-time, 1.6% unemployed and 2.4% retired).
Dependent variables
Participants rated how honest they perceived the ad to be (i.e. perceived ad honesty) using a 7‐point scale anchored at “dishonest”/ “honest”, “insincere”/ “sincere”, and
“unethical”/ “ethical” (Semaan, Kocher & Gould, 2018; Cronbach’s α = .72).
Attitude towards the brand (i.e. brand attitude) were measured using a 7-point scale with endpoints labelled “good”/ “bad”, “pleasant”/ “unpleasant”, “unfavorable”/ “favorable”, “unlikeable”/ “likeable” (Spears & Singh, 2004; Cronbach’s α = .93).
Self-prediction purchase intent (i.e. purchase intentions) was measured using a 7-point single-item scale with endpoints labelled “definitely would buy”/ “definitely would not buy”. (Batra & Ray, 1986). All scales are available in Appendix C and a summary can be found further down in Table 1.
Procedure
The participants could take part in the study by clicking on a link sent through personal invitations via email and social media. After providing informed consent, participants were randomly assigned to one of the three disclosure conditions featuring a
16 version of the mock advertisement. Brief instructions were given prior to exposure to the stimuli: the participants were told they were about to see a cosmetic product advertisement and they should pay attention to this ad as they would normally do if they came across it in a magazine. After exposure to the stimuli, the participants could proceed to fill- in the section containing the dependent measures, namely perceived ad honesty, brand attitude, and purchase intentions and the demographic section. Once those measures were completed, participants were provided with a debriefing text regarding the present study and its purpose.
Result section
Pretest - Testing disclosure salience
For the present study, a pretest was conducted to check the perceived salience of each disclosure which appeared in the mock ads. A total number of 15 participants took part in this pretest (n = 15). Participants who were exposed to the discreet disclosure condition rated the disclosure as less obvious/noticeable (M = 1.67 ; SD = 1.05) in comparison to the participants who were exposed to the salient disclosure condition who rated the disclosure as more obvious/noticeable (M = 5.13 ; SD = 1.19). The paired sample t-test for this mean differences was highly significant: t(14)= -8.18 ; p <.001 ; 95% CI [-4.38 ; -2.56], meaning the
manipulation was successful.
Additionally, participants who were exposed to the salient disclosure condition rated the disclosure as more obvious/noticeable (M = 5.80 ; SD =1.74) in comparison to the
participants who were exposed to the discreet disclosure condition who rated the disclosure as less obvious/noticeable (M = 2.60 ; SD = 1.18 ). The paired sample t-test for this second mean differences was also highly significant: t(14)= 5.78 ; p <.001 ; 95% CI [2.01 ; 3.39], meaning the manipulation was perceived as intended in both ways.
17 Testing brand familiarity
Another pretest was conducted to asses brand familiarity in the mock ad. A total number of 15 participants took part in this pretest (n = 15). A frequencies analysis was conducted on the variable to test possible brand familiarity. The results showed that a few respondents said they were familiar with the made-up brand (n = 2 or 13.3% of the respondents), however, the vast majority confirmed they were not familiar with
ABCosmestics (n = 13 or 86.7% of the respondents). Therefore, further conclusion drawn in this paper shall not be biased with brand familiarity.
Randomization checks
Randomization check for age
The first randomization check entailed the disclosure conditions as the independent variable and age as the dependent variable to see whether age was comparable over the 3 conditions. To do so, a one-way ANOVA was conducted. The results of the Levene’s test showed no significance (peducation = .607; page = .225), therefore the assumption of equal variance was met. Hence, the randomization of participants across conditions was successful for age.
Randomization check for education
The second randomization check entailed the disclosure conditions as the independent variable and education as the dependent variable to see whether education was comparable over the 3 conditions. The ANOVA analysis was not significant: Feducation(2 ; 123) = 2.79 and peducation = .065; Fage(2 ; 123) = 1.35 and page = .264. Hence, the randomization of participants across conditions was successful for education.
18 Randomization check for occupation
The third randomization check entailed the disclosure conditions as the independent variable and occupation as the dependent variable to see whether occupation was comparable over the 3 conditions. To do so, a crosstabulation and a chi-square test were conducted. The results showed that the variables were not associated: X2 = 3.98 and p = .859, which is above our critical value of .05. Hence, the randomization of participants across conditions was successful for occupation.
Scales
Perceived advertisement honesty
In this study, a pre-existing scale was used to measure the concept of perceived advertisement honesty. A principal axis factor analysis with all 3 items was conducted. The KMO measure of sampling adequacy was .65 which is higher than the required .50 score. In addition, Bartlett’s test of sphericity was statistically significant (<.001). The factor solution included 1 component with an Eigenvalues of 1.93. This component alone explained 64.28% of the variance in the 3 included items. The reliability analysis for the perceived
advertisement honesty scale including the 3 items resulted in a Cronbach’s alpha level of .72. Brand Attitude
Another pre-existing scale was used to measure the concept of brand attitude in this study. A principal axis factor analysis with all 4 items was conducted. The KMO measure of sampling adequacy was .83 which is higher than the required .50 score. In addition, Bartlett’s test of sphericity was statistically significant (<.001). The factor solution included 1
component with an Eigenvalues of 3.29. This component alone explained 82.25% of the variance in the 4 included items. The reliability analysis for the brand attitude scale including the 4 items resulted in a Cronbach's alpha level of .93.
19 A summary of all the results aforementioned can be found in the table bellow:
Table 1 - Scale summary
Variable Scale reference Items Eigen value Cronbach’s α
Perceived
Advertisement Honesty
Semaan, Kocher & Gould (2018)
3 1.93 .72
Brand Attitude Spears & Singh (2004) 4 3.29 .93
Purchase Intentions Batra & Ray (1986) 1 - -
Hypotheses testing
Our first hypothesis (H1) was that exposure to an edited-image advertisement containing a salient disclosure led to (a) lower brand attitude and (b) lower purchase
intentions than exposure to an edited-image advertisement containing a discrete disclosure or no disclosure. Our second hypothesis (H2) was that exposure to an edited-image
advertisement containing a discreet disclosure led to (a) lower brand attitude and (b) lower purchase intentions than exposure to an edited-image advertisement containing no disclosure. To test all parts of both H1 and H2 a one-way multivariate analysis of variance (MANOVA) was conducted.
The results showed that the MANOVA model as a whole was significant: Pillais’ Trace = .91, F(2, 120) = 610.56, p < .001. The effect size for brand attitude was estimated at -.011, which implies that 1.1% of the variance in brand attitude can be attributed to disclosure type. The Levene’s test shows an F-value of .22 and p = .804 which is not significant,
therefore homogeneity of variances was assumed. Additionally, the effect size for purchase intentions was estimated at -.016, which implies that only 1.6% of the variance in purchase intentions can be attributed to disclosure type. Moreover, the Levene’s test shows an F-value of .18 and p = .832 which is not significant, therefore homogeneity of variances was
20 intentions based on disclosure type: FBA(2)= .3 with p = .739 FPI(2) <.04 with p = .963. Therefore, both H1ab and H2ab were rejected.
Our third hypothesis (H3) was that perceived advertisement honesty moderated the effects of disclosure presence and salience on brand attitude and purchase intentions in a way that the more people perceived the advertisement to be honest, the greater (a) the brand attitude and (b). the greater the purchase intentions. To test each part of this last hypothesis, two moderated bootstrapping procedure in PROCESS SPSS (Model 1; 1,000 bootstraps; Hayes, 2018) were conducted.
The results for H3a showed that the model as a whole was significant: F(5 ; 118) = 11.04 and p < .001 with R2 = .319. The coefficient of determination indicates that this model explains 31.9% of the variance in the dependent variable, namely brand attitude. Furthermore, the coefficient for perceived ad honesty as an independent variable was significant: b* = .78, SE = .19 with 95% CI [.4 ; 1.17] and p < .001. This means that each point increase in perceived advertisement honesty corresponds to a 0.78-point increase in brand attitude. However, the interactions between perceived ad honesty and disclosure presence and salience were not significant. The results for the interaction between the discreet disclosure and perceived ad honesty were not significant: b*=-.45, SE = .26 with 95% CI [-.95; .06] and p =.083 ; nor were the results for the interaction between the salient disclosure and the moderator: b*=-.11, SE = .23 with 95% CI [-.56; .34] and p =.627. Therefore, H3a was rejected.
Regarding H3b, the results showed that the model as a whole was significant: F(5 ; 118) = 5.20 and p < .001 with R2 = .181. The coefficient of determination indicates that this model explains 18.1% of the variance in the dependent variable, namely purchase intentions. Furthermore, the coefficient for perceived ad honesty as an independent variable was
21 point increase in perceived advertisement honesty corresponds a 0.6-point increase in
purchase intentions. However, the general interactions between perceived ad honesty and disclosure presence and salience were not significant. The results for the interaction between the discreet disclosure and the moderator (e.g. perceived ad honesty) were not significant: b*=.02, SE = .35 with 95% CI [-.71; .67] and p =.956 ; nor were the results for the interaction between the salient disclosure and the moderator: b*=.02, SE = .31 with 95% CI [-.63; .59] and p =.956. Therefore, H3b was rejected too.
A table summarizing the results corresponding to all three hypotheses can be found below:
Table 2 – Summary of results
Hypotheses Conducted analysis Supported
H1a MANOVA x
H1b MANOVA x
H2a MANOVA x
H2b MANOVA x
H3a PROCESS model 1 x
H3b PROCESS model 1 x
Conclusion
The present study investigates the relationship between disclosure presence and salience and consumer’s brand attitude and purchase intentions in the context of digitally-edited advertisement. In addition, this work investigated the moderation effect of perceived advertisement honesty on this relationship. The results revealed no statistical significance in any of the main or interaction effects. Our results seem to add to the pre-existing confusion in the literature on digitally enhanced advertising images. Previous studies had inconsistent findings regarding disclosure’s impact on consumer’s brand attitude and purchase intentions (e.g. Borges, 2011; Boerman, Van Reijmersdal & Neijens, 2013; Wojdynski & Evans, 2016; Schirmer, et al., 2018; Semaan, Kocher & Gould, 2018). However, all these publications
22 supported the presence of some effect brought by disclosures on digitally-edited advertising images: the present paper’s findings suggest otherwise, namely that disclosure presence or salience has no effect on brand attitude or purchase intentions.
The world of academic publications is ruled by the quest for significance, therefore many papers which suggest the absence of an effect (i.e. no significance) are usually not published. Such a system entails that several important findings ever get any attention and that the scientific community loses a lot of the nuances present in the real world. In that sense, the current paper’s findings cannot be compared with similar findings from previous articles since such articles aren’t usually kept by academic journals. Nevertheless, our results are still relevant to the scientific community in the way that they point to the absence of an effect that was recurrently argued to be present.
Implications for researchers and policy makers
It appears that women’s attitudes regarding advertising are changing: reducing digital image editing and retouch-free advertisements have considerably gained popularity in the recent years (Borges, 2011; Cornelis & Peter, 2017; Schirmer, et al., 2018; Horwath, 2019). While female consumers are calling for more realistic beauty standards and “next-door” models, policy makers echoe this call by demanding more transparency regarding the advertising claims and marketing techniques (Borges 2011; Schirmer, et al., 2018; Horwath, 2019). For many policy makers, transparency can come in the form of a digital image editing disclosure accompanying branded advertisements. Although the hypotheses were not
supported, our results were not inconclusive: this paper shows that disclosure presence and salience do not significantly impact consumers’ brand attitude and purchase intentions. For marketers, this means that providing disclosures in advertising as an effort to appear more transparent to the consumers doesn’t impact sales or consumer’s attitude, unlike several
23 authors previously suggested (Borges, 2011; Boerman, Van Reijmersdal & Neijens, 2013; Wojdynski & Evans, 2016; Schirmer, et al., 2018; Semaan, Kocher & Gould, 2018). In today’s highly competitive market, brands should not fear encountering severe financial risk by applying regulations regarding advertisement disclosures. In conclusion, the current paper’s findings encourage the use of photoshop disclosures since doing so will not have a negative effect on consumer’s brand attitude or purchase intentions.
Limitations
The conclusions drawn from this paper must be taken carefully, this is so because this study includes several limitations. First, the experimental design chosen for this study
comprises some weaknesses by nature: an unnatural setting such as surveys combined with made-up advertisement could’ve exposed the participants to react differently from what they would normally do, for instance if they came across a real-life advertisement in a magazine. Though precautions were taken in the survey instructions, by pretending the branded ad was real and asking the participants to answer honestly, these two elements (i.e. artificial setting and created ad) could’ve have distorted the results of this paper. Further research should prioritize natural settings and real-life branded advertisement to increase ecological validity.
Regarding the participants who took part in this experiment, this study mainly resorted to personal contacts and Facebook groups as a convenience sampling strategy. This strategy can be considered as a considerable bias because it is not representative of the general population. For instance, the demographical section of this paper clearly shows a sample with a majority of students and people with higher education, which is not the case in the general population. Moreover, only females were included in the analysis of this paper, meaning the results can only apply to women. Further research should prioritize other
24 Moreover, the product type tested in this experiment is a limitation by itself: cosmetic products are high-involvement products, which means that the consumer’s decision process is more complex than that of low-involvement products. In the case of lipsticks, not being able to try or touch the product for example may have had an influence on purchase decisions and overall attitudes. Moreover, though makeup is relatively popular, it is not a standard in women’s habits: the female participants who took part in this study are very likely to have different attitudes towards lipstick and makeup products in general. Because of these reasons, choosing lipstick as a product to advertise in this study came at the cost of the findings of this paper being hardly generalizable to other products. Replicating this type of study to other products is therefore needed.
During the analysis of the current paper’s data, a weakness regarding group sizes was identified. Though each experimental condition had more than 30 respondents, the analysis comparing the disclosure conditions to the no-disclosure condition was heavily ill-balanced. Indeed, the results for H1a & H1b hypotheses were based on very different group sizes: the disclosure- free condition had a total of 33 participants whereas the disclosure condition had 90 participants in total. This substantial difference in group sizes may have affected the results of this study, further research shouldn’t neglect such factor.
Other elements which were not tested in this study comprised disclosure wording and graphic logos. Indeed, a paper by Wojdynski and Evans (2016) suggests that words like “advertising” or “sponsored” when used in a disclosure can increase advertising recognition and decrease advertising evaluations. Furthermore, a paper by Borges (2011) indicates that graphic warning regarding digital editing reduces the negative effects of a
computer-enhanced images on young girls’ self-esteem. Therefore, further research in the field investigating disclosures should also take into consideration these two parameters.
25
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Appendices
Appendix A – Stimuli
- No disclosure condition
29 - Salient disclosure condition
Appendix B – Pretest
Question (+ stimuli per set of questions):
“To what extent do you agree or disagree with the following statements:” - The disclosure message is very obvious/noticeable?
- The disclosure message is very discreet/hardly noticeable? - I am familiar with the brand mentioned in this ad?
(Participants answered using a 7-point Likert scale: “strongly disagree/disagree/somewhat disagree/neutral/somewhat agree/agree/strongly agree”)
Appendix C – Scales
1. Perceived ad honesty Question:
“Please describe your overall feelings about the ad you just saw” Endpoints:
“dishonest” / “honest” “insincere” / “sincere” “unethical” / “ethical”
30 2. Brand attitude
Question:
“Please describe your overall feelings about the brand featured in the ad you just saw” Endpoints:
“good” / “bad”
“pleasant” / “unpleasant” “unfavorable” / “favorable” “unlikeable” / “likeable”
(Respondents must answer using a 7-point scale)
3. Purchase intention Question:
“How likely is it that you would consider purchasing the product featured in the ad you just saw?”
Endpoints:
“Definitely would buy” / “definitely would not buy” (Respondents must answer using a 7-point scale)
