The first goal of Study 3 is to further investigate the effects of female model ad sexualization on product attractiveness and purchase intentions. Specifically, we will investigate emotions as a possible underlying mechanism of women’s decreased responses toward sexualized female ads (see Hypothesis 3a, Prediction 3b, Hypothesis 4). Given that men’s product attractiveness and purchase intentions did not consistently vary depending on ad sexualization, no effects on their emotions were hypothesized.
A second goal of Study 3 is to further explore the role of the sociocultural milieu by testing hostile sexist attitudes toward women as a potential moderator of the relation between sexualization in advertising and consumers’ responses (see Hypothesis 5a and Hypothesis 5b). Although in Study 2 the gender attitudes that women are sexual objects and men are sex-driven produced no effects, we predicted that hostile sexism may function as a moderator. Indeed, although the two constructs may be related to each other, we reasoned that hostile sexism represents a construct different from gender attitudes (Chen et al. 2009; Glick and Fiske 1996).
In addition, previous research has shown that consumers’ purchase intentions may be positively affected by the congruency between the gender-relevance of the product and the level of sexualization of the ad (e.g., Black and Morton 2017; Simpson et al. 1996; see also Wirtz et al. 2018 for a meta-analysis). Gender-relevant products are those products that are congruent with gender stereotypes—for example, masculine-typed liquor (Grazer and Kessling 1995), and feminine-typed fragrances (LaTour 1990; Reichert et al. 2001). Therefore, for a more complete methodology we included both gender-relevant and gender-irrelevant products and explored whether gender relevance would modulate the results.
Method
Participants
Two-hundred and two participants (105 women, 97 men) recruited through advertisement in social networks voluntarily participated in the present study. Three male and one female participant were excluded because they did not sign the final consent, therefore the final sample included 198 participants: 104 (52.5%) women and 94 (47.5%) men. The sensitivity power analyses (α = .05, Power 1 - β = .80, n = 198) showed a minimal detectable effect (MDE) Cohen’s f = .20, which fell in the small effect area (Cohen 1988). Participants’ age ranged from 18 to 67 years-old (M = 32.11, SD = 12.11). Seventeen (8.6%) participants received middle school diploma, 101 (51.0%) high school diploma, 45 (22.7%) Bachelor Degree, 32 (16.2%) Master Degree and three (1.5%) Ph.D/Postgraduate Degree. The sample was mostly composed of heterosexual men and women (n = 175, 88.4%). Thirteen men and women (6.6%) declared to be gay or lesbian (7 women, 6 men), three bisexuals (1 woman, 2 men), one woman declared herself “queer” (2%), and five participants did not respond (3%). Please note that results did not change when non-heterosexual respondents were excluded from analyses.
Procedure, Materials, and Measures
The procedure was similar to Study 2. Unlike Study 2, the study was a 2 (participant gender) × 2 (condition: sexualized vs. neutral ads, between-subject variable) × 2 (product’s gender relevance: gender-relevant vs. gender-irrelevant product, within-subject variable) mixed design. As in Study 2 participants were randomly exposed to either six female sexualized ads or six neutral ads; however, among the six ads three included gender-relevant products (i.e., vodka, perfume, and beer) and three gender-irrelevant products (i.e., chewing gum, sneakers, and toilet paper), a classification based on previous literature (Grazer and Kessling 1995). Thus, new ads were pretested together with the ads used in Study 2 (see the Online Supplement). The presentation order of the gender-ir/relevant ads was randomized. After viewing each ad participants rated its product attractiveness and indicated their purchase intentions. To make the manipulation salient again all ads were presented again in a random order and participants rated their emotions. At the end, as in Study 2, participants filled out the moderator questionnaire (i.e., hostile sexism together with a filler scale on environmentalism).
Product Attractiveness and Purchase Intentions
Product attractiveness and purchase intentions were measured as in Study 2. Given that participants were presented with three gender-relevant products and three gender-irrelevant products, we calculated three indexes of product attractiveness (gender-relevant product attractiveness: α = .85; gender-irrelevant product attractiveness: α = .79; product attractiveness across all six ads: α = .89) and three of purchase intentions (gender-relevant purchase intentions: α = .92; gender-irrelevant purchase intentions: α = .90; purchase intentions across all six ads: α = .94). Note that participants’ habits and familiarity with the products were also measured but did not affect the results (see the Online Supplement).
Emotions
Participants were asked to indicate the extent to which they had experienced some specific emotions after viewing the ads on a scale from 1 (Not at all) to 7 (Very much). In line with previous studies measuring emotions (Albarello and Rubini 2012; Vaes et al. 2003), we measured eight positive emotions and nine negative emotions in mixed order (i.e., positive emotions: attraction, admiration, excitement, joy, pleasure, contentment, passion, and surprise, α = .91; negative emotions: annoyance, anger, rage, contempt, disappointment, disgust, fear, sadness, and agitation, α = .90).
Hostile Sexism
Participants completed the 11-item Hostile Sexism (HS) subscale of the Ambivalent Sexism Inventory (ASI, Glick and Fiske 1996), validated in Italian by Manganelli Rattazzi et al. (2008). Structural validity of the Italian version of ASI was supported by both exploratory and confirmatory factor analyses and reported internal consistency for Hostile Sexism was α = .87 (Manganelli Rattazzi et al. 2008). Participants provided their responses to the items (e.g., “Women seek to gain power by getting control over men”; α = .91) on a scale from 1 (Not at all likely) to 7 (Very likely). Scores were averaged across items such that higher scores indicate stronger endorsement of hostile sexism.
Results
Product attractiveness and purchase intentions
The overall mean on the product attractiveness index was M = 2.81 (SD = 1.16); the purchase intentions average was M = 2.59 (SD = 1.07). As in Study 1 and Study 2, we conducted a MANOVA on product attractiveness and purchase intentions with condition (sexualized vs. control) and participants’ gender (men vs. women) as between-subjects factors. The multivariate main effects of condition, Pillai’s trace = .13, F(2, 193) = 14.89, p < .001, ηp2 = .13, and gender, Pillai’s trace = .05, F(2, 193) = 5.22, p = .006, ηp2 = .05, as well as the Condition x Gender interaction, Pillai’s trace = .03, F(2, 193) = 3.41, p = .035, ηp2 = .03 were significant.
Concerning the univariate effects on product attractiveness, the main effect of gender, F(1, 194) = 8.42, p = .004, ηp2 = .04 (see Table 1 for descriptive statistics), was qualified by a significant Condition x Gender interaction F(1, 194) = 5.93, p = .016, ηp2 = .03. In line with Study 1, Study 2, and Hypothesis 1b, as shown in Table 1, women reported lower product attractiveness after exposure to sexualized than neutral ads (p = .002, Cohen’s d = .70). In line with Study 1 and contrary to Hypothesis 1a, men did not show different product attractiveness across conditions (p = .727). Moreover, men in the sexualized condition indicated higher product attractiveness compared to women in the same condition (p < .001, Cohen’s d = .68) whereas no gender difference was found in the control condition (p = .743).
Table 1 Descriptive statistics overall and by condition and participants’ gender for all dependent measures, study 3 Concerning the univariate effects on purchase intentions significant main effects of gender, F(1,194) = 4.71, p = .031, ηp2 = .02, and condition, F(1,194) = 13.51, p < .001, ηp2 = .06, were found (see Table 1 for descriptive statistics). Importantly, the interaction between condition and gender was significant, F(1,194) = 6.85, p = .010, ηp2 = .03. In line with Study 1 and Study 2, as shown in Table 1, men did not show different purchase intentions after exposure to sexualized or neutral ads (p = .466). In contrast, women showed lower purchase intentions in the sexualized than in the control condition (p < .001, Cohen’s d = 1.04). Moreover, in the sexualized condition men showed significantly higher purchase intentions than women (p = .001, Cohen’s d = .64), whereas the same comparison was not significant after exposure to neutral ads (p = .753).
To explore the effects of product gender-relevance, we conducted repeated measure ANOVAs separately on product attractiveness and purchase intentions including condition and gender as between subjects factors and gender-relevance of the product (gender-relevant, gender-irrelevant) as the within-subjects variable. Neither the main effects of gender-relevance, Fs(1, 194) < 2.55, ps > .112, ηp2s < .01, nor the three-way interactions with condition and gender, Fs(1, 194) < .35, ps > .552, ηp2s < .002, were statistically significant, whereas the other effects remained statistically significant (see the Online Supplement for additional results).
Emotions
The average negative emotions score was M = 2.19 (SD = 1.27); the positive emotions’ average was M = 2.08 (SD = 1.14). To test Hypothesis 3a and Prediction 3b, we conducted a MANOVA on negative and positive emotions with condition (sexualized vs. control) and participant gender (men vs. women) as between factors. The multivariate effects of condition, Pillai’s trace = .22, F(2, 193) = 27.60, p < .001, ηp2 = .22, gender, Pillai’s trace = .06, F(2, 193) = 6.39, p = .002, ηp2 = .06, and Condition x Gender, Pillai’s trace = .08, F(2, 193) = 8.80, p < .001, ηp2 = .08 were significant.
Concerning univariate effects, a main effect of gender emerged on both negative emotions, F(2,194) = 8.70, p = .004, ηp2 = .04, and positive emotions, F(2,194) = 7.47, p = .007, ηp2 = .04, and a significant main effect of condition was found only on negative emotions, F(1,194) = 51.46, p < .001, ηp2 = .19 (see Table 1 for descriptive statistics). Importantly, as predicted, both negative, F(1, 194) = 15.17, p < .001, ηp2 = .06, and positive, F(1, 194) = 6.49, p = .012, ηp2 = .03, emotions experienced by participants were affected by the interaction between condition and participants’ gender. Specifically, in line with Hypothesis 3a (see Table 1), women reported significantly more negative emotions after exposure to sexualized than neutral ads (p < .001, Cohen’s d = 1.50), and a similar pattern was observed for men (p = .025, Cohen’s d = .50). Moreover, in the sexualized condition women showed significantly more negative emotions than men, (p < .001, Cohen’s d = .76) whereas the comparison was not statistically significant for the control condition (p = .506). With reference to positive emotions and in line with Prediction 3b (see Table 1), both women’s and men’s levels of positive emotions did not differ across conditions (ps > .072). The only significant comparison is that women exposed to sexualized ads manifested lower positive emotions than men (p < .001, Cohen’s d = .69), whereas this difference was not significant in the control condition (p = .896). Please notice that the correlation between positive and negative emotions was r (97) = −.24, p = .018 for men, and r (105) = −.29, p = .003 for women.
Mediation by Emotions
To test Hypothesis 4, we computed an overall index of emotional negativity by subtracting responses on positive emotions from those on negative emotions, thus the higher the index the higher the level of negative emotions reported by participants. A moderated mediation analysis was performed through PROCESS (Model n° 8, Hayes 2013) on product attractiveness. The model included condition (control = 0, sexualized = 1) as the independent variable, emotional negativity (continuous, centered) as the mediator, and participants’ gender (men = 0, women = 1) as the moderator assessing its effects both on the mediator and on the dependent variable. The overall model was significant (R2 = .51), F(4, 193) = 49.91, p < .001. Importantly, in line with Hypothesis 4, a significant indirect negative effect of condition through emotional negativity emerged specifically for women (b = −.91, SE = .15, 95% CI [−1.21, −.63]) (with 5000 bootstrap samples). Specifically, sexualized (vs. neutral) ads increased women’s negative emotions, which in turn decreased their product attractiveness scores. This was not the case for men (b = −.04, SE = .16, 95% CI [−.35, .29]).
We conducted the same analysis on purchase intentions. The overall model was significant (R2 = .47), F(4, 193) = 42.23, p < .001. Supporting Hypothesis 4, the indirect effect of condition through emotional negativity was significant specifically for women (b = −.77, SE = .14, 95% CI [−1.06, −.51]) (with 5000 bootstrap samples). In other words, similar to product attractiveness, women reported lower purchase intentions after viewing sexualized ads than neutral ads because of their higher level of negative emotions. Again, this was not the case for men (b = −.03, SE = .14, 95% CI [−.31, .24]).
Moderation by Hostile Sexism
The overall mean on the hostile sexism index was M = 3.36 (SD = 1.21). Using PROCESS (Model n.3; Hayes 2013), we tested the moderating role of hostile sexism on both product attractiveness (Hypothesis 5a) and purchase intentions (Hypothesis 5b). Specifically, we entered condition (sexualized = 1, control = 0) as the independent variable, participants’ gender (women = 1, men = 0) as the first moderator and hostile sexism as the second moderator (continuous, centered). Concerning product attractiveness, although the overall model was statistically significant, F(7,190) = 5.26, p < .001, the model including the three-way interaction of Condition x Gender x Hostile sexism (b = −.48, t = −1.84, p = .067, 95% CI [−1.01, .03]) did not increase the amount of variance explained (ΔR2 = .01, R2 = .16, p = .067), thus not supporting Hypothesis 5a regarding the moderating role of hostile sexism on product attractiveness.
With respect to purchase intentions, analysis revealed a significant two-way interaction between condition and hostile sexism (b = .36, t = 2.02, p = .044, 95% CI [.01, .71]) qualified by a significant three-way interaction among Condition x Gender x Hostile sexism (b = −.53, t = −2.26, p = .025, 95% CI [−1.021, −.07]), which significantly increased the amount of variance explained (ΔR2 = .02, p = .025; overall model: R2 = .21, F(7, 190) = 7.13, p < .001). Supporting Hypothesis 5b, the higher men’s hostile sexism in the sexualized condition, the higher their purchase intentions (b = .45, SE = .13, t = 3.42, p = .001, 95% CI [.19, .70]). In contrast, hostile sexism was unrelated to purchase intentions for men in the control condition (b = .08, SE = .12, t = .68, p = .497, 95% CI [−.16, .33]) as well as for women in the sexualized condition (b = .13, SE = .10, t = 1.29, p = .198, 95% CI [−.07, .34]). Unexpectedly, the higher the hostile sexism the higher the purchase intentions also for women in the control condition (b = .31, SE = .12, t = 2.66, p = .008, 95% CI [08, .53]).
Discussion
In Study 3 women showed lower product attractiveness after exposure to sexualized female ads than neutral ads confirming Hypothesis 1b, whereas, contrary to Hypothesis 1a, men were unaffected by ads’ sexualization. This pattern of results replicated Study 1’s results as a whole and Study 2’s results for women. Interestingly, the same pattern was observed on purchase intentions, which fully replicated both Study 1’s and Study 2’s results. Moreover, contrary to Wirtz et al. (2018), the gender relevance of the product produced no effects. Therefore, this variable was not measured in the following study.
In addition, a series of important results were found on emotions. First, in line with Hypothesis 3a, women showed higher negative emotions after exposure to sexualized than neutral ads. Moreover, in line with Prediction 3b, women’s positive emotions did not differ across conditions. Second, the same pattern was found on men’s emotions. Most important, in line with Hypothesis 4, emotional negativity was shown to be the mechanism specifically underlying women’s decrement in product attractiveness and purchase intentions toward sexualized female models (vs. neutral) ads. Finally, consistent with Hypothesis 5b, an interesting result was that the higher the level of hostile sexism by men, the higher their purchase intentions after viewing sexualized than neutral ads.