Cross-Cultural Sexism and the Effectiveness of Gender (Non)Traditional Advertising: A Comparison of Purchase Intentions in Poland, South Africa, and the United Kingdom
Magdalena J. Zawisza , Russell Luyt , Anna Zawadzka , Jacek Buczny
AbstractFindings regarding the effectiveness of (non)traditionally gendered advertisements are mixed and largely emanate from the United States. We tested the stereotype content model and ambivalent sexism theory cross-nationally in an advertising context and predicted that paternalistic (vs. envious) female stereotypes will trigger higher purchase intent (PI) irrespective of country (Hypothesis 1), viewers’ benevolent sexism will positively predict PI for paternalistic housewife advertisements (Hypothesis 2a), viewers’ hostile sexism will negatively predict PI for envious businesswoman advertisements (Hypothesis 2b), and these relationships with sexism will be confined to less gender egalitarian countries (i.e., Poland and South Africa) (Hypothesis 3). Statistical analyses of data from 468 Polish, South African, and British university students supported Hypothesis 1 and partially supported Hypotheses 2 and 3. The predicted patterns held for South Africa, but in Poland, viewers’ benevolence positively predicted PI for both advertisement types, with the exception of highly hostile women. British viewers’ hostility positively predicted PI for the housewife advertisement. Our findings support the cross-cultural applicability of the stereotype content model to advertising and suggest that the predictive role of sexism changes depending on its type, advertisement type, country, and gender. We recommend that advertisers should adopt a nuanced approach in predicting the effectiveness of gendered advertisements.
|Journal series||Sex Roles: A Journal of Research, ISSN 0360-0025, (A 30 pkt)|
|Publication size in sheets||0.65|
|Keywords in English||Advertising, Cross-cultural, Cross-national, Gender portrayal, Gender roles, Sexism, Stereotype content|
|ASJC Classification||; ;|
|Publication indicators||: 2016 = 1.387; : 2017 = 2.024 (2) - 2017=2.742 (5)|
|Citation count*||5 (2020-10-22)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.