Does it pay to break male gender stereotypes in advertising? A comparison of advertisement effectiveness between the United Kingdom, Poland and South Africa
Magdalena Zawisza , Russell Luyt , Anna Maria Zawadzka , Jacek Buczny
AbstractAdvertisers shy away from using non-traditional (vs. traditional) male gender portrayals even though theory suggests they may be more effective cross-nationally. Two main hypotheses were tested cross-nationally for the first time. H1: ‘paternalistic’ male stereotypes (e.g. Househusband) would be more effective than ‘envious’ male stereotypes (e.g. Businessman) across countries confirming the stereotype content model (SCM). H2: the match between initial male gender role attitudes and advertisement type would increase advertisement effectiveness only in countries with relatively low egalitarian norms (i.e. Poland and South Africa). A cross-national study was conducted through the use of student samples following a 3(country: United Kingdom, Poland and South Africa) × 2(advertisement type) × (gender attitude) mixed design (N = 373). A three-way multivariate analysis of variance showed support for H1 and partial support for H2 (i.e. the second hypothesis held on purchase intent and for South Africa). The study provides evidence for the cross-national applicability of the SCM to advertising and the limited predictive value of gender attitudes for purchase intent depending on country. Thus, contrary to mainstream advertising practices, breaking male gender stereotypes does appear to pay cross-nationally. Theoretical and practical implications alongside the potential for change in practices are discussed.
|Journal series||Journal of Gender Studies, ISSN 0958-9236, (A 25 pkt)|
|Publication size in sheets||0.8|
|Keywords in English||Advertising, gender attitudes, gender portrayal, gender stereotypes, sex roles, cross-cultural,|
|ASJC Classification||; ;|
|Publication indicators||: 2017 = 1.13; : 2017 = 0.918 (2) - 2017=1.193 (5)|
|Citation count*||6 (2020-09-29)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.