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Men’s and women’s implicit negativity towards obese fashion models
Halmstad University, School of Business, Innovation and Sustainability.ORCID iD: 0000-0002-0419-8654
2022 (English)In: Journal of Global Fashion Marketing, ISSN 2325-4483, Vol. 13, no 3, p. 273-288Article in journal (Refereed) Published
Abstract [en]

The purpose of this article is to investigate whether women’s relatively positive response to obese models is the result of social desirability bias on the part of women rather than deep seated attitudes. 60 university students in Sweden underwent an Implicit Associations Test (IAT) to reveal attitudes towards obese models that the participants were not able or willing to openly express. The study shows that even though women express significantly more positive attitudes towards obese models than men do, women and men display similar implicit negativity towards obese models. The study replicates a previously shown explicit gender effect, but also extends theory on gender preferences towards models of different sizes and body types by introducing measurements of implicit attitudes. Finally, the paper provides a possible explanation for why the fashion industry largely refrains from using obese models even though women express relatively positive attitudes towards them. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Place, publisher, year, edition, pages
Singapore: Taylor & Francis, 2022. Vol. 13, no 3, p. 273-288
Keywords [en]
Brands, IAT, obese, plus-size, user imagery
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hh:diva-46471DOI: 10.1080/20932685.2021.1977164ISI: 000727155700001Scopus ID: 2-s2.0-85121286152OAI: oai:DiVA.org:hh-46471DiVA, id: diva2:1644659
Available from: 2022-03-15 Created: 2022-03-15 Last updated: 2022-08-25Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf