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Cited by 375

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Predictive Validity of the Implicit Association Test in Studies of Brands, Consumer Attitudes, and Behavior

Maison, Dominika, Greenwald, Anthony G., Bruin, Ralph H.·2004·Journal of Consumer Psychology

Abstract

Three studies investigated implicit brand attitudes and their relation to explicit attitudes, product usage, and product differentiation. Implicit attitudes were measured using the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998). Study 1 showed expected differences in implicit attitudes between users of two leading yogurt brands, also revealing significant correlations between IAT‐measured implicit attitudes and explicit attitudes. In Study 2, users of two fast food restaurants (McDonald's and Milk Bar) showed implicit attitudi‐nal preference for their favorite restaurant. In Study 3, implicit attitudes of users of two soft drinks (Coca‐Cola and Pepsi) predicted brand preference, product usage, and brand recognition in a blind taste test. A meta‐analytic combination of the three studies showed that the use of IAT measures increased the prediction of behavior relative to explicit attitude measures alone.

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Metadata

Authors
Maison, D., Greenwald, A. G., & Bruin, R. H.
Venue
Journal of Consumer Psychology
Publisher
Wiley
Published
2004-01
Volume
14
Issue
4
Pages
405-415
ISSN
  • 1057-7408 (ISSN-L)
  • 1532-7663
OpenAlex
W2041468403
Cited by
375
References
49
FWCI
35.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Predictive Validity of the Implicit Association Test in Studies of Brands, Consumer Attitudes, and Behavior. https://app.cochat.ai/papers/10.1207/s15327663jcp1404_9
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Maison, D., Greenwald, A. G., & Bruin, R. H. (2004). Predictive Validity of the Implicit Association Test in Studies of Brands, Consumer Attitudes, and Behavior. Journal of Consumer Psychology. https://doi.org/10.1207/s15327663jcp1404_9

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.