Fooled by heteroscedastic randomness: Local consistency breeds extremity in price-based quality inferences
De Langhe, Bart Van Osselaer, Stijn Puntoni, Stefano McGill, Ann L.
De Langhe, Bart
Van Osselaer, Stijn
Puntoni, Stefano
McGill, Ann L.
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Publication Type
Journal article with impact factor
Editor
Supervisor
Publication Year
2014
Journal
Journal of Consumer Research
Book
Publication Volume
41
Publication Issue
4
Publication Begin page
978
Publication End page
994
Publication NUmber of pages
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Abstract
In some product categories, low-priced brands are consistently of low quality, but high-priced brands can be anything from terrible to excellent. In other product categories, high-priced brands are consistently of high quality, but quality of low-priced brands varies widely. Three experiments demonstrate that such heteroscedasticity leads to more extreme price-based quality predictions. This finding suggests that quality inferences do not only stem from what consumers have learned about the average level of quality at different price points through exemplar memory or rule abstraction. Instead, quality predictions are also based on learning about the covariation between price and quality. That is, consumers inappropriately conflate the conditional mean of quality with the predictability of quality. We discuss implications for theories of quantitative cue learning and selective information processing, for pricing strategies and luxury branding, and for our understanding of the emergence and persistence of erroneous beliefs and stereotypes beyond the consumer realm.
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Keywords
Brand Name Product Sales & Prices, Product Quality, Consumer Attitudes, Luxuries, Statistical Correlation, Heteroscedasticity, Stereotypes, Human Information Processing