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    Fooled by heteroscedastic randomness: Local consistency breeds extremity in price-based quality inferences

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    Publication type
    FT ranked journal article  
    Author
    De Langhe, Bart
    Van Osselaer, Stijn
    Puntoni, Stefano
    McGill, Ann L.
    Publication Year
    2014
    Journal
    Journal of Consumer Research
    Publication Volume
    41
    Publication Issue
    4
    Publication Begin page
    978
    Publication End page
    994
    
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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.
    Keyword
    Brand Name Product Sales & Prices, Product Quality, Consumer Attitudes, Luxuries, Statistical Correlation, Heteroscedasticity, Stereotypes, Human Information Processing
    Knowledge Domain/Industry
    Marketing & Sales
    DOI
    10.1086/678035
    URI
    http://hdl.handle.net/20.500.12127/7175
    ae974a485f413a2113503eed53cd6c53
    10.1086/678035
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