The Love of Large Numbers Revisited: A Coherence Model of the Popularity Bias.

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ID: 82678
2020
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Abstract
Preferences are often based on social information such as experiences and recommendations of other people. The reliance on social information is especially relevant in the case of online shopping, where buying decisions for products may often be based on online reviews by other customers. Recently, Powell, Yu, DeWolf, and Holyoak (2017, Psychological Science, 28, 1432-1442) showed that, when deciding between two products, people do not consider the number of product reviews in a statistically appropriate way as predicted by a Bayesian model but rather exhibit a bias for popular products (i.e., products with many reviews). In the present work, we propose a coherence model of the cognitive mechanism underlying this empirical phenomenon. The new model assumes that people strive for a coherent representation of the available information (i.e., the average review score and the number of reviews). To test this theoretical account, we reanalyzed the data of Powell and colleagues and ran an online study with 244 participants using a wider range of stimulus material than in the original study. Besides replicating the popularity bias, the study provided clear evidence for the predicted coherence effect, that is, decisions became more confident and faster when the available information about popularity and quality was congruent.
Reference Key
heck2020thecognition Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Heck, Daniel W;Seiling, Lukas;Bröder, Arndt;
Journal Cognition
Year 2020
DOI
S0010-0277(19)30242-2
URL
Keywords
decision making judgment information integration heuristics parallel constraint satisfaction

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