Alone, Together: A Model of Social (Mis)Learning from Consumer Reviews

Tommaso Bondi ()
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Tommaso Bondi: Cornell Tech, New York, New York 10044; and SC Johnson School of Management, Cornell University, Ithaca, New York 14853

Marketing Science, 2025, vol. 44, issue 6, 1258-1277

Abstract: We develop a dynamic model of naïve social learning from consumer reviews. In our model, consumers decide if and what to buy based on both the products’ expected quality and their idiosyncratic taste for them. Products’ qualities are initially unknown and are (mis)learned from reviews. At the heart of the model lies a dynamic feedback loop between reviews, beliefs, and choices: period t reviews influence t + 1 consumers’ beliefs and, thus, choices; these determine the average of t + 1 reviews, which, in turn, influences t + 2 beliefs, choices, and reviews. We show that, in the long run ( t = ∞ ), reviews are systematically biased, leading some consumers astray. In particular, in both monopoly and duopoly, reviews relatively advantage lower quality and more polarizing products because these products induce stronger taste-based consumer self-selection. Thus, in stark contrast with the winner-takes-all dynamics of classic observational learning models in which consumers learn from the choices of their predecessors, social learning from opinions generates excessive choice fragmentation. Our findings have implications for interpreting the variance and number of reviews, pricing in the presence of reviews, and the short- and long-term effectiveness of fake reviews.

Keywords: online reviews; social learning; digitization (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:44:y:2025:i:6:p:1258-1277

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