HEC Research Papers Series,
HEC Paris

Abstract: Online ratings emerge from a multi-stage process that can systematically distort their informational content. We develop a unified framework decomposing the rating process into distinct components: experienced quality (driven by intrinsic quality, seller effort, and price), expectations formed prior to consumption, contextual influences, strategic distortions, idiosyncratic tastes, and selection into reviewing. This decomposition organizes a growing theoretical and empirical literature and clarifies how seemingly disparate findings -- from fake reviews to disappointment effects to selection biases - relate to distinct stages of the data-generating process. Our framework also provides a lens for evaluating platform design interventions: effective policies target specific components of the rating process, yet many distortions remain difficult to address without introducing new trade-offs. We highlight open questions where further research is most needed.

Keywords: Online reviews; Rating biases; Digital platforms; Platform design

JEL-codes: D83; D83; L86

28 pages, January 29, 2026

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