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The Value of Social Dynamics in Online Product Ratings Forums

Moe, Wendy W., Trusov, Michael·2011·Journal of Marketing Research

Abstract

Research has shown that consumer online product ratings reflect both the customers' experience with the product and the influence of others' ratings. In this article, the authors measure the impact of social dynamics in the ratings environment on both subsequent rating behavior and product sales. First, they model the arrival of product ratings and separate the effects of social influences from the underlying (or baseline) ratings behavior. Second, the authors model product sales as a function of posted product ratings while decomposing ratings into a baseline rating, the contribution of social influence, and idiosyncratic error. This enables them to quantify the sales impact of observed social dynamics. The authors consider both the direct effects on sales and the indirect effects that result from the influence of dynamics on future ratings (and thus future sales). The results show that although ratings behavior is significantly influenced by previously posted ratings and can directly improve sales, the effects are relatively short lived once indirect effects are considered.

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Metadata

Authors
Moe, W. W., & Trusov, M.
Venue
Journal of Marketing Research
Published
2011-06
Volume
48
Issue
3
Pages
444-456
ISSN
  • 0022-2437 (ISSN-L)
  • 1547-7193
OpenAlex
W2178002576
Cited by
672
References
2
FWCI
107.16
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Value of Social Dynamics in Online Product Ratings Forums. https://app.cochat.ai/papers/10.1509/jmkr.48.3.444
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Moe, W. W., & Trusov, M. (2011). The Value of Social Dynamics in Online Product Ratings Forums. Journal of Marketing Research. https://doi.org/10.1509/jmkr.48.3.444

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.