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Self-Selection and Information Role of Online Product Reviews
Open accessAbstract
Online product reviews may be subject to self-selection biases that impact consumer purchase behavior, online ratings' time series, and consumer surplus. This occurs if early buyers hold different preferences than do later consumers about the quality of a given product. Readers of early product reviews may not successfully correct for these preference differences when interpreting ratings and making purchases. In this study, we develop a model that examines how idiosyncratic preferences of early buyers can affect long-term consumer purchase behavior as well as the social welfare created by review systems. Our model provides an explanation for the structure of product ratings over time, which we empirically test using online book reviews posted on Amazon.com. Our analysis suggests that firms could benefit from altering their marketing strategies such as pricing, advertising, or product design to encourage consumers likely to yield positive reports to self-select into the market early and generate positive word-of-mouth for new products. On the other hand, self-selection bias, if not corrected, decreases consumer surplus.
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Cited by
The impact of electronic word-of-mouth communication: A literature analysis and integrative model
Cheung, C. M. K., & Thadani, D. R. (2012) · Decision Support Systems · doi:10.1016/j.dss.2012.06.008 · Cited by 2,005
Digital marketing: a framework, review, and research agenda
Kannan, P. K., & Li, H. “. (2017) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2016.11.006 · Cited by 1,707
Predictive Analytics in Information Systems Research1
Shmueli, G., & Koppius, O. R. (2011) · MIS Quarterly · doi:10.2307/23042796 · Cited by 1,328
Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
Luca, M., & Zervas, G. (2016) · Management Science · doi:10.1287/mnsc.2015.2304 · Cited by 1,263
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Metadata
- Authors
- Li, X., & Hitt, L. M.
- Venue
- Information Systems Research
- Published
- 2008-12
- Volume
- 19
- Issue
- 4
- Pages
- 456-474
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2135189989
- Cited by
- 1,125
- References
- 2
- FWCI
- 103.38
- Type
- journal article
- Language
- en
- Open access
- green
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Data sources
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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.