Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

6-2006

Abstract

As a digital version of word-of-mouth, online review has become a major information source for consumers and has very important implications for a wide range of management activities. While some researchers focus their studies on the impact of online product review on sales, an important assumption remains unexamined, that is, can online product review reveal the true quality of the product? To test the validity of this key assumption, this paper first empirically tests the underlying distribution of online reviews with data from Amazon. The results show that 53% of the products have a bimodal and non-normal distribution. For these products, the average score does not necessarily reveal the product's true quality and may provide misleading recommendations. Then this paper derives an analytical model to explain when the mean can serve as a valid representation of a product's true quality, and discusses its implication on marketing practices.

Keywords

Bi-Modal Distribution, Online Reviews, Word-of-Mouth

Discipline

Computer Sciences | E-Commerce | Numerical Analysis and Scientific Computing

Research Areas

Information Systems and Management

Publication

EC '06: Proceedings of the 7th ACM Conference on Electronic Commerce, Ann Arbor, MI, June 11-15

First Page

324

Last Page

330

ISBN

9781595932365

Identifier

10.1145/1134707.1134743

Publisher

ACM

City or Country

New York

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1145/1134707.1134743

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