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Can online reviews reveal a product's true quality? Empirical findings analytical modeling of online word-of-mouth communication

  • Nan Hu
  • , Paul A. Pavlou
  • , Jennifer Zhang
  • Singapore Management University
  • University of California at Riverside
  • University of Toledo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

298 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 7th ACM Conference on Electronic Commerce 2006
Pages324-330
Number of pages7
StatePublished - 2006
Externally publishedYes
Event7th ACM Conference on Electronic Commerce - Ann Arbor, MI, United States
Duration: 11 Jun 200615 Jun 2006

Publication series

NameProceedings of the ACM Conference on Electronic Commerce
Volume2006

Conference

Conference7th ACM Conference on Electronic Commerce
Country/TerritoryUnited States
CityAnn Arbor, MI
Period11/06/0615/06/06

Keywords

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

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