The informational role of online product review distributions: An experimental study of biases in online product reviews

Wenjuan Yuan, Yili Hong, Paul A. Pavlou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Previous studies have identified the impact of self-selection biases in online product reviews on consumer surplus. However, no empirical study has studied how the consumers evaluate the rating distributions of online reviews, especially when credibility of reviews is susceptible to be jeopardized by self-selection biases. This study investigates how the existence of different types of self-selection biases in online product reviews influences consumers' intentions to purchase products and post reviews. A 2×2×2 randomized experiment was conducted to examine the role of two self-selection biases (underreporting and purchasing biases). Results indicate that subjects exposed to online product reviews that suffer from underreporting bias and purchasing bias have a significantly lower intention to purchase a product and post a review. Because consumers are not able to fully correct the self-selection biases in online product reviews, this study calls for the need to overcome self-selection biases and formulate strategies to help consumers trust online product reviews.

Original languageEnglish (US)
Title of host publication18th Americas Conference on Information Systems 2012, AMCIS 2012
Pages3780-3790
Number of pages11
StatePublished - 2012
Externally publishedYes
Event18th Americas Conference on Information Systems 2012, AMCIS 2012 - Seattle, WA, United States
Duration: Aug 9 2012Aug 12 2012

Publication series

Name18th Americas Conference on Information Systems 2012, AMCIS 2012
Volume5

Other

Other18th Americas Conference on Information Systems 2012, AMCIS 2012
Country/TerritoryUnited States
CitySeattle, WA
Period8/9/128/12/12

Keywords

  • Online product reviews
  • Purchasing bias
  • Purchasing intention
  • Self-selection biases
  • Trust
  • Under-reporting bias

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Library and Information Sciences

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