Understanding the determinants of online review helpfulness: A meta-analytic investigation

Hong Hong, Di Xu, G. Alan Wang, Weiguo Fan

Research output: Contribution to journalArticle

Abstract

Online consumer reviews can help customers reduce uncertainty and risks faced in online shopping. However, the studies examining the determinants of perceived review helpfulness produce mixed findings. We review extant research about the determinant factors of perceived online review helpfulness. All review related determinants (i.e., review depth, review readability, linear review rating, quadratic review rating, review age) and two reviewer related determinants (i.e., reviewer information disclosure and reviewer expertise) are found to have inconsistent conclusions on how they affect perceived review helpfulness. We conduct a meta-analysis to examine those determinant factors in order to reconcile the contradictory findings about their influence on perceived review helpfulness. The meta-analysis results affirm that review depth, review age, reviewer information disclosure, and reviewer expertise have positive influences on review helpfulness. Review readability and review rating are found to have no significant influence on review helpfulness. Moreover, we find that helpfulness measurement, online review platform, and product type are the three factors that cause mixed findings in extant research.

Original languageEnglish (US)
Pages (from-to)1-11
Number of pages11
JournalDecision Support Systems
Volume102
DOIs
StatePublished - Oct 2017
Externally publishedYes

Keywords

  • Meta-analysis
  • Online customer reviews
  • Review
  • Review helpfulness

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management

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