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An Investigation of Peripheral and Central Cues of Online Customer Review Voting and Helpfulness through the Lens of Elaboration Likelihood Model

Author

Listed:
  • Mohammadreza Mousavizadeh

    (Western Michigan University)

  • Mehrdad Koohikamali

    (California State Polytechnic University)

  • Mohammad Salehan

    (California State Polytechnic University)

  • Dam J. Kim

    (University of North Texas)

Abstract

Online consumer reviews (OCRs) have become an important part of online consumers’ decision-making to purchse products. Consumers use OCRs not only to get a better understanding of the characteristics of products but also to learn about other customers’ experiences with them. Drawing upon Elaboration Likelihood Model, this research investigates the predictors of popularity and helpfulness of OCRs. The results of the study show that longer reviews, as well as those with extreme star ratings, are more popular. Moreover, the amount of hedonic and utilitarian cues in a review and its sentiment significantly influence perceptions of online consumers regarding its helpfulness. The results also show how product type moderates the effect of utilitarian and hedonic cues on helpfulness. Our results can be used by online review websites to develop more efficient methods for sorting OCRs.

Suggested Citation

  • Mohammadreza Mousavizadeh & Mehrdad Koohikamali & Mohammad Salehan & Dam J. Kim, 2022. "An Investigation of Peripheral and Central Cues of Online Customer Review Voting and Helpfulness through the Lens of Elaboration Likelihood Model," Information Systems Frontiers, Springer, vol. 24(1), pages 211-231, February.
    • Handle: RePEc:spr:infosf:v:24:y:2022:i:1:d:10.1007_s10796-020-10069-6
    DOI: 10.1007/s10796-020-10069-6
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