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Online Review Consistency Matters: An Elaboration Likelihood Model Perspective

Author

Listed:
  • Navid Aghakhani

    (University of Tennessee Chattanooga)

  • Onook Oh

    (University of Colorado Denver)

  • Dawn G. Gregg

    (University of Colorado Denver)

  • Jahangir Karimi

    (University of Colorado Denver)

Abstract

To date, online review usefulness studies have explored the independent influence of central and peripheral cues on online review usefulness. Employing the Elaboration Likelihood Model (ELM), however, we argue that central and peripheral cues are jointly, not independently, processed by online users. For this exploration, we develop and measure “review consistency” variable (i.e., level of consistency between a review text and its attendant review rating), and rating inconsistency (i.e., level of inconsistency between a review rating and the average rating). We find a positive effect of review consistency on the review usefulness. Contrary to our hypothesis, however, we find a positive effect of rating inconsistency on the review usefulness. Our results also indicate that the contingency effect of rating inconsistency on the relationship between review consistency and review usefulness. Particularly, we find that rating inconsistency negatively moderates the effect of review consistency on the review usefulness. The theoretical and practical implications of the findings are discussed.

Suggested Citation

  • Navid Aghakhani & Onook Oh & Dawn G. Gregg & Jahangir Karimi, 0. "Online Review Consistency Matters: An Elaboration Likelihood Model Perspective," Information Systems Frontiers, Springer, vol. 0, pages 1-15.
    • Handle: RePEc:spr:infosf:v::y::i::d:10.1007_s10796-020-10030-7
    DOI: 10.1007/s10796-020-10030-7
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    References listed on IDEAS

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