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Estimating the Effect of Social Influence on Subsequent Reviews

In: Advances in Service Science

Author

Listed:
  • Saram Han

    (Cornell University)

  • Chris K. Anderson

    (Cornell University)

Abstract

This study proposes an effective way of using retailer-prompted review data from TripAdvisor to measure the social network effect in self-motivated online reviews by overcoming the reflection problem. After applying the network effect model, we find that self-motivated review ratings are positively associated with previous corresponding peer reviews. We further show that the size of this peer effect attenuates as the peer reviews are located further away from the first page. This study suggests that reviewer ratings are more strongly influenced by peer ratings located on the visible page.

Suggested Citation

  • Saram Han & Chris K. Anderson, 2019. "Estimating the Effect of Social Influence on Subsequent Reviews," Springer Proceedings in Business and Economics, in: Hui Yang & Robin Qiu (ed.), Advances in Service Science, pages 231-238, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-04726-9_23
    DOI: 10.1007/978-3-030-04726-9_23
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    Cited by:

    1. Zhou, Tao & Li, Kai, 2024. "Designing manufacturer’s new product technology for a closed-loop supply chain with consumer context effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).

    More about this item

    Keywords

    Peer effect; eWOM on-line review;

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