Estimating the Effect of Social Influence on Subsequent Reviews

Saram Han, Chris K. Anderson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationAdvances in Service Science - Proceedings of the 2018 INFORMS International Conference on Service Science
EditorsHui Yang, Robin Qiu
PublisherSpringer Science and Business Media B.V.
Pages231-238
Number of pages8
ISBN (Print)9783030047252
DOIs
StatePublished - 2019
EventINFORMS International Conference on Service Science, ICSS 2018 - Phoenix, United States
Duration: 3 Nov 20183 Nov 2018

Publication series

NameSpringer Proceedings in Business and Economics
ISSN (Print)2198-7246
ISSN (Electronic)2198-7254

Conference

ConferenceINFORMS International Conference on Service Science, ICSS 2018
Country/TerritoryUnited States
CityPhoenix
Period3/11/183/11/18

Keywords

  • eWOM on-line review
  • Peer effect

Fingerprint

Dive into the research topics of 'Estimating the Effect of Social Influence on Subsequent Reviews'. Together they form a unique fingerprint.

Cite this