Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/1001
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dc.contributor.authorGao, Baojun
dc.contributor.authorHu, Nan
dc.contributor.authorBose, Indranil
dc.date.accessioned2021-08-26T06:03:21Z-
dc.date.available2021-08-26T06:03:21Z-
dc.date.issued2017
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/1001-
dc.descriptionBaojun Gao, Associate Professor of Management Science at Wuhan University; Nan Hu, Associate Professor at Stevens Institute of Technology; Indranil Bose, Department of Management Information Systems, Indian Institute of Management Calcutta, Kolkata;
dc.descriptionpp.1-11
dc.descriptionDOI - https://doi.org/10.1016/j.dss.2016.11.005
dc.description.abstractThis study investigates if reviewers' pattern of rating is consistent over time and predictable. Two interesting results emerge from the econometric analyses using publicly available data from TripAdvisor.com. First, reviewers' rating behavior is consistent over time and across products. Furthermore, most of the variation in their future rating behavior can be explained by their rating behavior in the past rather than by the observed average rating. Second, reviews by reviewers with higher absolute bias in rating in the past receive more helpful votes in future. We further divide the bias in rating into intrinsic bias (driven by intrinsic reviewer characteristics) and extrinsic bias (driven by influences beyond intrinsic bias) and document that intrinsic bias plays a more significant role in influencing helpful votes for reviews than extrinsic bias. Our results are robust to different product categories and different definition of bias. Overall our results indicate that in the online review context, the observed average rating or an attention grabbing strategy may not be as important as believed in the past. This study provides insights into reviewers' rating behavior and prescribes actionable items for online vendors so that they can proactively influence online opinion instead of passively responding to them.
dc.publisherAR-IIMC
dc.publisherDecision Support System
dc.publisherElsevier
dc.relation.ispartofseries95
dc.titleFollow the herd or be myself? An analysis of consistency in behaviour of reviewers and helpfulness of their reviews
dc.typeArticle
Appears in Collections:Management Information Systems

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