Follow the herd or be myself? An analysis of consistency in behavior of reviewers and helpfulness of their reviews

作者:

Highlights:

• Reviewers' rating behavior is consistent over time and products and predictable.

• Rating behavior of reviewers in the past explains future ratings provided by them.

• Extreme reviews by reviewers receive more helpful votes from readers in future.

• Intrinsic bias of reviewers influences the helpfulness of their reviews.

摘要

This 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.

论文关键词:Consistency in rating,Helpful votes,Online hotel reviews,Rating bias,Rating difference,Tripadvisor

论文评审过程:Received 23 April 2016, Revised 18 November 2016, Accepted 20 November 2016, Available online 25 November 2016, Version of Record 3 March 2017.

论文官网地址:https://doi.org/10.1016/j.dss.2016.11.005