The Pitfalls of Review Solicitation: Evidence from a Natural Experiment on TripAdvisor
成果类型:
Article
署名作者:
Gao, Baojun; Wang, Jing; Ding, Xiaojie; Guo, Yue
署名单位:
Wuhan University; Hong Kong University of Science & Technology; Wuhan Textile University; Southern University of Science & Technology
刊物名称:
MANAGEMENT SCIENCE
ISSN/ISSBN:
0025-1909
DOI:
10.1287/mnsc.2023.01006
发表日期:
2025
关键词:
review solicitation program
online reviews
two-stage difference-in-differences
Spillover effect
structural topic model
摘要:
This study examines the effect of firms' participation in platform -endorsed review solicitation programs on consumers' online review generation. We leverage a natural experiment on TripAdvisor, which launched a review solicitation program that allows hotels to collect reviews directly from guests after their stays with the aid of certified connectivity partners. Applying a two -stage difference -in -differences approach to a panel data set of online reviews for a matched set of hotels across TripAdvisor and Expedia, we find that hotels' participation in the review solicitation program results in a 34.3% increase in review volume, a 0.151 increase in review rating, but a 16.9% decrease in review length. Review solicitation, however, generates a notable negative spillover effect on the volume of organic reviews. Specifically, the volume of organic reviews is reduced by 15.5% after hotels start soliciting reviews. We provide evidence that the motivational crowding -out effect plays an important role in driving this negative spillover. Further analyses reveal that the effects of review solicitation are heterogeneous with respect to hotels of different types and consumers with different demographic and behavioral characteristics. Finally, using a novel structural topic model, we detect a significant shift in review content from specific and concrete topics to general and abstract topics. Our findings suggest that review platforms and firms should be cautious about the unintended negative consequences of review solicitation on consumers' review generation.