Responding to Online Reviews in Competitive Markets: A Controlled Diffusion Approach

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Publication History

Received: March 21, 2019
Revised: July 28, 2020; July 26, 2021; December 17, 2021; March 3, 2022
Accepted: March 5, 2022
Published Online as Articles in Advance: February 27, 2023
Published Online in Issue: March 1, 2023

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We study how firms respond to online customer reviews in a competitive market where they jostle with one another for sales based on online ratings. The focus of this paper is on how firms can optimally manage their ratings through management response and how review ratings affect the sales and profits of competing firms. We develop a controlled diffusion process to model the coevolution of sales and ratings as a function of the response strategy chosen to maximize profit over time. Our model considers a variety of factors, such as profit margin and customer rating sensitivity, that influence a firm’s effort to manage ratings and subsequently its sales and profits. More response effort needs to be exerted to manage ratings when either the profit margin of a tour is very high or customers are very sensitive to ratings. We estimate our model using data on Ctrip’s tours that include each tour’s sales, reviews, prices, and tour features. We find that consumers anchor their beliefs in the mean market rating and that their purchase decisions depend on the tour’s rating relative to this anchor. Thus, relative, rather than absolute, ratings matter. Our study informs firms on how competition and other primitives impact their efforts to manage ratings and hence profit. Our methodology allowed us to conduct “what-if” analyses, for example, to study what would happen to the review ratings, sales, and profits of a tour if a firm adopted a different response strategy. We were also able to provide turnaround strategies for struggling tours, i.e., factors that a loss-making tour should change if it wishes to make a positive profit. Ultimately, we conducted a competitive analysis that allowed us to modify certain parameters that affect the intensity of competition and hence the sales and the profits of competing tours. Finally, we demonstrate the flexibility of the model by extending it to incorporate multiple state variables that might affect the response strategy. 

Additional Details
Author Mingwen Yang, Zhiqiang (Eric) Zheng, Vijay Mookerjee, and Hongyu Chen
Year 2023
Volume 47
Issue 1
Keywords Social media, competition, management response, controlled diffusion processes
Page Numbers 161-194
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