Effects of Online Reviews and Competition on Quality and Pricing Strategies

Cui Zhao, Xiaojun Wang, Yongbo Xiao*, Jie Sheng

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

23 Citations (Scopus)

Abstract

By providing useful product information from the perspective of other buyers, online product/service reviews can help customers better evaluate the true quality of products and judge whether a product is a good fit for them. Based on online reviews, firms may improve product quality and/or adjust selling price to compete with other firms. In this study, we investigate the effects of online reviews on product quality and pricing decisions in a duopoly market that consists of two competing firms. Specifically, we consider a stylized two-period model and study the equilibrium decisions based on a Nash game framework. In the base scenario, the selling prices are exogenously given, and the firms decide on the product quality across two periods to optimize their respective profits. We study the equilibrium decisions in the static setting (in which the product quality remains the same across the two periods) and in the dynamic setting (in which the product quality can be improved in the second period), respectively. In the extended scenario, the selling prices can be endogenously determined as well. For each scenario, we compare the equilibrium decisions under dynamic competition with those under static competition through theoretical analysis and numerical experiments, which uncover some interesting managerial insights regarding the impact of online reviews under competition.
Original languageEnglish
Pages (from-to)3840 - 3858
Number of pages19
JournalProduction and Operations Management
Volume31
Issue number10
DOIs
Publication statusPublished - 1 Oct 2022

Bibliographical note

Funding Information:
We are grateful to the Department Editor, the Associate Editor, and two anonymous referees for their valuable comments that have helped improve the paper significantly. This work has been partially supported by the National Key R&D Program of China under Grant Number: 2020AAA0103801 and the National Natural Science Foundation of China under Grant Number: 72125002.

Publisher Copyright:
© 2022 Production and Operations Management Society.

Keywords

  • online reviews
  • Nash game
  • quality improvement
  • optimal pricing

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