Pricing Decisions with Social Interactions: A Game-Theoretic Model

Xiaofang Wang (), Yaoyao Yang () and Jun Zhuang ()
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Xiaofang Wang: School of Business, Renmin University of China, Beijing 100872, China
Yaoyao Yang: School of Business, Renmin University of China, Beijing 100872, China
Jun Zhuang: Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, New York 14260

Decision Analysis, 2023, vol. 20, issue 1, 40-54

Abstract: For media or digital products with quality uncertainty like online games, movies, theater plays, software, and smartphone applications, online customers may strategically delay their purchase waiting for online reviews and their peers’ purchase decisions. Thus, a firm needs to consider both social learning and positive network externality to anticipate the customers’ purchasing decisions and set a good pricing strategy over time. This paper investigates how these dual concerns affect the strategic interaction between a firm using preannounced pricing or responsive pricing and strategic customers in a two-period game-theoretic model. Deviating from conventional wisdom suggesting that social learning and externality work in a similar way, our results highlight their differences and provide valuable managerial insights. Although social learning and externality play a similar role in expanding the increasing-price-optimal region, they are different in other aspects: The firm will be worse off with learning if the externality gets stronger, whereas it will be worse off or better off with learning if learning gets stronger. In addition, we characterize the condition under which responsive pricing may outperform preannounced pricing. We further find that the firm’s discount factor has an influence on the firm’s pricing strategy selection.

Keywords: decision analysis; preannounced pricing; responsive pricing; network externality; social learning (search for similar items in EconPapers)
Date: 2023
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