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Pricing strategies of two-sided platforms considering privacy concerns

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  • Duan, Yongrui
  • Liu, Peng
  • Feng, Yixuan

Abstract

Most online platforms, represented by news media, are keen to adopt a business model based on user subscription prices and advertising prices. However, in the context of the popularity of this subscription model, the contents and advertisements recommended by the platform also increase users' concerns about privacy, and the managerial implications of how to balance the revenue from users and advertisers to optimal platform profits are not well understood. We develop a two-sided model considering users' privacy concerns to investigate the optimal pricing strategy of online platforms. Specifically, we analyze the impacts of information disclosure level and user's privacy concerns for information disclosure on the optimal pricing strategy and surplus of users and advertisers. We find that the platform can strategically make pricing decisions based on the level of information disclosure to influence user demand and further promote the participation of advertisers, and when the information disclosure is at an intermediate level, the surplus of advertisers and users reaches the maximum. Besides, we discuss the conditions under which the online platform has an incentive to provide users with free services. We find that privacy concerns and information disclosure have a positive effect on the platform's free strategy.

Suggested Citation

  • Duan, Yongrui & Liu, Peng & Feng, Yixuan, 2022. "Pricing strategies of two-sided platforms considering privacy concerns," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:joreco:v:64:y:2022:i:c:s0969698921003477
    DOI: 10.1016/j.jretconser.2021.102781
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    6. Mohit Tyagi & Nomesh B. Bolia, 2024. "Optimal pricing of subscription services in the restaurant industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(3), pages 262-273, June.

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