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Should Online Content Providers Be Allowed To Subsidize Content?—An Economic Analysis

Author

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  • Soohyun Cho

    (Rutgers, The State University of New Jersey, Newark, New Jersey 07102; and Department of Information Systems and Operations Management, Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611)

  • Liangfei Qiu

    (Department of Information Systems and Operations Management, Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611)

  • Subhajyoti Bandyopadhyay

    (Department of Information Systems and Operations Management, Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611)

Abstract

Internet service providers (ISPs) are experimenting with a business model that allows content providers (CPs) to subsidize Internet access for end consumers. In this study, we develop a game-theoretical model to analyze the effects of this sponsorship of consumer data usage. We find that the ISP’s optimal network management choice of data sponsorship crucially depends on market conditions, such as the revenue rates of CPs and the fit cost of consumers. If the fit cost is low, the ISP will either allow both CPs to subsidize consumers’ Internet access, or will allow only the more competitive CP to subsidize, depending on the per-consumer revenue generation rates of CPs. If the fit cost is high, it is in the ISPs interest not to allow any subsidization. We also identify conditions under which the ISP’s network management choices of data sponsorship deviate from social optimum. These results should be of interest to the telecom industry as it searches additional revenue models, and to online CPs competing for customer loyalty. It should also be of interest to policymakers investigating into this issue.

Suggested Citation

  • Soohyun Cho & Liangfei Qiu & Subhajyoti Bandyopadhyay, 2016. "Should Online Content Providers Be Allowed To Subsidize Content?—An Economic Analysis," Information Systems Research, INFORMS, vol. 27(3), pages 580-595.
    • Handle: RePEc:inm:orisre:v:27:y:2016:i:3:p:580-595
    DOI: 10.1287/isre.2016.0641
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    References listed on IDEAS

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    Cited by:

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    3. Subodha Kumar & Xiaowei Mei & Liangfei Qiu & Lai Wei, 2020. "Watching Ads for Free Mobile Data: A Game-Theoretic Analysis of Sponsored Data with Reward Task," Working Papers 20-08, NET Institute.
    4. Xiaowei Mei & Hsing Kenneth Cheng & Subhajyoti Bandyopadhyay & Liangfei Qiu & Lai Wei, 2022. "Sponsored Data: Smarter Data Pricing with Incomplete Information," Information Systems Research, INFORMS, vol. 33(1), pages 362-382, March.
    5. Perera, Sandun & Gupta, Varun & Buckley, Winston, 2020. "Management of online server congestion using optimal demand throttling," European Journal of Operational Research, Elsevier, vol. 285(1), pages 324-342.
    6. Wu, Jie & Li, Yunbing & Dong, Yu & Zha, Yong, 2023. "Sponsored data: A game-theoretic model with consumer multihoming behaviour," European Journal of Operational Research, Elsevier, vol. 307(2), pages 731-744.
    7. Schnurr, Daniel & Wiewiorra, Lukas, 2018. "Bit-by-Bit Towards Unlimited: An Analysis of Zero Rating and Sponsored Data Practices of Internet Service Providers," 29th European Regional ITS Conference, Trento 2018 184965, International Telecommunications Society (ITS).

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