Monday, February 24, 2020

Sponsored Data: Smarter Data Pricing with Incomplete Information

Xiaowei Mei, Hong Kong Polytechnic University - Department of Management and Marketing, Hsing Kenneth Cheng University of Florida - Warrington College of Business, Shubho Bandyopadhyay University of Florida - Warrington College of Business Administration, Liangfei Qiu University of Florida - Warrington College of Business Administration, and Lai Wei Shanghai Jiao Tong University (SJTU) theorize about Sponsored Data: Smarter Data Pricing with Incomplete Information.

ABSTRACT: As the amount of online content explodes, mobile network operators (MNOs) are investigating new business models that encourage content providers (CPs) to sponsor data for consumers. We analyze this recent phenomenon using an incomplete information game-theoretical model, where the MNO does not observe consumers’ types (personal valuation of mobile data), and provides multiple data plans to consumers. We find that the impact of sponsored data on consumer surplus crucially depends on whether the MNO has complete information over consumer types: Under complete information, sponsored data does not improve consumer surplus. However, under incomplete information, sponsored data increases consumer surplus. Our analysis also shows that under incomplete information, the MNO should allow sponsored data in a wider range of market conditions than those under complete information. Our study finds that prior literature tends to underestimate both the long-run detrimental effect of sponsored data on content diversity and the short-run beneficial effect on consumer surplus. Our findings have important managerial implications for the MNO who is interested in optimizing the data plans and for policymakers who regulate the wireless internet market.

https://lawprofessors.typepad.com/antitrustprof_blog/2020/02/sponsored-data-smarter-data-pricing-with-incomplete-information.html

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