Sponsored Data: Smarter Data Pricing with Incomplete Information

Xiaowei Mei, Hsing Kenneth Cheng, Subhajyoti Bandyopadhyay, Liangfei Qiu, Lai Wei (Corresponding Author)

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

With the upcoming next-generation 5G networks, mobile network operators (MNOs, such as AT&T, T-Mobile, and Verizon) are investigating new business models that encourage content providers (such as Netflix and Spotify) to sponsor data for consumers. Sponsored data allow customers to browse, stream, and enjoy content from their data sponsors without impacting their monthly data plan allowance. 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 do not improve consumer surplus. However, under incomplete information, sponsored data increase 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 suggests 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 offer important managerial implications for the MNO, who is interested in optimizing the data plans, and for policymakers who regulate the wireless internet market.

Original languageEnglish
Pages (from-to)362-382
JournalInformation Systems Research
Volume33
Issue number1
Publication statusPublished - Mar 2022

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