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Content Revenue Models and Net Neutrality
By Abhinav Uppal, Jagmohan S. Raju
Citation
Uppal, Abhinav., Raju, Jagmohan S.. (2025). Content Revenue Models and Net Neutrality .
Copyright
2025
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Abstract
There is an ongoing global debate on network neutrality, a principle that prohibits Internet Service Providers (ISPs) such as Comcast from charging content providers like Netflix for preferential delivery of their content to end-users. In this paper, we shed new light on the debate by developing and analyzing a model of the Internet that allows the ISP to charge CPs (in the absence of network neutrality) while considering different revenue structures of the CPs. We show that the implications of network neutrality depend critically on the CPs’ revenue models. While CPs become worse off without network neutrality in the scenario where we limit CPs to rely on advertising alone for revenue, we find that they can be better off without network neutrality when they can charge a subscription fee to end-users. End-users, on the other hand, receive a lower surplus without network neutrality when both CPs can charge them subscription fees. We also study a scenario where only one content provider can charge end-users directly while the other relies only on advertising revenue. We find that the ISP, CPs and end-users can all be better off without network neutrality in this scenario.
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Abhinav Uppal

Abhinav Uppal is an assistant professor of Marketing at the Indian School of Business. His research interests lie broadly in using microeconomic theory and game-theory based models to study topical problems in marketing. Currently, his work focuses on two main streams of research: the first is retailing, specifically how traditional retailers can counter modern threats; the second is competitive strategy and pricing, particularly how various market settings, structures, and strategic partnerships influence firms’ competitive behavior and marketing decisions.

Professor Uppal received his PhD and MS in Marketing from the Wharton School, University of Pennsylvania. He has previously worked on algorithmic trading strategies in equity markets at Tower Research Capital and conducted research on technology for emerging markets at Microsoft Research India. He holds a BTech in Computer Science from the Indian Institute of Technology (IIT) Delhi and is a KVPY and NTSE scholar.

Abhinav Uppal