The Role of Data Cap in Optimal Two-part Network Pricing

Abstract

Internet services are traditionally priced at flat rates; however, many Internet service providers (ISPs) have recently shifted towards two-part tariffs where a data cap is imposed to restrain data demand from heavy users and usage over the data cap is charged based on a per-unit fee. Although the two-part tariff could generally increase the revenue for ISPs and has been supported by the FCC chairman, the role of data cap and its revenue-optimal and welfare-optimal pricing structures are not well understood. In this paper, we study the impact of data cap on the optimal two-part pricing schemes for congestion-prone service markets, e.g., broadband or cloud services. We model users' demand and preferences over pricing and congestion alternatives and derive the market share and congestion of service providers under a market equilibrium. Based on the equilibrium model, we characterize the two-part structures of the revenue-optimal and welfare-optimal pricing schemes. Our results reveal that 1) the data cap provides a mechanism for ISPs to transition from flat-rate to pay-as-you-go type of schemes, 2) with growing data demand and network capacity, the revenue-optimal pricing moves towards usage-based schemes with diminishing data caps, and 3) the structure of the welfare-optimal tariff comprises lower fees and data cap than those of the revenue-optimal counterpart, suggesting that regulators might want to promote usage-based pricing but regulate the per-unit fees. Our results could help providers design revenue-optimal pricing schemes and guide regulatory authorities to legislate desirable regulations.