The role of data cap in two-part pricing under market competition

Wang, Xin; Richard, T. B.; Xu, Yinlong

doi:10.1109/infcomw.2015.7179440

“…If q I < q 0 and ρ(u, q I ) > g I and p I g I − f I ≤ p I ρ(u, q 0 ), for any user type φ = (u, v), ∀v < p I , it satisfies that y * (φ, θ I , q I ) = g I and y * (φ, θI , q I ) = ρ(u, q I ) by Equation ( 4). Thus we have that π y * (φ, θ I , q I ), v, θ I = vg I − f I ≤ p I g I − f I ≤ vρ(u, q 0 ) and π y * (φ, θI , q I ), v, θI = vρ(u, q I ) − f I − ρ(u, q I ) − g I p I ≤ vρ(u, q I ) − p I ρ(u, q I ) + p I ρ(u, q 0 ) ≤ vρ(u, q 0 ) by Equation (2). It implies that the user type φ = (u, v), ∀v < p I would not choose the ISP no matter it adopts the pricing strategy θ I or θI .…”

Section: Proof Of Theoremmentioning

confidence: 96%

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

Wang

¹

,

Richard

²

,

Xu

³

2017

IEEE/ACM Trans. Networking

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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. Although the two-part tariff could generally increase the revenue for ISPs and has been supported by the US FCC, the role of data cap and its optimal pricing structures are not well understood. In this article, we study the impact of data cap on the optimal two-part pricing schemes for congestion-prone service markets. 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-and welfare-optimal pricing schemes. Our results reveal that 1) the data cap provides a mechanism for ISPs to transition from the flat-rate to pay-as-you-go type of schemes, 2) both the revenue and welfare objectives of the ISP will drive the optimal pricing towards usage-based schemes with diminishing data caps, and 3) the welfare-optimal tariff comprises lower fees than the revenue-optimal counterpart, suggesting that regulators might want to promote usage-based pricing but regulate the lump-sum and per-unit fees.• We model users' optimal data usages and preferences over providers for any pricing scheme and congestion level (Section III). We characterize the existence and uniqueness (Theorem 1) of a congestion equilibrium and show its monotonic dynamics (Theorem 2) under varying pricing and market structures. • We analyze the impact of data cap on a provider's optimal pricing and revenue under two-part tariffs (Section IV). We find that by decreasing data cap, the revenue-optimal pricing transforms from flat-rate to pay-as-you-go, during which the provider's revenue increases from a minimum to a maximum (Theorem 3). With heavier user demand, higher provider'sThe updated version serves an erratum to prior papers [1-3], which studied the role of data cap in optimal two-part tariffs. In Section VI and V of [1] and [3], and Section III and VI of [2], the theoretical analysis and simulation results of the optimal pricing do not hold in general. In this present article, we combine the models from the original papers with new corrected results in Section IV and V.

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“…9. According to [26], [27], [28], a consumer usually chooses a data plan with monthly data cap larger than his average consumption. Period of data plan helps an SP to manage its network capacity, because an SP should make sure a corresponding network capacity is prepared during the whole period in case that the consumers consume all data quota for the whole period in a very short time.…”

Section: Discrete-consumer-typementioning

confidence: 99%

“…Solve the problem: max t k P k , where the optimal point tk can be obtained from (28) If the period assignments obtained are not feasible, using Algorithm 1 to adjust infeasible sub-sequences into feasible sub-sequences (the definition of infeasible sub-sequence is in Definition 3).…”

mentioning

confidence: 99%

A Novel Mobile Data Contract Design with Time Flexibility

Wei

¹

,

Yu

²

,

Lok

³

et al. 2019

IEEE Trans. on Mobile Comput.

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In conventional mobile data plans, the data is associated with a fixed period (e.g., one month) and the unused data will be cleared at the end of each period. To take advantage of consumers' heterogeneous demands across different periods and meanwhile to provide more time flexibility, some mobile data service providers (SP) have offered data plans with different lengths of period. In this paper, we consider the data plan design problem for a single SP, who provides data plans with different lengths of period for consumers with different characteristics of data demands. We propose a contract-theoretic approach, wherein the SP offers a period-price data plan contract which consists of a set of period and price combinations, indicating the prices for data with different periods. We study the optimal data plan contract designs under two different models: discrete and continuous consumer-type models, depending on whether the consumer type is discrete or continuous. In the former model, each type of consumers are assigned with a specific period-price combination. In the latter model, the consumers are first categorized into a finite number of groups, and each group of consumers (possibly with different types) are assigned with a specific period-price combination. We systematically analyze the incentive compatibility (IC) constraint and individual rationality (IR) constraint, which ensure each consumer to choose the data plan with the period-price combination intended for his type. We further derive the optimal contract that maximizes the SP's expected profit, meanwhile satisfying the IC and IR constraints of consumers. Our numerical results show that the proposed optimal contract can increase the SP's profit by 35%, comparing with the conventional fixed monthly-period data plan.

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“…by Equation (2). It implies that the user type φ = (u, v), ∀v < p I would not choose the ISP no matter it adopts the pricing strategy θ I orθ I .…”

Section: Proof Of Propositionmentioning

confidence: 99%

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

Wang

¹

,

Richard

²

,

Xu

³

2015

Proceedings of the 24th International Conference on World Wide Web

Self Cite

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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. Although the two-part tariff could generally increase the revenue for ISPs and has been supported by the US FCC, the role of data cap and its optimal pricing structures are not well understood. In this article, we study the impact of data cap on the optimal two-part pricing schemes for congestion-prone service markets. 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-and welfare-optimal pricing schemes. Our results reveal that 1) the data cap provides a mechanism for ISPs to transition from the flat-rate to pay-as-you-go type of schemes, 2) both the revenue and welfare objectives of the ISP will drive the optimal pricing towards usage-based schemes with diminishing data caps, and 3) the welfare-optimal tariff comprises lower fees than the revenue-optimal counterpart, suggesting that regulators might want to promote usage-based pricing but regulate the lump-sum and per-unit fees.

show abstract

The role of data cap in two-part pricing under market competition

Cited by 6 publications

References 25 publications

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

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

A Novel Mobile Data Contract Design with Time Flexibility

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

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