SDP research papers can be roughly categorized by the different types of pricing that they investigate. We consider 15 such topics here. If you know of a paper we missed, let us know.
Usage-based pricing (8)
Usage-based pricing charges users in proportion to their actual volume of data usage, creating an incentive for users to moderate their data usage. Most service providers offer a form of usage-based pricing for wired and wireless data, charging users a fixed fee for a monthly cap on usage volume and, if necessary, usage-based overage charges.
Xin Wang, Richard T.B. Ma, and Yinlong Xu Proceedings of the 24th International Conference on World Wide Web 2015
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.
A. Nevo, J. L. Turner and J. W. Williams NBER Working Paper Series
We estimate demand for residential broadband using high-frequency data from subscribers facing a three-part tariff. The three-part tariff makes data usage during the billing cycle a dynamic problem; thus, generating variation in the (shadow) price of usage. We provide evidence that subscribers respond to this variation, and use their dynamic decisions to estimate a flexible distribution of willingness to pay for different plan characteristics. Using the estimates, we simulate demand under alternative pricing and find that usage-based pricing eliminates low-value traffic. Furthermore, we show that the costs associated with investment in fiber-optic networks are likely recoverable in some markets, but that there is a large gap between social and private incentives to invest.
J. Walrand Z. Liu and C. H. Xia, Eds., Performance Modeling and Engineering. Springer, New York, Chapter 3, 57–90, 2008
Standard performance evaluations of communication networks focus on the technology layer where protocols define precise rules of operations. Those studies assume a model of network utilization and of network characteristics and derive performance measures. However, performance affects how users utilize the network. Also, investments by network providers affect performance and consequently network utilization. We call the actions of users and network providers the “economic layer” of the network because their decisions depend largely on economic incentives. The economic and technology layers interact in a complex way and they should be studied together. This tutorial explores economic models of networks that combine the economic and technology layers.
A. Odlyzko, B. St. Arnaud, E. Stallman and M. Weinberg Public Knowledge, 2012
Usage-‐based pricing, today most commonly encountered in the form of data caps, is rapidly becoming part of the Internet access landscape. Wired and wireless Internet service providers – most of whom had traditionally operated on an unlimited basis – are evaluating or implementing pricing strategies that limit the amount of data a customer can use, charge customers for using data beyond a predetermined amount, or combine the two. Although some providers have been quick to embrace these pricing structures, consumers have generally not been enthusiastic, and have often expressed strong protests. For their part, regulators have largely avoided asking even basic questions about this trend. This whitepaper is an attempt to begin a serious consideration of usage-‐based pricing. It attempts to move beyond rhetoric and recognizes that usage-‐based pricing is a tool. As with any tool, usage-‐based pricing can be used for both productive and destructive ends. Sometimes these ends are intentional. Other times, they are a byproduct of other goals or even a lack of careful consideration. Regardless of the motivation driving its implementation, usage-‐based pricing has the potential to signiHicantly impact how networks are designed and used. This, in turn, impacts the innovation that relies on those networks. Before deciding if and when usage-‐based pricing is desirable, it is critical to fully understand the history of usage-‐based pricing, how it impacts markets, and both the beneHits and harms that such a model can bring. 1 This paper aims to explain the basic issues surrounding usage-‐based versus Hlat-‐rate pricing. Section I examines the trend towards usage-‐based pricing in both the wired and wireless markets. Section II then considers the beneHits and justiHications for using usage-‐based pricing. This is followed in Section III by a review of the history and economics of Hlat rate pricing. Since broadband access is central to so many national and societal goals, the penultimate section – Section IV – discusses the problems that might be caused by usage-‐based pricing. Finally, we end with a series of conclusions and recommendations for responsible implementation of usage-‐ based pricing.
S. Li, J. Huang and S. Y. R. Li Proceedings of IEEE GLOBECOM, 2009
We study the optimal usage-based pricing problem in a resource-bounded network with one profit-maximizing service provider and multiple groups of surplus-maximizing users. We first analytically derive the optimal pricing mechanism that the service provider maximizes the service provider's revenue under complete network information. Then we consider the incomplete information case, and propose two incentive compatible pricing schemes that achieve different complexity and performance tradeoff. Finally, by properly combining the two pricing schemes, we can show that it is possible to maintain a very small revenue loss (e.g., 0.5% in a two-group case) without knowing detailed information of each user in the network.
P. Hande, M.Chiang, R. Calderbank and J. Zhang Proceedings of IEEE INFOCOM, 2010
This paper investigates pricing of Internet connectivity services in the context of a monopoly ISP selling broadband access to consumers. We first study the optimal combination of flat-rate and usage-based access price components for maximization of ISP revenue, subject to a capacity constraint on the data-rate demand. Next, we consider time-varying consumer utilities for broadband data rates that can result in uneven demand for data-rate over time. Practical considerations limit the viability of altering prices over time to smoothen out the demanded data-rate. Despite such constraints on pricing, our analysis reveals that the ISP can retain the revenue by setting a low usage fee and dropping packets of consumer demanded data that exceed capacity. Regulatory attention on ISP congestion management discourages such ``technical" practices and promotes economics based approaches. We characterize the loss in ISP revenue from an economics based approach. Regulatory requirements further impose limitations on price discrimination across consumers, and we derive the revenue loss to the ISP from such restrictions. We then develop partial recovery of revenue loss through non-linear pricing that does not explicitly discriminate across consumers. While determination of the access price is ultimately based on additional considerations beyond the scope of this paper, the analysis here can serve as a benchmark to structure access price in broadband access networks.
M. Chetty, R. Banks, A. Brush, J. Donner and R. Grinter Proceedings of ACM SIGCHI, 2012
Bandwidth caps, a limit on the amount of data users can upload and download in a month, are common globally for both home and mobile Internet access. With caps, each bit of data consumed comes at a cost against a monthly quota or a running tab. Yet, relatively little work has considered the implications of this usage-based pricing model on the user experience. In this paper, we present results from a qualitative study of households living with bandwidth caps. Our findings suggest home users grapple with three uncertainties regarding their bandwidth usage: invisible balances, mysterious processes, and multiple users. We discuss how these uncertainties impact their usage and describe the potential for better tools to help monitor and manage data caps. We conclude that as a community we need to cater for users under Internet cost constraints.
H. Shen and T. Basar IEEE Journal on Selected Areas in Communications, 25(6): 1216-1223, 2007
In the communication network pricing literature, it is the linear pricing schemes that have been largely adopted as the means of controlling network usage or generating profits for network service providers. This paper extends the framework to nonlinear pricing and investigates optimal nonlinear pricing policy design for a monopolistic service provider. The problem is formulated as an incentive-design problem, and incentive (pricing) policies are obtained for a many-users regime, which enable the service provider to approach arbitrarily close to Pareto- optimal solutions. Under the assumption that the service provider knows the true user types, analytical and numerical results indicate a profit improvement exceeding 38% over linear pricing by the introduction of nonlinear pricing. We also consider the scenario where the service provider has incomplete information on user types. A comparative study of the results for complete information and incomplete information is carried out as well, with numerical results pointing to 25%-40% loss of profit by the service provider due to incompleteness of information on the user types.
Two-sided pricing (15)
QoS-aware pricing (14)