Linear and Nonlinear Pricing for Network Games with Complete and Incomplete Information
Shen, Hongxia
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/99601
Description
Title
Linear and Nonlinear Pricing for Network Games with Complete and Incomplete Information
Author(s)
Shen, Hongxia
Issue Date
2007-05
Keyword(s)
Network games
Pricing
Nonlinear pricing
Incomplete information
Network externality
Incentive
Stackelberg game
Abstract
This dissertation addresses optimal linear and nonlinear pricing policy design for a monopolistic network service provider with various types of public and private information on user types. In the communication network pricing literature, it is the linear pricing schemes that have been largely adopted, and here we investigate both linear and nonlinear pricing within the framework of a hierarchical Stackelberg (leader-follower) game, where the service provider sets prices for the resources (bandwidth) he offers as the leader, and the users respond by their choices of the amount of bandwidth (flow) they are willing to pay for. At the lower level, the presence of congestion cost (negative network effect) in the net utility functions of users leads to a noncooperative game among themselves, with Nash or Bayesian equilibrium being natural candidates for a solution. In the nonlinear pricing case, the approach is to view the problem as a reverse Stackelberg game, which is also an incentive-design problem. We also consider, for both linear and nonlinear pricing, three different scenarios based on the information sharing structure for all parties on the users' true types, namely complete information, partially incomplete information, and totally incomplete information. For each case, we obtain the optimal, or near-optimal, pricing policy that maximizes the service provider's profit given the noncooperative price-taking behavior of the users, generally for the asymptotic case regarding the number of users, since our focus is on communication networks with a large user population. Comparative studies between linear and nonlinear pricing, as well as between the three classes of informational scenarios, are carried out to evaluate profit improvement by adoption of nonlinear pricing and the service provider's game preferences.
Publisher
Coordinated Science Laboratory, University of Illinois at Urbana-Champaign
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
