Operations Research
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


OPERATIONS RESEARCH
Vol. 53, No. 2, March-April 2005, pp. 242-262
DOI: 10.1287/opre.1040.0172
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Maglaras, C.
Right arrow Articles by Zeevi, A.
Right arrow Search for Related Content

Pricing and Design of Differentiated Services: Approximate Analysis and Structural Insights

Constantinos Maglaras, Assaf Zeevi

Graduate School of Business, Columbia University, Uris Hall, 3022 Broadway, New York, New York 10027
Graduate School of Business, Columbia University, Uris Hall, 3022 Broadway, New York, New York 10027

c.maglaras{at}gsb.columbia.edu
assaf{at}gsb.columbia.edu

We consider a model of a service system that delivers two nonsubstitutable services to a market of heterogenous users. The first service is delivered subject to a "guaranteed" (G) processing rate, and the second is a "best-effort" (BE) type service in which residual capacity not allocated to the guaranteed class is shared among BE users. Users, in turn, are sensitive to both price and congestion-related effects. The service provider’s objective is to optimally design the system so as to extract maximum revenues. The design variables in this problem consist of a pair of static prices for the two services, a policy that controls admission of G users into the system, and the mechanism by which users are informed of the state of congestion in the system. Because these objectives are difficult to address using exact analysis, we pursue approximations that are tractable and lead to structural insights. Specifically, we first solve a deterministic relaxation of the original objective to obtain a "fluid-optimal" solution that is subsequently evaluated and refined to account for stochastic fluctuations. Using diffusion limits, we derive approximations that yield the following structural results: (1) pricing rules derived from the deterministic analysis are "almost" optimal, (2) the optimal operational regime for the system is close to heavy traffic, and (3) real-time congestion notification results in increased revenues. Numerical results illustrate the accuracy of the proposed approximations and validate the aforementioned structural insights.

Subject classifications: congestion notification; diffusion approximations; economics; Halfin-Whitt regime; many server limits; pricing; queueing; revenue management; service differentiation.
History: Received April 2003; revision received November 2003; accepted March 2004.




This article has been cited by other articles:


Home page
Information Systems ResearchHome page
S. Sen, T. S. Raghu, and A. Vinze
Demand Heterogeneity in IT Infrastructure Services: Modeling and Evaluation of a Dynamic Approach to Defining Service Levels
Information Systems Research, June 1, 2009; 20(2): 258 - 276.
[Abstract] [PDF]


Home page
Operations ResearchHome page
B. Ata and T. L. Olsen
Near-Optimal Dynamic Lead-Time Quotation and Scheduling Under Convex-Concave Customer Delay Costs
Operations Research, May 1, 2009; 57(3): 753 - 768.
[Abstract] [PDF]


Home page
Operations ResearchHome page
I. Gurvich, M. Armony, and C. Maglaras
Cross-Selling in a Call Center with a Heterogeneous Customer Population
Operations Research, March 1, 2009; 57(2): 299 - 313.
[Abstract] [PDF]


Home page
MSOMHome page
A. Bassamboo, J. M. Harrison, and A. Zeevi
Pointwise Stationary Fluid Models for Stochastic Processing Networks
MSOM, January 1, 2009; 11(1): 70 - 89.
[Abstract] [PDF]


Home page
Operations ResearchHome page
G. Y. Lin, Y. Lu, and D. D. Yao
The Stochastic Knapsack Revisited: Switch-Over Policies and Dynamic Pricing
Operations Research, July 1, 2008; 56(4): 945 - 957.
[Abstract] [PDF]


Home page
Management ScienceHome page
I. Gurvich, M. Armony, and A. Mandelbaum
Service-Level Differentiation in Call Centers with Fully Flexible Servers
Management Science, February 1, 2008; 54(2): 279 - 294.
[Abstract] [PDF]


Home page
Management ScienceHome page
N. Gans and S. Savin
Pricing and Capacity Rationing for Rentals with Uncertain Durations
Management Science, March 1, 2007; 53(3): 390 - 407.
[Abstract] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2005 by INFORMS.