Dynamic pricing to control loss systems with quality of service targets

Robert C. Hampshire, William A. Massey, Qiong Wang

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Numerous examples of real-time services arise in the service industry that can be modeled as loss systems. These include agent staffing for call centers, provisioning bandwidth for private line services, making rooms available for hotel reservations, and congestion pricing for parking spaces. Given that arriving customers make their decision to join the system based on the current service price, the manager can use price as a mechanism to control the utilization of the system. A major objective for the manager is then to find a pricing policy that maximizes total revenue while meeting the quality of service targets desired by the customers. For systems with growing demand and service capacity, we provide a dynamic pricing algorithm. A key feature of our solution is congestion pricing. We use demand forecasts to anticipate future service congestion and set the present price accordingly.

Original languageEnglish (US)
Pages (from-to)357-383
Number of pages27
JournalProbability in the Engineering and Informational Sciences
Volume23
Issue number2
DOIs
StatePublished - Apr 1 2009

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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