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Optimal Scheduling and Incentive Compatible Pricing for a Service System with Quality of Service Guarantees

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Author Info

  • Vernon N. Hsu

    ()
    (Department of Decision Sciences and Managerial Economics, Faculty of Business Administration, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong)

  • Susan H. Xu

    ()
    (Department of Supply Chain and Information Systems, Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

  • Boris Jukic

    ()
    (School of Business, Clarkson University, Potsdam, New York 13699)

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    Abstract

    This paper proposes a resource allocation and pricing mechanism for a service system that serves multiple classes of jobs within an organization. Each class of service request is subject to a class-dependent quality of service (QoS) guarantee on the expected delay bound, which may be imposed by business rules in an organization or other application-specific technical constraints. We develop an extension of a resource allocation and pricing mechanism for an M/M/1 system. In contrast to the system without the QoS guarantee, where a fixed priority scheduling policy--known as the c\mu rule--is optimal, we show that the system may need to adopt a more general randomized priority scheduling policy to maximize the overall system profit. We also develop a transfer pricing scheme that is both optimal and incentive compatible, allowing users to act in their self-interests while collectively achieving the system optimum. We show that the pricing scheme with the QoS guarantee depends on the scheduling policy implemented and has different characteristics from that without the QoS guarantee.

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    File URL: http://dx.doi.org/10.1287/msom.1080.0226
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    Bibliographic Info

    Article provided by INFORMS in its journal Manufacturing & Service Operations Management.

    Volume (Year): 11 (2009)
    Issue (Month): 3 (May)
    Pages: 375-396

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    Handle: RePEc:inm:ormsom:v:11:y:2009:i:3:p:375-396

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    Related research

    Keywords: capacity planning and investment; technology management and process design; service operations;

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