IDEAS home Printed from https://ideas.repec.org/a/inm/orserv/v2y2010i1-2p76-91.html
   My bibliography  Save this article

A Stochastic Model of Resource Allocation for Service Systems

Author

Listed:
  • Ralph Badinelli

    (Virginia Tech, Department of BIT (0235), Virginia Tech, Blacksburg VA 24061, USA)

Abstract

Purpose: In this paper we develop a resource allocation model for a service system. The uncertainty of the relationship between inputs and outputs of a process of co-creation of value by a service provider and a service recipient is modeled with a stochastic form of the technology function of each service process of the system. The model development is directed at providing useful policy prescription for service providers and a foundation for research into the nature of resource allocation policies in service industries. Design/methodology/approach: The model development makes use of concepts of probability theory, optimization theory and extant DEA models. Findings: A practical optimization for allocating resources to service processes as well as insights into the complexity of service resource management are obtained. Research limitations/implications: The model presented in this paper is based on constant returns to scale of the service process. Nonlinear technology functions will be the subject of future research. Originality/value: To date, service science lacks models for resource management that approach the usefulness of resource-management models for manufacturing enterprises even though the service economy in the industrialized world is larger than the manufacturing economy. This paper initiates a stream of model-building research. [ Service Science , ISSN 2164-3962 (print), ISSN 2164-3970 (online), was published by Services Science Global (SSG) from 2009 to 2011 as issues under ISBN 978-1-4276-2090-3.]

Suggested Citation

  • Ralph Badinelli, 2010. "A Stochastic Model of Resource Allocation for Service Systems," Service Science, INFORMS, vol. 2(1-2), pages 76-91, June.
  • Handle: RePEc:inm:orserv:v:2:y:2010:i:1-2:p:76-91
    DOI: 10.1287/serv.2.1_2.76
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/serv.2.1_2.76
    Download Restriction: no

    File URL: https://libkey.io/10.1287/serv.2.1_2.76?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orserv:v:2:y:2010:i:1-2:p:76-91. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.