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Output-specific input-assurance regions in DEA

Listed author(s):
  • W D Cook

    (York University, Toronto, ON, Canada)

  • J Zhu

    (Worcester Polytechnic Institute, Worcester, MA, USA)

Registered author(s):

    The use of assurance region (AR) constraints to restrict multipliers in data envelopment analysis (DEA) is well-established, and has been discussed at length in the literature. The conventional assumption in imposing such restrictions is that they apply universally. Specifically, AR constraints on input multipliers are intended to control the relative importance of the individual inputs in terms of how they impact the entire bundle of outputs. In many settings the relative importance of inputs is different for some of the outputs than for others. A typical example of this in the financial services sector is where the importance of sales staff versus service staff is different in regard to sales outputs than is true for service outputs. In this paper we develop a general DEA framework that incorporates multiple input-AR structures that cater to multiple output classes. We examine the cases of both divisible and indivisible inputs, and as well as mutually exclusive and overlapping output sets. The concepts are applied to a financial services situation.

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    Article provided by Palgrave Macmillan & The OR Society in its journal Journal of the Operational Research Society.

    Volume (Year): 62 (2011)
    Issue (Month): 10 (October)
    Pages: 1881-1887

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    Handle: RePEc:pal:jorsoc:v:62:y:2011:i:10:p:1881-1887
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