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Sensitivity Analysis in DEA

  • William W. Cooper
  • Shanling Li
  • Lawrence M. Seiford
  • Joe ZhuEmail author
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 164)

Abstract

This chapter presents some of the recently developed analytical methods for studying the sensitivity of DEA results to variations in the data. The focus is on the stability of classification of DMUs (decision making units) into efficient and inefficient performers. Early work on this topic concentrated on developing algorithms for conducting such analyses after it was noted that standard approaches for conducting sensitivity analyses in linear programming could not be used in DEA. However, recent work has bypassed the need for such algorithms. It has also evolved from the early work that was confined to studying data variations in one input or output for one DMU. The newer methods described in this chapter make it possible to analyze the sensitivity of results when all data are varied simultaneously for all DMUs.

Keywords

Data envelopment analysis Efficiency Stability Sensitivity 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • William W. Cooper
    • 1
  • Shanling Li
    • 2
  • Lawrence M. Seiford
    • 3
  • Joe Zhu
    • 4
    Email author
  1. 1.Red McCombs School of BusinessUniversity of Texas at AustinAustinUSA
  2. 2.Faculty of ManagementMcGill UniversityMontrealCanada
  3. 3.Department of Industrial and Operations EngineeringUniversity of Michigan at Ann ArborAnn ArborUSA
  4. 4.School of BusinessWorcester Polytechnic InstituteWorcesterUSA

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