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Sensitivity Analysis in DEA

In: Handbook on Data Envelopment Analysis

Author

Listed:
  • William W. Cooper

    (University of Texas at Austin)

  • Shanling Li

    (McGill University)

  • Lawrence M. Seiford

    (University of Michigan at Ann Arbor)

  • Joe Zhu

    (Worcester Polytechnic Institute)

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.

Suggested Citation

  • William W. Cooper & Shanling Li & Lawrence M. Seiford & Joe Zhu, 2011. "Sensitivity Analysis in DEA," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 71-91, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-6151-8_3
    DOI: 10.1007/978-1-4419-6151-8_3
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    Cited by:

    1. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    2. D'Inverno, Giovanna & Carosi, Laura & Ravagli, Letizia, 2018. "Global public spending efficiency in Tuscan municipalities," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 102-113.
    3. Alfons Oude Lansink & Spiro Stefanou & Magdalena Kapelko, 2015. "The impact of inefficiency on diversification," Journal of Productivity Analysis, Springer, vol. 44(2), pages 189-198, October.

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