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Non-Discretionary and Categorical Variables

In: Data Envelopment Analysis


  • William W. Cooper

    (University of Texas)

  • Lawrence M. Seiford

    (University of Michigan)

  • Kaoru Tone

    (National Graduate Institute for Policy Studies)


In this chapter we expanded the ability of DEA to deal with variables that are not under managerial control but nevertheless affect performances in ways that need to be taken into account when effecting evaluations. Non-discretionary and categorical variables represent two of the ways in which conditions beyond managerial control can be taken into account in a DEA analysis. Uses of upper or lower bounds constitute yet another approach and, of course, these approaches can be combined in a variety of ways. Finally, uses of Wilcoxon-Mann-Whitney statistics were introduced for testing results in a nonparametric manner when ranking can be employed. Illustrative examples were supplied along with algorithms that can be used either separately or with the computer code DEA-Solver. We also showed how to extend DEA in order to deal with production possibility sets (there may be more than one) that are not convex. Finally we provided examples to show how new results can be secured when DEA is applied to such sets to test the efficiency of organization forms (and other types of activities) in ways that were not otherwise available.

Suggested Citation

  • William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Non-Discretionary and Categorical Variables," Springer Books, in: Data Envelopment Analysis, edition 0, chapter 7, pages 215-255, Springer.
  • Handle: RePEc:spr:sprchp:978-0-387-45283-8_7
    DOI: 10.1007/978-0-387-45283-8_7

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