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Robust DEA Efficiency Scores: A Heuristic for the Combinatorial/Probabilistic Approach

In: Advances in Efficiency and Productivity II

Author

Listed:
  • Juan Aparicio

    (Miguel Hernández University)

  • Juan F. Monge

    (Miguel Hernández University)

Abstract

In this paper, we present a comparison of robust efficiency scores for the scenario in which the specification of the inputs/outputs to be included in the data envelopment analysis (DEA) model is modeled with a probability distribution, through the traditional cross-efficiency evaluation procedure. We evaluate the ranking obtained from these scores and analyze the robustness of these rankings, in such a way that any changes respect the set of units selected for the analysis. The probabilistic approach allows us to obtain two different robust efficiency scores: the unconditional expected score and the expected score under the assumption of maximum entropy principle. The calculation of these efficiency scores involves the resolution of an exponential number of linear problems. We also present an algorithm to estimate the robust scores in an affordable computational time.

Suggested Citation

  • Juan Aparicio & Juan F. Monge, 2020. "Robust DEA Efficiency Scores: A Heuristic for the Combinatorial/Probabilistic Approach," International Series in Operations Research & Management Science, in: Juan Aparicio & C. A. Knox Lovell & Jesus T. Pastor & Joe Zhu (ed.), Advances in Efficiency and Productivity II, pages 125-142, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-41618-8_8
    DOI: 10.1007/978-3-030-41618-8_8
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