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Robustness of efficiency scores in data envelopment analysis with interval scale data

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  • Nasrabadi, Nasim
  • Dehnokhalaji, Akram
  • Korhonen, Pekka
  • Lokman, Banu
  • Wallenius, Jyrki

Abstract

Our paper focuses on a robustness analysis of efficiency scores in the context of Data Envelopment Analysis (DEA) assuming interval scale data, as defined in A. Dehnokhalaji, P. J. Korhonen, M. Köksalan, N. Nasrabadi and J. Wallenius, “Efficiency Analysis to incorporate interval scale data”, European Journal of Operational Research 207 (2), 2010, pp. 1116–1121. We first show that the definition of the efficiency score used in our paper is a well-defined measure according to Aparicio and Pastor (J. Aparicio and J. T. Pastor, “A well-defined efficiency measure for dealing with closest targets in DEA”, Applied Mathematics and Computation 219 (17), 2013, pp. 9142–9154.). Next, we characterize how robust the efficiency scores are with respect to improvements and deteriorations of inputs and outputs. We illustrate our analysis with two examples: a simple numerical example and a more complex example using real-world data.

Suggested Citation

  • Nasrabadi, Nasim & Dehnokhalaji, Akram & Korhonen, Pekka & Lokman, Banu & Wallenius, Jyrki, 2022. "Robustness of efficiency scores in data envelopment analysis with interval scale data," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1151-1161.
    • Handle: RePEc:eee:ejores:v:297:y:2022:i:3:p:1151-1161
    DOI: 10.1016/j.ejor.2021.06.049
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    References listed on IDEAS

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    1. Köksalan, Murat & Büyükbasaran, Tayyar & Özpeynirci, Özgür & Wallenius, Jyrki, 2010. "A flexible approach to ranking with an application to MBA Programs," European Journal of Operational Research, Elsevier, vol. 201(2), pages 470-476, March.
    2. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    3. Korostelev, A. P. & Simar, L. & Tsybakov, A. B., 1995. "Estimation of monotone boundaries," LIDAM Reprints CORE 1178, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Zhu, Joe, 1996. "Robustness of the efficient DMUs in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 90(3), pages 451-460, May.
    5. Dehnokhalaji, Akram & Korhonen, Pekka J. & Köksalan, Murat & Nasrabadi, Nasim & Wallenius, Jyrki, 2010. "Efficiency analysis to incorporate interval-scale data," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1116-1121, December.
    6. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    7. SIMAR , Léopold, 1995. "Aspects of Statistical Analysis in DEA-Type Frontier Models," LIDAM Discussion Papers CORE 1995061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Lawrence Seiford & Joe Zhu, 1999. "Sensitivity and Stability of the Classifications of Returns to Scale in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 12(1), pages 55-75, August.
    9. Korostelev, A.P. & Simar , L. & Tsybakov, A.B., 1995. "On estimation of monotone and convex boundaries," LIDAM Reprints CORE 1139, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
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