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Selective measures in data envelopment analysis

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  • Mehdi Toloo
  • Mona Barat
  • Atefeh Masoumzadeh

Abstract

Data envelopment analysis (DEA) is a data based mathematical approach, which handles large numbers of variables, constraints, and data. Hence, data play an important and critical role in DEA. Given a set of decision making units (DMUs) and identified inputs and outputs (performance measures), DEA evaluates each DMU in comparison with all DMUs. According to some statistical and empirical rules, a balance between the number of DMUs and the number of performance measures should exist. However, in some situations the number of performance measures is relatively large in comparison with the number of DMUs. These cases lead us to choose some inputs and outputs in a way that produces acceptable results. We refer to these selected inputs and outputs as selective measures. This paper presents an approach toward a large number of inputs and outputs. Individual DMU and aggregate models are recommended and expanded separately for developing the idea of selective measures. The practical aspect of the new approach is illustrated by two real data set applications. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Mehdi Toloo & Mona Barat & Atefeh Masoumzadeh, 2015. "Selective measures in data envelopment analysis," Annals of Operations Research, Springer, vol. 226(1), pages 623-642, March.
    • Handle: RePEc:spr:annopr:v:226:y:2015:i:1:p:623-642:10.1007/s10479-014-1714-3
    DOI: 10.1007/s10479-014-1714-3
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    Cited by:

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    3. Sepideh Abolghasem & Mehdi Toloo & Santiago Amézquita, 2019. "Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems," Health Care Management Science, Springer, vol. 22(3), pages 512-533, September.
    4. Navas, Lina P. & Montes, Felipe & Abolghasem, Sepideh & Salas, Ricardo J. & Toloo, Mehdi & Zarama, Roberto, 2020. "Colombian higher education institutions evaluation," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    5. Toloo, Mehdi & Hančlová, Jana, 2020. "Multi-valued measures in DEA in the presence of undesirable outputs," Omega, Elsevier, vol. 94(C).
    6. Mehdi Toloo & Mona Barat, 2015. "On considering dual-role factor in supplier selection problem," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 82(1), pages 107-122, August.
    7. Lee, Yooneun & Prabhu, Vittaldas, 2019. "Evaluation and monitoring of community youth prevention programs using a robust productivity index," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    8. Lukáš Melecký & Michaela Staníčková & Jana Hančlová, 2019. "Nonparametric Approach to Evaluation of Economic and Social Development in the EU28 Member States by DEA Efficiency," JRFM, MDPI, vol. 12(2), pages 1-34, April.
    9. Marta García-Mollá & Rosa Puertas & Carles Sanchis-Ibor, 2021. "Application of Data Envelopment Analysis to Evaluate Investments in the Modernization of Collective Management Irrigation Systems in Valencia (Spain)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 5011-5027, November.
    10. Villanueva-Cantillo, Jeyms & Munoz-Marquez, Manuel, 2021. "Methodology for calculating critical values of relevance measures in variable selection methods in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 290(2), pages 657-670.
    11. Toloo, Mehdi & Tone, Kaoru & Izadikhah, Mohammad, 2023. "Selecting slacks-based data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1302-1318.
    12. Toloo, Mehdi & Keshavarz, Esmaeil & Hatami-Marbini, Adel, 2021. "Selecting data envelopment analysis models: A data-driven application to EU countries," Omega, Elsevier, vol. 101(C).

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