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Data Envelopment Analysis with Fuzzy Parameters: An Interactive Approach

Author

Listed:
  • Adel Hatami-Marbini

    (Universite Catholique de Louvain, Belgium)

  • Saber Saati

    (Islamic Azad University, Iran)

  • Madjid Tavana

    (La Salle University, USA)

Abstract

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. In the conventional DEA, all the data assume the form of specific numerical values. However, the observed values of the input and output data in real-life problems are sometimes imprecise or vague. Previous methods have not considered the preferences of the decision makers (DMs) in the evaluation process. This paper proposes an interactive evaluation process for measuring the relative efficiencies of a set of DMUs in fuzzy DEA with consideration of the DMs’ preferences. The authors construct a linear programming (LP) model with fuzzy parameters and calculate the fuzzy efficiency of the DMUs for different a levels. Then, the DM identifies his or her most preferred fuzzy goal for each DMU under consideration. A modified Yager index is used to develop a ranking order of the DMUs. This study allows the DMs to use their preferences or value judgments when evaluating the performance of the DMUs.

Suggested Citation

  • Adel Hatami-Marbini & Saber Saati & Madjid Tavana, 2011. "Data Envelopment Analysis with Fuzzy Parameters: An Interactive Approach," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 2(3), pages 39-53, July.
  • Handle: RePEc:igg:joris0:v:2:y:2011:i:3:p:39-53
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    Cited by:

    1. Gözde YEŞİLAYDIN & Nesrin ALPTEKİN, 2016. "Bulanık Veri Zarflama Analizi İle OECD Ülkelerinin Sağlık Alanındaki Etkinliklerinin Değerlendirilmesi," Sosyoekonomi Journal, Sosyoekonomi Society, issue 24(30).
    2. Vladimir Pajković & Mirjana Grdinić-Rakonjac, 2021. "Evaluation of Road Safety Performance Based on Self-Reported Behaviour Data Set," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    3. Wanke, Peter & Barros, C.P. & Nwaogbe, Obioma R., 2016. "Assessing productive efficiency in Nigerian airports using Fuzzy-DEA," Transport Policy, Elsevier, vol. 49(C), pages 9-19.
    4. Barros, C.P. & Emrouznejad, Ali, 2016. "Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banksAuthor-Name: Wanke, Peter," European Journal of Operational Research, Elsevier, vol. 249(1), pages 378-389.

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