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Efficiency measurement in fuzzy additive data envelopment analysis

Author

Listed:
  • Adel Hatami-Marbini
  • Madjid Tavana
  • Ali Emrouznejad
  • Saber Saati

Abstract

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers’ intuition and subjective judgements. This paper extends the conventional DEA models to a fuzzy framework by proposing a new fuzzy additive DEA model for evaluating the efficiency of a set of decision-making units (DMUs) with fuzzy inputs and outputs. The contribution of this paper is threefold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA, (2) we propose a new fuzzy additive DEA model derived from the ?-level approach and (3) we demonstrate the practical aspects of our model with two numerical examples and show its comparability with five different fuzzy DEA methods in the literature.

Suggested Citation

  • Adel Hatami-Marbini & Madjid Tavana & Ali Emrouznejad & Saber Saati, 2012. "Efficiency measurement in fuzzy additive data envelopment analysis," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 10(1), pages 1-20.
    • Handle: RePEc:ids:ijisen:v:10:y:2012:i:1:p:1-20
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    Citations

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    Cited by:

    1. Adel Hatami-Marbini & Zahra Ghelej Beigi & Hirofumi Fukuyama & Kobra Gholami, 2015. "Modeling Centralized Resources Allocation and Target Setting in Imprecise Data Envelopment Analysis," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 1189-1213, November.
    2. HATAMI-MARBINI, Adel & AGRELL, Per & AGHAYI, Nazila, 2013. "Imprecise data envelopment analysis for the two-stage process," LIDAM Discussion Papers CORE 2013004, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Mahmoudabadi, Mohammad Zarei & Emrouznejad, Ali, 2019. "Comprehensive performance evaluation of banking branches: A three-stage slacks-based measure (SBM) data envelopment analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 359-376.
    4. S. Mohammad Arabzad & Mazaher Ghorbani & Arash Shahin, 2013. "Ranking players by DEA the case of English Premier League," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 15(4), pages 443-461.
    5. Xiao-Li Meng & Liu-Tang Gong & Jen-Chih Yao, 2020. "A fuzzy evaluation approach with the quasi-ordered set: evaluating the efficiency of decision making units," Fuzzy Optimization and Decision Making, Springer, vol. 19(3), pages 297-310, September.
    6. Hashem Omrani & Arash Alizadeh & Ali Emrouznejad & Tamara Teplova, 2024. "Data envelopment analysis model with decision makers’ preferences: a robust credibility approach," Annals of Operations Research, Springer, vol. 339(3), pages 1269-1306, August.
    7. Utsav Pandey & Sanjeet Singh, 2022. "Data envelopment analysis in hierarchical category structure with fuzzy boundaries," Annals of Operations Research, Springer, vol. 315(2), pages 1517-1549, August.
    8. Cui, Qiang & Li, Xin-yi, 2021. "Investigating the Profit Pollution Abatement Costs difference before and after the “Carbon neutral growth from 2020” strategy was proposed," Research in Transportation Economics, Elsevier, vol. 90(C).

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