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A fuzzy data envelopment analysis for clustering operating units with imprecise data

Author

Listed:
  • SAATI, Saber
  • HATAMI-MARBINI, Adel
  • TAVANA, Madjid
  • AGRELL, Per

Abstract

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Suggested Citation

  • SAATI, Saber & HATAMI-MARBINI, Adel & TAVANA, Madjid & AGRELL, Per, 2013. "A fuzzy data envelopment analysis for clustering operating units with imprecise data," LIDAM Reprints CORE 2465, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvrp:2465
    DOI: 10.1142/S0218488513500037
    Note: In : International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 21(1), 29-54, 2013
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    Cited by:

    1. Sakouvogui Kekoura & Shaik Saleem & Addey Kwame Asiam, 2020. "Cluster-Adjusted DEA Efficiency in the presence of Heterogeneity: An Application to Banking Sector," Open Economics, De Gruyter, vol. 3(1), pages 50-69, January.
    2. 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.
    3. Aparicio, Juan & Cordero, Jose M. & Ortiz, Lidia, 2019. "Measuring efficiency in education: The influence of imprecision and variability in data on DEA estimates," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    4. Nam Hyok Kim & Feng He & Kwon Ryong Hong & Hyok-Chol Kim & Sok-Min Han, 2024. "A new common weights DEA model based on cluster analysis," Operational Research, Springer, vol. 24(2), pages 1-35, June.

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