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Fuzzy Ranking Network DEA with General Structure

Author

Listed:
  • Plácido Moreno

    (School of Engineering, Universidad de Sevilla, E41092 Seville, Spain)

  • Sebastián Lozano

    (School of Engineering, Universidad de Sevilla, E41092 Seville, Spain)

Abstract

This paper extends two fuzzy ranking data envelopment analysis (DEA) approaches to the case of general networks of processes. The first approach provides an efficiency score for each possibility level which requires solving one linear program for each possibility level. The second approach is even simpler and provides an overall efficiency score solving just one linear program. The proposed approaches are tested on two datasets from the literature and compared with other fuzzy network DEA approaches. The results show that the two methods provide very highly correlated efficiency estimates which are also consistent with those of other fuzzy network DEA approaches.

Suggested Citation

  • Plácido Moreno & Sebastián Lozano, 2020. "Fuzzy Ranking Network DEA with General Structure," Mathematics, MDPI, vol. 8(12), pages 1-18, December.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:12:p:2222-:d:461830
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    References listed on IDEAS

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    1. Kao, Chiang, 2009. "Efficiency decomposition in network data envelopment analysis: A relational model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 949-962, February.
    2. Plácido Moreno & Sebastián Lozano, 2014. "A network DEA assessment of team efficiency in the NBA," Annals of Operations Research, Springer, vol. 214(1), pages 99-124, March.
    3. Olfat, Laya & Amiri, Maghsoud & Bamdad Soufi, Jahanyar & Pishdar, Mahsa, 2016. "A dynamic network efficiency measurement of airports performance considering sustainable development concept: A fuzzy dynamic network-DEA approach," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 272-290.
    4. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    5. Hatami-Marbini, Adel & Emrouznejad, Ali & Tavana, Madjid, 2011. "A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making," European Journal of Operational Research, Elsevier, vol. 214(3), pages 457-472, November.
    6. Kaoru Tone & Miki Tsutsui, 2014. "Slacks-Based Network DEA," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 231-259, Springer.
    7. Sebastian Lozano & Belarmino Adenso-Diaz, 2018. "Network DEA-based biobjective optimization of product flows in a supply chain," Annals of Operations Research, Springer, vol. 264(1), pages 307-323, May.
    8. Mirhedayatian, Seyed Mostafa & Azadi, Majid & Farzipoor Saen, Reza, 2014. "A novel network data envelopment analysis model for evaluating green supply chain management," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 544-554.
    9. Lozano, Sebastián, 2016. "Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector," Omega, Elsevier, vol. 60(C), pages 73-84.
    10. EMROUZNEJAD, Ali & TAVANA, Madjid & HATAMI-MARBINI, Adel, 2014. "The state of the art in fuzzy data envelopment analysis," LIDAM Reprints CORE 2543, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Shermeh, H. Ebrahimzadeh & Najafi, S.E. & Alavidoost, M.H., 2016. "A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies," Energy, Elsevier, vol. 112(C), pages 686-697.
    12. Kaveh Khalili-Damghani & Behnam Taghavifard, 2013. "Sensitivity and stability analysis in two-stage DEA models with fuzzy data," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 17(1), pages 1-37.
    13. Cook, Wade D. & Zhu, Joe & Bi, Gongbing & Yang, Feng, 2010. "Network DEA: Additive efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1122-1129, December.
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    Cited by:

    1. Kaiyang Zhong & Chenglin Li & Qing Wang, 2021. "Evaluation of Bank Innovation Efficiency with Data Envelopment Analysis: From the Perspective of Uncovering the Black Box between Input and Output," Mathematics, MDPI, vol. 9(24), pages 1-18, December.

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