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Z-number network data envelopment analysis approach: A case study on the Iranian insurance industry

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  • Fatemeh Sadat Seyed Esmaeili
  • Emran Mohammadi

Abstract

The main aim of this research is to present an innovative method known as fuzzy network data envelopment analysis (FNDEA) in order to assess the performance of network decision-making units (DMUs) that possess a two-stage structure while taking into account the uncertainty of data. To attain this goal, we utilize various methodologies including the non-cooperative game (leader-follower) NDEA method, the concept of Z-number, credibility theory, and chance-constrained programming (CCP) to develop a model for the fuzzy NDEA approach. The FNDEA approach offers several advantages, such as the linearity of the presented FNDEA models, the ability to rank two-stage DMUs in situations of ambiguity, the provision of a unique efficiency decomposition method in an uncertain environment, and the capability to handle Z-information. To demonstrate the applicability and effectiveness of the proposed approach, we implement the Z-number network data envelopment analysis (ZNDEA) approach in assessing the performance of Iranian private insurance companies. The results of this implementation reveal that the proposed ZNDEA method is suitable and effective for measuring and ranking insurance companies in situations where data ambiguity is present.

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  • Fatemeh Sadat Seyed Esmaeili & Emran Mohammadi, 2024. "Z-number network data envelopment analysis approach: A case study on the Iranian insurance industry," PLOS ONE, Public Library of Science, vol. 19(7), pages 1-26, July.
    • Handle: RePEc:plo:pone00:0306876
    DOI: 10.1371/journal.pone.0306876
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    as
    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. Mohammad Khodabakhshi & Farhad Hosseinzadeh Lotfi & Kourosh Aryavash, 2014. "Review of Input Congestion Estimating Methods in DEA," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    3. Galagedera, Don U.A. & Roshdi, Israfil & Fukuyama, Hirofumi & Zhu, Joe, 2018. "A new network DEA model for mutual fund performance appraisal: An application to U.S. equity mutual funds," Omega, Elsevier, vol. 77(C), pages 168-179.
    4. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    5. Chen, Yao & Cook, Wade D. & Li, Ning & Zhu, Joe, 2009. "Additive efficiency decomposition in two-stage DEA," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1170-1176, August.
    6. Tavakoli, Ibrahim M. & Mostafaee, Amin, 2019. "Free disposal hull efficiency scores of units with network structures," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1027-1036.
    7. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    8. 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.
    9. Zhimin Huang & Susan Li, 2001. "Stochastic DEA Models With Different Types of Input-Output Disturbances," Journal of Productivity Analysis, Springer, vol. 15(2), pages 95-113, March.
    10. Meilin Wen & Linhan Guo & Rui Kang & Yi Yang, 2014. "Data Envelopment Analysis with Uncertain Inputs and Outputs," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    11. Pejman Peykani & Jafar Gheidar-Kheljani & Reza Farzipoor Saen & Emran Mohammadi, 2022. "Generalized robust window data envelopment analysis approach for dynamic performance measurement under uncertain panel data," Operational Research, Springer, vol. 22(5), pages 5529-5567, November.
    12. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    13. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    14. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    15. Madjid Tavana & Salman Nazari-Shirkouhi & Hamidreza Farzaneh Kholghabad, 2021. "An integrated quality and resilience engineering framework in healthcare with Z-number data envelopment analysis," Health Care Management Science, Springer, vol. 24(4), pages 768-785, December.
    16. Guo, Chuanyin & Zhu, Joe, 2017. "Non-cooperative two-stage network DEA model: Linear vs. parametric linear," European Journal of Operational Research, Elsevier, vol. 258(1), pages 398-400.
    17. Li, Haitao & Chen, Chialin & Cook, Wade D. & Zhang, Jinlong & Zhu, Joe, 2018. "Two-stage network DEA: Who is the leader?," Omega, Elsevier, vol. 74(C), pages 15-19.
    18. Pejman Peykani & Mehdi Namazi & Emran Mohammadi, 2022. "Bridging the knowledge gap between technology and business: An innovation strategy perspective," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-18, April.
    19. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    20. Mohammad Khodabakhshi & Farhad Hosseinzadeh Lotfi & Kourosh Aryavash, 2014. "Review of Input Congestion Estimating Methods in DEA," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, April.
    21. Meilin Wen & Linhan Guo & Rui Kang & Yi Yang, 2014. "Data Envelopment Analysis with Uncertain Inputs and Outputs," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-7, August.
    22. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    23. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.
    24. Dimitris Despotis & Gregory Koronakos & Dimitris Sotiros, 2016. "Composition versus decomposition in two-stage network DEA: a reverse approach," Journal of Productivity Analysis, Springer, vol. 45(1), pages 71-87, February.
    25. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    26. Olesen, Ole B. & Petersen, Niels Christian, 2016. "Stochastic Data Envelopment Analysis—A review," European Journal of Operational Research, Elsevier, vol. 251(1), pages 2-21.
    27. Reza Yazdanparast & Reza Tavakkoli-Moghaddam & Razieh Heidari & Leyla Aliabadi, 2021. "A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 611-631, June.
    28. Alireza Amirteimoori & Vincent Charles & Saber Mehdizadeh, 2023. "Stochastic data envelopment analysis in the presence of undesirable outputs," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 74(12), pages 2619-2632, December.
    29. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
    30. Chen, Zhongfei & Wanke, Peter & Antunes, Jorge Junio Moreira & Zhang, Ning, 2017. "Chinese airline efficiency under CO2 emissions and flight delays: A stochastic network DEA model," Energy Economics, Elsevier, vol. 68(C), pages 89-108.
    31. Huang, Tai-Hsin & Lin, Chung-I & Wu, Ruei-Cian, 2019. "Assessing the marketing and investment efficiency of Taiwan’s life insurance firms under network structures," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 132-147.
    32. Ya Chen & Yongjun Li & Qiwei Xie & Qingxian An & Liang Liang, 2014. "Data envelopment analysis with missing data: a multiple imputation approach," International Journal of Information and Decision Sciences, Inderscience Enterprises Ltd, vol. 6(4), pages 315-337.
    33. Cook, Wade D. & Liang, Liang & Zhu, Joe, 2010. "Measuring performance of two-stage network structures by DEA: A review and future perspective," Omega, Elsevier, vol. 38(6), pages 423-430, December.
    34. Ali RezaHoseini & Zahra Rahmani & Morteza BagherPour, 2022. "Performance evaluation of sustainable projects: a possibilistic integrated novel analytic hierarchy process-data envelopment analysis approach using Z-Number information," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3198-3257, March.
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