-استفاده از مدل FUZZY NSBM با در نظرگیری منابع مشترک و متغیرهای نامطلوب جهت ارزیابی عملکرد سیستم بانکداری جامع

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی صنایع، دانشگاه آزاد اسلامی واحد علوم تحقیقات تهران، ایران

2 گروه مهندسی صنایع دانشگاه آزاد اسلامی واحد علوم تحقیقات تهران، ایران

3 گروه ریاضیات، دانشگاه آزاد اسلامی واحد علوم تحقیقات تهران، ایران

4 گروه مهندسی صنایع ، دانشگاه آزاد اسلامی واحد علوم تحقیقات تهران، ایران

چکیده

با توجه به ورود اکثر بانک‌ها در فضای رقابتی بانکداری جامع به عنوان رویکردی مشتری‌محور و با هدف ارائه طیف وسیعی از خدمات مالی به گروه مشتریان تفکیک شده، ارزیابی عملکرد فرآیند کاری شعب بانک با این رویکرد حائز اهمیت است. با توجه به عدم قطعیت و مطلوبیت برخی شاخص‌ها و همچنین وجود منابع مشترک در فضای واقعی مدلسازی، هدف از این مقاله طراحی مدل فازی شبکه‌ای تحلیل پوششی داده‌ها با در نظرگرفتن همزمان متغیرهای نامطلوب و منابع مشترک و استفاده کاربردی از آن جهت اندازه‌گیری کارایی فرآیند ارائه خدمات بانکداری جامع است. نتایج نشان می‌دهد که شعب در هر کدام از فرآیندهای بانکداری جامع به چه صورت فعالیت دارند. میانگین کارایی کمتر سرویس‌‌دهی به مشتریان خرد بیانگر لزوم توجه بانک به ارائه سبد محصولات و خدمات اعتباری بهتر به آن‌ها است. مقایسه نتایج عملکرد شعب در هرکدام از فرآیندها می‌تواند در اتخاذ سیاست‌های تشویقی و تنبیهی مدیران نقش بسزائی ایفا نماید.

کلیدواژه‌ها


عنوان مقاله [English]

Using a Fuzzy NSBM Model with Shared Resources and Undesirable Variables for the Assessment of Universal Banking System

نویسندگان [English]

  • homa ghasemi 1
  • esmaeil najafi 2
  • farhad Hosseinzadeh Lotfi 3
  • farzad movahedi 4
1 Department of Industrial Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran.
2 Department of Industrial Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran.
3 Faculty of Department of Mathematics, Science and Research branch, Islamic Azad University, Tehran, Iran.
4 Faculty of Department of Industrial Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran.
چکیده [English]

With regard to the entry of most banks into the competitive environment of universal banking, as a customer-centric approach aiming to provide financial services to customer groups, it is important to assess the performance of the business process in bank branches using this approach. Due to the uncertainty and desirability of some indicators as well as the existence of shared resources in the real environment of modelling, this paper aims to design a network fuzzy data envelopment analysis (DAE) model, with the simultaneous consideration of undesirable variables and shared resources, and its practical use to measure the effectiveness of service delivery process in universal banking. The results indicate how the branches performed in each of the processes of universal banking. The lower mean efficiency of service provision to customers reflects the necessity for the bank to provide a portfolio of products and better credit services. Comparing the performance of branches in terms of each process can play an important role in the adoption of incentive and punitive policies for managers.

کلیدواژه‌ها [English]

  • α-cut
  • fuzzy NSBM data envelopment analysis model
  • shared resources
  • universal banking
Akther, S., Fukuyama, H., & Weber, W. L. (2013). Estimating two-stage network slacks-based inefficiency: An application to Bangladesh banking. Omega, 41, 88–96. DOI:10.1016/j.omega.2011.02.009
Amado, C.A.F., Santos, S.P., Marques, P.M. (2012). “Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment”. Omega 40, pp.390-403.  DOI:10.1016/j.omega.2011.06.006
Avkiran, N.K., (2009) “Opening the black box of efficiency analysis: An illustration with UAE banks”, Omega, 37 930-941 Doi:  10.22034/amfa.2019.582260.1165
BO, H., Ching, C.C., Yung, H.C. and Ching, R.C., (2011), “Using fuzzy super-efficiency slack-based measure data envelopment analysis to evaluate Taiwan’s commercial bank efficiency”, Expert Systems with Applications, Vol.38, pp.9147–9156. Doi:  10.22034/amfa.2019.582260.1165
Charnes, A., Cooper, W.W., Rhodes, E.L. (1978) “Measuring the efficiency of decision making units”, European Journal of Operational Research, 2(6), pp.429–444. doi:10.1016/0377-2217(78)90138-8
Chen, Y., Cook, W. D., Li, N., Zhu, J., (2009). Additive efficiency decomposition in two-stage DEA. European Journal of Operational Research, 196(3), 1170-1176. doi:10.3724/SP.J.1383.203008
Cook, W. D. & Seiford, L. M. (2009). “Data envelopment analysis (DEA) – Thirty years on”. European Journal of Operational Research, 192(1), pp.1–17.  doi:10.1016/j.ejor.2008.01.032
Cook, W.D. Hababou, M. Tuenter, H.J.H., (2000), "Multicomponent efficiency measurement and shared inputs in DEA: an application to sales and service performance in Bank branches”, Journal of Productivity Analysis, Volume 14, Issue 3, pp 209–224 doi:10.1016/j.ejor.2008.01.032
Ebrahimnejad, A., Tavana, M., Hosseinzadeh Lotfi, F., Shahverdi, R. and Yousefpour, M., (2014) “A three-stage Data Envelopment Analysis model with application to banking industry”, Measurement,49,pp.308-319.  DOI:10.1016/j.measurement.2013.11.043
Ebrahimzadeh Shermeh H., 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 vol. 112 pp. 686-697 DOI:10.1016/j.measurement.2013.11.043
Färe, R., Grosskopf, S, (2000) “Network DEA”. Socio-Economic Planning Sciences, 34(1), pp.35-49. doi:10.1016/S0038-0121(99)00012-9
Fukuyama H. and Weber W. L., (2010) “A slacks-based inefficiency measure for a two-stage system with bad outputs”, Omega, 38(5), pp. 398-409. Doi:10.3182/20130619-3-RU-3018.00048
Ghasemi H.; Najafi, E.; Hosseinzadeh Lotfi, F.; Movahedi-Sobhani, F., (2018). “Using multivariate analysis approaches in designing NSBM Model with considering undesirable variable and shared resources” International Journal of Science and Technology, DOI 10.24200/SCI.2018.5578.1392
Hatami-Marbini, A., Emrouznejad, A., &Tavana, M. 2011. “A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making”. European Journal of Operational Research 214, pp. 457–472 DOI:10.1016/j.ejor.2011.02.001
Hsiao Bo, Chern Ching-Chin, Chiu Yung-Ho, Chiu Ching-Ren. (2011), “Using fuzzy super-efficiency slack-based measure data envelopment analysis to evaluate Taiwan's commercial bank efficiency. Expert Syst Appl; 38(8):9147e56. DOI:10.1016/j.eswa.2011.01.075
Hsieh, L. F., & Lin, L. H. (2010). “A performance evaluation model for international tourist hotels in Taiwan-An application of the relational network DEA”. International Journal of Hospitality Management 29, pp.14-24. DOI:10.1108/14635771311307650
Huang J.H, Yang X.G., Cheng G. and Wang S. Y., (2014) “A Comprehensive Eco-efficiency Model and Dynamics of Regional Eco-efficiency in China”, Journal of Cleaner Production, 67, pp. 228-238. DOI:10.21203/rs.3.rs-489750/v1
Huang, J., Chen, J. and Yin, Z., (2014) “A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China”, Mathematical Problems in Engineering,pp.1-14. DOI:10.1155/2014/793192
Jafarian Moghaddam, A. R. & Ghoseiri, K. (2010) “Fuzzy Dynamic Multi-Objective Data Envelopment Analysis Model (FDM-DEA)”. Journal of Industrial Management, 2(4), pp.19-36. (In Persian) Doi:  10.22059/imj.2016.61711
Kahraman, C. and Tolga, E.,) 1998(, “Data envelopment analysis using fuzzy concept”. 28th International Symposium on MultipleValued Logic, pp.338–34. DOI:10.1007/978-3-642-41372-8-1
Kao, C. And Liu, S.T., (2014) “Multi-period efficiency measurement in data envelopment analysis: The case of Taiwanese commercial banks”, Omega, 47 90-98 DOI:10.1016/j.omega.2013.09.001
Kao, C. (2014b). Network data envelopment analysis: A review. European Journal of Operational Research, 239(1), pp.1-16. doi:10.1016/j.ejor.2014.02.039
Kao, C. and Liu, S.T., (2000), “Fuzzy efficiency measures in data envelopment analysis”, Fuzzy Sets and Systems, Vol. 113, No.3, pp.427–437. DOI:10.1016/S0165-0114(98)00137-7
Kao, C., Hwang, S.N. (2010). “Efficiency measurement for network systems: IT impact on firm performance”, Decision Support Systems 48, 3, pp.437–446. Doi:  10.24200/sci.2020.54619.3836
Kao, C., Hwang, S.N., (2010) “Efficiency measurement for network systems: IT impact on firm performance”, Decision Support Systems, 48 (3), pp.437–446. DOI:10.1007/s00170-013-5021-y
Khalili Damghani. K, Tavana. M. (2013). “A new fuzzy network data envelopment analysis model for measuring the performance of agility in supply chains”, Int J Adv Manuf Technol Vol 69. Pp.291–318 Doi: 10.1007/s10479-017-2540-1 ·
Kordrostami, S., Amirteimoori, A., (2005). “Un-desirable factors in multi-component performance measurement”. Applied Mathematics and Computation, 171(2), pp.; 721-729 DOI:10.1016/S0305-0548(03)00095-9
Kuo, H. C. (2001), “An interdisciplinary approach for modelling credit evaluation”, International Journal of Management, 18, 11–17.  DOI:10.1016/S0305-0548(03)00095-9
Lewis H.F and Sexton T. R., (2004) “Network DEA: efficiency analysis of organizations with complex internal structure”, Computers & Operations Research, 31(9), pp.1365-1410. DOI:10.1016/S0305-0548(03)00095-9
Lin, T.Y., Chiu, S.H., (2013) “Using independent component analysis and network DEA to improve bank performance evaluation”, Economic Modelling, 32, pp.608–616. DOI:10.1016/j.econmod.2013.03.003
Lozano, L., Gutiérrez, E., Moreno, P., (2013). "Network DEA approach to airports performance assessment considering undesirable outputs”. Applied Mathematical Modelling, 37(4), pp.1665-1676. DOI:10.1016/j.apm.2012.04.041
Olfat, L., Amiri, M., Soufi, J., Pishdar, M., (2016) “A dynamic network efficiency measurement of airports performance considering sustainable development concept: A fuzzy dynamic network-DEA approach”, “journal of Air Transport Management, 57, pp.272-29. DOI:10.1016/J.JAIRTRAMAN.2016.08.007
Salehi Sadaghiani, J., Amiri, M., Razavi, S. H., Hashemi, S. S. & Habibzadeh, A. (2009). “A Linear Goal Programming Model for Calculating Common Weights in Data Envelopment Analysis Problems”. Journal of Industrial Management, 1(2), pp.89-104. (In Persian) doi:10.1016/j.dajour.2021.100005
Seiford, L. M., Zhu, J., (2002). “Modeling undesirable factors in efficiency evaluation”. European Journal of Operational Research, 142(1), pp.16–20. DOI:10.7835/jcc-berj-2011-0061
Sengupta, J.K., (1972) “A fuzzy systems approach in data envelopment analysis”. Computers and Mathematics with Applications, Vol.24, pp.259–266. doi:10.1016/j.fss.2011.03.003
Sexton T. R. and Lewis H. F., (2003) "Two-stage DEA: An application to major league baseball,"Journal of Productivity Analysis, 19(2-3), pp.227-249. doi:10.1016/S1874-8651(10)60001-4
Tavassoli, M., Faramarzi, G.R., Farzipoor Saen, R., (2014), “Efficiency and effectiveness in airline performance using a SBM-NDEA model in the presence of shared input”, Journal of Air Transport Management 34, pp.146–153 DOI:10.1016/j.jairtraman.2013.09.001
Tone K., (2001), “A slacks-based measure of efficiency in data envelopment analysis”, European Journal of Operational Research, 130, pp.498-509. DOI:10.1016/S0377-2217(99)00407-5
Tone, K., Tsutsui, M., (2009) “Network DEA: a slacks-based measure approach. European Journal of Operational Research, 197 (1), pp.243–252. DOI:10.1016/j.ejor.2008.05.027
Wang, K, Huang, W, Wu, J, Liu, YN. (2014). Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA. Omega, 44, 5-20. DOI:10.1016/j.omega.2013.09.005
Wu, J., Zhu, Q., Ji, X., Chu, J. Liang, L., (2016), “Two-stage network processes with shared resources and resources recovered from undesirable outputs”, European Journal of Operational Research 251, pp. 182-197 DOI:10.1016/j.cie.2018.04.011
Yuan. G. Y., “Data envelopment analysis in fuzzy environment” (2001). Int J INF Manag Sci; 12(2):51e66 Doi: 10.1016/j.cam.2008.03.003
Zha, Y. and Liang, L., (2010) “Two-stage cooperation model with input freely distributed among the stages”, European Journal of Operational Research, 205 332-338 Doi: 10.3390/su131911060
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