نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مدیریت مالی، دانشکده مدیریت، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران، تهران، ایران

2 استاد،گروه برنامه ریزی و مدیریت، پژوهشکده مطالعات مدیریت و توسعه فناوری، دانشگاه تربیت مدرس، تهران، ایران.

3 استادیار،گروه اجرایی و کسب و کار، دانشکده مدیریت و حسابداری، دانشگاه آزاد اسلامی،واحد اسلامشهر، تهران، ایران.

چکیده

بانک‌ها به‌عنوان بازیگران اصلی بازار پول، نهادهای مالی هستند که با جمع‌آوری پس‌اندازها و نقدینگی‌های سرگردان و روانه آن به بخش‌های مهم اقتصادی، روند تولید و رشد اقتصادی را تسریع می‌نمایند. در این مؤسسات نیز هرگونه تلاشی در جهت ارزیابی کارایی و به طبع آن بهبود بهره‌وری، از جمله اولین اقدامات مهم مدیریتی محسوب می‌گردد که بازدهی کارکرد آنها را بهبود می‌بخشد. اما به دلیل تنوع شاخص‌ها و معیارهای ورودی و خروجی مورداستفاده در تعیین کارایی آنها، لازم است که باتوجه‌به معیارهای معین و مناسبی، این شاخص‌ها شناسایی و مورداستفاده قرار گیرد. ازاین‌رو در این مطالعه با به‌کارگیری یک روش تحلیلی - توصیفی و جمع‌آوری داده‌هایی به روش اسنادی و میدانی برای سال‌های 1399-1394، شاخص‌های مؤثر بر ارزیابی کارایی بانک‌های تجاری ایران از دیدگاه جمعی از خبرگان و اولویت‌بندی آنها بر اساس تحلیل عاملی و دلفی فازی شناسایی گردید. نتایج حاصل از این بررسی نشان داد که تعداد 19 عامل اصلی تعیین‌کننده کارایی بانکی قابل‌شناسایی است که در 7 گروه اصلی می‌توان آنها را طبقه‌بندی نمود. این عوامل به ترتیب به عوامل مالی، انسانی، محیطی و جغرافیایی، ساختاری و سازمانی، فیزیکی، فنی و در نهایت نسبت‌های مالی تقسیم می‌شوند که روی‌هم 45/62 درصد از واریانس کل را تعیین می‌نمایند که به‌عنوان مؤثرترین نهاده و یا ستانده، می-توانند که کارایی بانک‌های تجاری در ایران را تبیین و تعیین نماید.

کلیدواژه‌ها

عنوان مقاله [English]

Identification and Prioritization of Banks' Efficiency Evaluation Indicators Using Factor Analysis and Fuzzy Delphi Method

نویسندگان [English]

  • Sajjad Jalali 1
  • Ali Asghar Anvary Rostamy 2
  • Jalal Seifoddini 3

1 PhD student, Department of Financial Management, Faculty of Management, Islamic Azad University, Tehran Science and Research Unit, Tehran, Iran

2 Prof.Department of Management & Planning, Iran Management Study & Technology Development Center,Tarbiat Modares University, Tehran, Iran.

3 Assistant professor, Islamic Azad University, Eslamshar Branch , Tehran, Iran.

چکیده [English]

Banks, as key participants in the financial market, play a crucial role in expediting production processes and driving economic growth. They achieve this by gathering savings and idle liquidity, and channeling these resources into vital economic sectors. Enhancing efficiency and performance is a primary management objective for these institutions, as it leads to improved productivity. However, given the multitude of indicators and criteria used to assess efficiency, it is essential to identify and employ appropriate indicators based on specific guidelines. This study adopts an analytical-descriptive approach, collecting data from 2014 to 2019 through documentary research and surveys. The goal is to identify the influential indicators for evaluating the efficiency of commercial banks in Iran, as determined by a panel of experts. These indicators are then prioritized using factor analysis and the Fuzzy Delphi method. The findings reveal the existence of 19 key factors that determine bank efficiency, categorized into 7 main groups. These factors encompass financial, human, environmental and geographical, structural and organizational, physical, technical, and financial ratios. Together, they account for 62.45% of the total variance and serve as the most significant inputs and outputs that explain and determine the efficiency of commercial banks in Iran.

کلیدواژه‌ها [English]

  • Performance evaluation
  • efficiency
  • factor analysis
  • fuzzy Delphi
  • banking system
[1] Saatian, A., Hamedi, O. & Hosseini Dust, E. The effect of financial repression policy on credit risk taking in iranian banking system. Financial Management Strategy, 9(3), 2021, 103-122. Doi: 2020.28701.2236JFM1. [In Persian]
[2] Aghaei, M., & Qolizad, R. Investigating effective factors on overdue and overdue claims of selected branches of sepah bank. Islamic Banking and Financial Studies, 2(3), 2016, 95-111. [In Persian]
[3] Milenkovic, N., Radovanov, B. Kalaš, B. & Horvat, A.M. External two stage DEA analysis of bank efficiency in west Balkan countries. Sustainability, 14, 2022, 978. doi: 10.3390/su14020978.
[4]  Fallah Jelodar, M. Prioritization of the Factors Affecting Bank Efficiency Using Combined Data Envelopment Analysis and Analytical Hierarchy Process Methods. Hindawi Publishing Corporation. Journal of Optimization. 2016.Article ID 5259817, 7. doi: 10.1155/2016/5259817 [In Persian]
[5] Wanke P., Barros, C. Efficiency drivers in Brazilian insurance: A two-stage DEA meta frontier-data mining approach. Economic Modelling, 53 (2016), 8–22. doi: 10.1016/j.econmod.2015.11.005
[6] Maziki, A., Khatami Firouzabadi, M. & Bamdad Sofi, J. A model to evaluate efficiency of decision-making units using data envelopment analysis and ideal planning (case study: government counters of iran health insurance organization). Khatam New Management Research, 1(2), 2017, 145-186. [In Persian]
[7] Sepherdoost, H., Afshari, F. The effect of financial development and the granting of bank facilities on the total productivity of production factors in the industry sector. Quarterly Journal of Applied Economic Studies of Iran. 20, 2015, 221-251. [In Persian]
[8] Emami Meybodi, A. Basics of efficiency and productivity measurement (scientific-practical) (2nd ed.). Tehran: Business Studies and Research Institute. 2016. [In Persian]
[9] Ngo, T., & Le, T. Capital market development and bank efficiency: A cross-country analysis. International Journal of Managerial Finance, 15(4), 2019, 478-491.  doi: 10.1108/IJMF-02-2018-0048
[10] Alhadeff, D. Monopoly and Competition in Banking; University of California Press: Berkeley, CA, USA; 1954, 65, 323.
[11] Basso, A., Francesco, C. & Funari, S. How well is the museum performing? A joint use of DEA and BSC to measure the performance of museums, Omega, 81(10), 2018, 67-84. doi: 10.1016/j.omega.2017.09.010
[12] Ehtesham Rathi, R. & Naji, I. Evaluation of organizational performance using two integrated approaches DEA-BSC and ANN-DEA. Development and Transformation Management, 43, 2020, 91-101. [In Persian]
[13] Berger, A.N. & Humphrey, D.B. Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, 98(2), 1997, 175-212. doi: 10.2139/ssrn.2140
[14] Barati, S. & Lorestani, A. Investigating management factors in banks. new researches in management, economics and accounting ntional conference. Berlin, Germany, 2017. [In Persian]  
[15] Bernardo, M.  & Madeira de Souza., M.A., Lopes, R.S.N. Rodrigues, L.F. University library performance management: Applying zero-sum gains DEA models to resource allocation, Socio-Economic Planning Sciences, Article in press. 2020. [In Persian]
[16] Umar, M. Ji, X. Mirza, N. & Rahat, N. The impact of resource curse on banking efficiency: Evidence from twelve oil producing countries‏. Resources Policy, 72, 2021. doi: 10.1016/j.resourpol.2021.102080
[17] Banerjee, B. Banking sector efficiency in new EU member states: a survey. Prikazi in Analize, 18(3), 2012, 1-38. doi:10.2753/EEE0012-8775500604
[18] Fethi,D. & Pasiouras, F. Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operations Ressearch, 204(2), 2010, P 189–198. doi: 10.1016/j.ejor.2009.08.003
[19] Burgstaller, J. Retail-bank efficiency: Nonstandard goals and environmental determinants. Wily online library, 91(2), 2020, 87-99. doi: 10.1111/apce.12270
[20] Ahen, H. & Le, M.H. An insight into the specification of the input-output set for DEA-based bank efficiency measurement. Quarterly Journal OF Management Review, 64, 2014, 3–37. doi: 10.1007/s11301-013-0098-9
[21] Yaghoubi, A. Fazli, S. Proposing a model to forecast the efficiency of bank branches under uncertainty conditions based on SDEA-PCA approach and monte carlo simulation.  Quarterly Journal of Modern Researches in Decision Making, 6(4), 2021, 1-33. doi: 20.1001.1.24766291.1400.6.4.1.5 [In Persian]
[22] Hosseinzadeh Saljooghi, F. & Zaker Harofte, E. Evaluation of cost-effectiveness and cost efficiency of network systems case study: Bank branches. Quarterly Journal of Modern Researches in Decision Making. 6(1), 2021, 22-42. doi: 20.1001.1.24766291.1400.6.1.2.0 [In Persian]
[23] Hamidi, N. Akbari Shemirani, R. & Fazli, S. Identifying inefficient bank branches using DEA and use of integrated strategies in order to increase performance branches. Quarterly Journal of Management Research in Iran. 15(3), 2011, 87-103. doi: 20.1001.1.2322200.1390.15.3.4.8 [In Persian]
[24] Azadeh, O. Azar, A. Dehghan Nayeri, M.A. Moghbel. Developing a network data envelopment analysis approach to compare the environmental efficiency of active industries in Tehran. Quarterly Journal of Management Research in Iran. 25(3), 2021, 193-216. doi: 20.1001.1.2322200.1400.25.3.8.2 [In Persian]
[25] Anwar Al-Gasaymeh. Bank efficiency determinant: Evidence from the gulf cooperation council countries. Research in International Business and Finance, 38(C), 2016, 214-223. doi: 10.1016/j.ribaf.2016.04.018
[26] Ponary, M.A. Four Essays on Efficiency and Productivity in Swedish Banking, Kompendiet, Goteborg. 1999. Doctoral Theses from University of Gothenburg/ Doktorsavhandlingar Från Göteborgs Universitet.
[27] Yousefi, M. Ranking of Iranian banks based on financial parameters and using fuzzy AHP and TOPSIS. Monetary and Banking Research Quarterly,11(35), 2018, 25-54. [In Persian]
[28] Pirasteh, A., & Heydarnia, A. Exploraty factor analysis of questionnaires of pshychosocial factors effective on physical activity among iranian adolescent girls. Scientific Journal of Islamic Republic of Iran Medical Organization, 26(4), 2007, 474-485. [In Persian]
[29] Tavakoli, H. Fayaz, M. & Hassannejad, M. Investigating the performance of rangeland projects in Razavi Khorasan province with fuzzy delphi approach and multicriteria decision making models. Journal of Agricultural Economics and Development, 27(1), 2013, 37-50. Doi: 10.22067/JEAD2.V0I0.24251. [In Persian]
 [30] Houman, H. Structural equation modelling using LISREL. Organization of Study and Development of Human Sciences Textbooks. 2008. ISBN : 978-964-459-962-0 SAMT Publication. . [In Persian]