بررسی کارایی مدیریت بانک‌ها با استفاده از تکنیک DEA (مطالعۀ موردی شعب مختلف بانک‌های تهران)
محورهای موضوعی : مدیریت صنعتیمحمدرحیم رمضانیان 1 , کیخسرو یاکیده 2 , لعبت اخوان دیلمی 3
1 - دانشیارگروه مدیریت، دانشکده ادبیات و علوم انسانی، دانشگاه گیلان،ایران
2 - استادیار، دانشکده ادبیات و علوم انسانی، دانشگاه گیلان،ایران
3 - کارشناسی ارشد گروه مدیریت، دانشکده ادبیات و علوم انسانی، دانشگاه گیلان،ایران
کلید واژه: تحلیل پوششی داده‌ها, کارایی مدیریت, مدل جمعی, مدل جمعی شبکه‌ای,
چکیده مقاله :
بانک‌ها نهادهای مالی هستند که دارایی‌ها را از منابع گوناگون جمع‌آوری کرده و آنها را در اختیار بخش‌هایی قرار می‌دهند که به نقدینگی نیاز دارند. از این‌رو بانک‌ها شریآنهای حیاتی هر کشور محسوب می‌شوند. در این پژوهش برای ارزیابی کارایی از مدل تحلیل پوششی داده‌ها، علی رغم وجود محدودیت‌ها استفاده می‌شود. مدل‌های مرسوم تحلیل پوششی داده‌ها برای ارزیابی کارایی سازمآنها مبتنی بر رویداد جعبه سیاه می‌باشند، به‌گونه‌ای که ورودی‌ها در واحدهای تحت ارزیابی بدون توجه به مراحل میانجی تبدیل به خروجی می‌شوند، اما ازآنجایی‌که فرآیند ارائه خدمات در بانک‌ها از مراحل وابسته به هم تشکیل‌شده است. این پیوستگی باعث می‌شود در این پژوهش با استفاده از رویکرد تحلیل پوششی داده‌های شبکه‌ای، مدل اندازه‌گیری کارایی در بانک طراحی شود.بنابراین در این مقاله به‌منظور شناسایی ضعف‌های مدیریتی از طریق محاسبه کارایی به روش (مدل جمعی شبکه‌ای)و ارائه راه‌حل‌های ممکن، 19 شعبه از بانک‌های خصوصی استان تهران با استفاده از داده‌های سال 92 موردبررسی قرارگرفته‌اند. درواقع هدف اصلی این پژوهش محاسبه و ارزیابی کارایی کل و کارایی هر بخش از بانک‌ها می‌باشد. نتایج نشان می‌دهد که مدل‌های جمعی شبکه‌ای تعداد واحدهای کارایی کمتری را در مقایسه با مدل جمعی ساده دارند. هم‌چنین کارایی به‌دست‌آمده در مدل جمعی شبکه‌ای در مقایسه با مدل جمعی ساده مقدار دقیق‌تری را در اختیار مدیران قرار می‌دهد که بتوانند با شناسایی ناکارایی هر بخش ضعف‌های آن را برطرف نمایند.
Banks are considered as vital circulatory system of finance and financial institutions that collect assets from various sources and allocate them to sectors that need market liquidity. Despite existing limitations, the present enquiry aimed to examine the efficiency of bank management through the use of Data Envelopment Analysis Model. Typical Models of Data Envelopment Analysis employed in evaluation of organizational performance are based on the black box events, that is, the input into units under scrutiny converted into output regardless of the intermediate stages. However, providing bank services is a complex process comprising different interconnected stages and the interwoven stages involved necessitated the use of Network Data Envelopment Analysis, in the present study, to design a Bank Performance Measurement Model. Thus, the aim of this scrutiny was to identify managerial weaknesses by calculating the management efficiency using the Network Model and to offer viable solutions. To serve the purpose, the banking data accumulated in 19 private bank branches in Tehran during the year 2014 were surveyed to estimate both the overall efficiency and the efficiency of each bank segment. The findings indicated significantly lower levels of efficiency in Network Collective Models compared to Simple Collective Models. Also, the NSBM model rendered a more precise measure of efficiency in comparison to the SBM model which can enable managers to identify and rectify inefficiencies in each sector.
Azar,A.,Zarei Mahmoudabadi, M., Moghbel,A.,& khadivar,A. (2014), Evaluating the Productivity of a Bank's Branches Using Network Data Envelopment Analysis Approach(Case Study :A Bank in Guilan Province). Journal Of Monetary and Banking Research,7(20),285-305,(In Persian).
Azar,A., Zarei Mahmoodabadi, M.,& Tahari Mehrjardi, M.H.(2012), Prioritization Factors Effecting Productivity of Manpower in the Tile Industry by Combined Approach DEA and Multi Attribute Decision Making.Journal of Industrial Management Perspective,2(5),5-29,(In Persian).
Chang, K.C., Lin, C.-L., Cao, Y., & Lu, C.-F. (2011), Evaluating Branch Efficiency of a Taiwanese Bank Using Data Envelopment Analysis with an Undesirable Factor African Journal of Business Management, 5(8), 3220-3228.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978), Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444.
Chiu,Y. H., & Chen, Y. C. (2009), The Analysis of Taiwanese Bank Efficiency: Incorporating Both External Environment Risk and Internal Risk. Economic Modeling, 26(2), 456-463.
Drake, L., Hall, M. J., & Simper, R. (2006), The Impact of Macroeconomic and Regulatory Factors on Bank Efficiency: A Non-Parametric Analysis of Hong Kong’s Banking system. Journal of Banking & Finance, 30(5), 1443-1466.
Fare, R. & Grosskopf, S. (2000), Network DEA. Socio-Economic Planning Sciences, 34(1), 35-49.
Farrell, M. J. (1957), The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
Frei, F. X., & Harker, P. T. (1999), Measuring The Efficiency of Service Delivery Processes: an Application to Retail Banking. Journal of Service Research, 1(4), 300-312.
Fethi, M. D., & Pasiouras, F. (2010), Assessing Bank Efficiency and Performance with Operational Research and Artificial Intelligence Techniques: A survey. European Journal of Operational Research, 204(2), 189-198.
Halkos, G. E., & Salamouris, D. S. (2004), Efficiency Measurement of the Greek Commercial Banks with the Use of Financial Ratios: a Data Envelopment Analysis Approach. Management Accounting Research, 15(2), 201-224.
Holod, D., & Lewis, H. F. (2011), Resolving the Deposit Dilemma: A New DEA Bank Efficiency Model. Journal of Banking & Finance, 35(11), 2801-2810.
Hsieh, L. F., & Lin, L. H. (2010), A Performance Evaluation Model for International Tourist Hotels inTaiwan: An Application of the Relational Network DEA. International Journal of Hospitality Management, 29(1), 14-24.
Huang, C.-W., Chiu, Y. H., Lin, C.-H., & Liu, H.-H. (2012),, Using a Hybrid Systems Dea Model To Analyze The Influence Of Automatic Banking Service On Commercial Banks Efficiency. Journal of the Operations Research Society of Japan, 55(4), 209-224.
Jahanshahloo Gh., Hosseinzadeh F. (1385), An Introduction to Data Envelopment Analysis, Vol. 1, Unpublished Lesson. Faculty of Mathematics, University of Educational Sciences, (In Persian).
Kao, C., & Hwang, S. N. (2010), Efficiency Measurement for Network Systems: IT Impact on Firm Performance. Decision Support Systems, 48(3), 437-446.
Kazemizadeh,GH.,Mohammadi, E.,& Nazari,R. (2016), Evaluation of Private Banks Listed in The Stock Exchange Using the BSC Model and Fuzzy MADM Techniques. Productivity Mangement,10(36), 163-186, (In Persian).
Khalili Damghani,k., TaghaviFard,M.T.,& Karbaschi,K. (2016), A Hybrid Approach Based on Multi-Criteria Satisfaction Analysis (MUSA) and Three-stage Network Data Envelopment Analysis (DEA) to Evaluate the Relative Efficiency of Services in Iran Melli Bank Branches. Industrial Management Studies,14(40),75-109, (In Persian).
Mali, P. (1978), Improving Total Productivity: MBO Strategies for Business Government and Non Profit Organization: New York: John Wiley & Sons.
Matthews, K. (2013), Risk Management and Managerial Efficiency in Chinese Banks: a Network DEA Framework. Omega, 41(2),207-215.
Mehrabiyan,S.,Saati,S.,&Hadi,A.(2011), efficiency Assessment in Eghtesad Novin Bank Branches Using Hybrid of Artificial Neural Network and Data Envelopment Analysis. Journal of Operational Research in Its Applications 8(4),29-39, (In Persian).
Mehregan,MohammadReza.,(2013), Data Envelopment Analysis (Quantitative Models For Organizational Performance Evaluation, Publication of Academic books, Tehran, Second Edition,1-159, (In Persian).
Murphy, N. B., & Orgler, Y. E. (1982), Cost Analysis for Branching Systems: Methodology, Test results, and Implications for Management. Journal of Financial Research, 5(2), 181-188.
Noulas, A. G., Glaveli, N., & Kiriakopoulos, I. (2008), Investigating Cost Efficiency in the Branch Network of a Greek Bank: An Empirical study. Managerial Finance, 34(3), 160-171.
Ohsato, S., & Takahashi, M. (2015), Management Efficiency in Japanese Regional Banks: A Network DEA. Procedia-Social and Behavioral Sciences, 172, 511-518.
Tone, K. (2001), A Slacks-Based Measure of Efficiency in Data Envelopment Analysis. European Journal of Operational Research, 130(3), 498-509.
Tone, K. & Tsutsui, M. (2009), Network DEA: A slack-Based Measure Approach. European Journal of Operational Research, 197, 243-252.
Wang, K., Huang, W., Wu, J., & Liu, Y. N. (2014). Efficiency Measures of the Chinese Commercial Banking System Using an Additive Two-Stage DEA. Omega, 44, 5-20.
Salari ,M.,& Zandieh, M. (2016), Measuring the Efficiency of Internet Shops Using a Multi stages Data Envelopment Analysis (DEA) model. Management Research in Iran,20(3),127-151, (In Persian).
Schweser, C., & Temte, A. (2002), Schweser’s Study Notes: Financial Statement Analysis (Vol. 3). Kaplan Professional Company.
Sherman, H. D., & Gold, F. (1985), Bank Branch Operating Efficiency: Evaluation with Data Envelopment Analysis. Journal of banking & finance, 9(2), 297-315.
Usefi, SH.,Fahimi,M.,Mohammadi,D.,& Abdollahzadeh,A.A. (2014), Evaluation of Performance Branches of Melat Bank Using Hybrid Techniques DEA/AHP. Journal of Operational Research in Its Applications 11(3),109-123, (In Persian).
Yazdi,F.,& Moeinoldin,M. (2015), Ranking and Assessing the Efficiency of Insurance in Iran Using Dynamic Approach of Data Window Analysis,9(35),131-149, (In Persian)
_||_Azar,A.,Zarei Mahmoudabadi, M., Moghbel,A.,& khadivar,A. (2014), Evaluating the Productivity of a Bank's Branches Using Network Data Envelopment Analysis Approach(Case Study :A Bank in Guilan Province). Journal Of Monetary and Banking Research,7(20),285-305,(In Persian).
Azar,A., Zarei Mahmoodabadi, M.,& Tahari Mehrjardi, M.H.(2012), Prioritization Factors Effecting Productivity of Manpower in the Tile Industry by Combined Approach DEA and Multi Attribute Decision Making.Journal of Industrial Management Perspective,2(5),5-29,(In Persian).
Chang, K.C., Lin, C.-L., Cao, Y., & Lu, C.-F. (2011), Evaluating Branch Efficiency of a Taiwanese Bank Using Data Envelopment Analysis with an Undesirable Factor African Journal of Business Management, 5(8), 3220-3228.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978), Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444.
Chiu,Y. H., & Chen, Y. C. (2009), The Analysis of Taiwanese Bank Efficiency: Incorporating Both External Environment Risk and Internal Risk. Economic Modeling, 26(2), 456-463.
Drake, L., Hall, M. J., & Simper, R. (2006), The Impact of Macroeconomic and Regulatory Factors on Bank Efficiency: A Non-Parametric Analysis of Hong Kong’s Banking system. Journal of Banking & Finance, 30(5), 1443-1466.
Fare, R. & Grosskopf, S. (2000), Network DEA. Socio-Economic Planning Sciences, 34(1), 35-49.
Farrell, M. J. (1957), The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
Frei, F. X., & Harker, P. T. (1999), Measuring The Efficiency of Service Delivery Processes: an Application to Retail Banking. Journal of Service Research, 1(4), 300-312.
Fethi, M. D., & Pasiouras, F. (2010), Assessing Bank Efficiency and Performance with Operational Research and Artificial Intelligence Techniques: A survey. European Journal of Operational Research, 204(2), 189-198.
Halkos, G. E., & Salamouris, D. S. (2004), Efficiency Measurement of the Greek Commercial Banks with the Use of Financial Ratios: a Data Envelopment Analysis Approach. Management Accounting Research, 15(2), 201-224.
Holod, D., & Lewis, H. F. (2011), Resolving the Deposit Dilemma: A New DEA Bank Efficiency Model. Journal of Banking & Finance, 35(11), 2801-2810.
Hsieh, L. F., & Lin, L. H. (2010), A Performance Evaluation Model for International Tourist Hotels inTaiwan: An Application of the Relational Network DEA. International Journal of Hospitality Management, 29(1), 14-24.
Huang, C.-W., Chiu, Y. H., Lin, C.-H., & Liu, H.-H. (2012),, Using a Hybrid Systems Dea Model To Analyze The Influence Of Automatic Banking Service On Commercial Banks Efficiency. Journal of the Operations Research Society of Japan, 55(4), 209-224.
Jahanshahloo Gh., Hosseinzadeh F. (1385), An Introduction to Data Envelopment Analysis, Vol. 1, Unpublished Lesson. Faculty of Mathematics, University of Educational Sciences, (In Persian).
Kao, C., & Hwang, S. N. (2010), Efficiency Measurement for Network Systems: IT Impact on Firm Performance. Decision Support Systems, 48(3), 437-446.
Kazemizadeh,GH.,Mohammadi, E.,& Nazari,R. (2016), Evaluation of Private Banks Listed in The Stock Exchange Using the BSC Model and Fuzzy MADM Techniques. Productivity Mangement,10(36), 163-186, (In Persian).
Khalili Damghani,k., TaghaviFard,M.T.,& Karbaschi,K. (2016), A Hybrid Approach Based on Multi-Criteria Satisfaction Analysis (MUSA) and Three-stage Network Data Envelopment Analysis (DEA) to Evaluate the Relative Efficiency of Services in Iran Melli Bank Branches. Industrial Management Studies,14(40),75-109, (In Persian).
Mali, P. (1978), Improving Total Productivity: MBO Strategies for Business Government and Non Profit Organization: New York: John Wiley & Sons.
Matthews, K. (2013), Risk Management and Managerial Efficiency in Chinese Banks: a Network DEA Framework. Omega, 41(2),207-215.
Mehrabiyan,S.,Saati,S.,&Hadi,A.(2011), efficiency Assessment in Eghtesad Novin Bank Branches Using Hybrid of Artificial Neural Network and Data Envelopment Analysis. Journal of Operational Research in Its Applications 8(4),29-39, (In Persian).
Mehregan,MohammadReza.,(2013), Data Envelopment Analysis (Quantitative Models For Organizational Performance Evaluation, Publication of Academic books, Tehran, Second Edition,1-159, (In Persian).
Murphy, N. B., & Orgler, Y. E. (1982), Cost Analysis for Branching Systems: Methodology, Test results, and Implications for Management. Journal of Financial Research, 5(2), 181-188.
Noulas, A. G., Glaveli, N., & Kiriakopoulos, I. (2008), Investigating Cost Efficiency in the Branch Network of a Greek Bank: An Empirical study. Managerial Finance, 34(3), 160-171.
Ohsato, S., & Takahashi, M. (2015), Management Efficiency in Japanese Regional Banks: A Network DEA. Procedia-Social and Behavioral Sciences, 172, 511-518.
Tone, K. (2001), A Slacks-Based Measure of Efficiency in Data Envelopment Analysis. European Journal of Operational Research, 130(3), 498-509.
Tone, K. & Tsutsui, M. (2009), Network DEA: A slack-Based Measure Approach. European Journal of Operational Research, 197, 243-252.
Wang, K., Huang, W., Wu, J., & Liu, Y. N. (2014). Efficiency Measures of the Chinese Commercial Banking System Using an Additive Two-Stage DEA. Omega, 44, 5-20.
Salari ,M.,& Zandieh, M. (2016), Measuring the Efficiency of Internet Shops Using a Multi stages Data Envelopment Analysis (DEA) model. Management Research in Iran,20(3),127-151, (In Persian).
Schweser, C., & Temte, A. (2002), Schweser’s Study Notes: Financial Statement Analysis (Vol. 3). Kaplan Professional Company.
Sherman, H. D., & Gold, F. (1985), Bank Branch Operating Efficiency: Evaluation with Data Envelopment Analysis. Journal of banking & finance, 9(2), 297-315.
Usefi, SH.,Fahimi,M.,Mohammadi,D.,& Abdollahzadeh,A.A. (2014), Evaluation of Performance Branches of Melat Bank Using Hybrid Techniques DEA/AHP. Journal of Operational Research in Its Applications 11(3),109-123, (In Persian).
Yazdi,F.,& Moeinoldin,M. (2015), Ranking and Assessing the Efficiency of Insurance in Iran Using Dynamic Approach of Data Window Analysis,9(35),131-149, (In Persian)