Improving the Banks Shareholder Long Term Values by Using Data Envelopment Analysis Model
الموضوعات :
Mohammad Izadikhah
1
(Department of Mathematics, College of Science, Arak Branch, Islamic Azad University, Arak, Iran
P. O. Box: 38135/567)
الکلمات المفتاحية: Financial Assessment, Data envelopment analysis, Efficiency, Returns to Scale, Banking,
ملخص المقالة :
Given the rapid development of the banking sector, it is reasonable to expect that the performance of banks has become the centre of attention among bank managers, stakeholders, policy makers, and regulators. In order to maximizing the share-holders’ satisfactory level, two bank efficiency measurement approaches, i.e. the production approach and the user cost approach, which are financial evaluations, are employed. The evaluations are done by means of data envelopment analysis method. The proposed methodology is run on the 15 privet bank branches in Markazi province. By using this approach, four regions that show the various performances are obtained. In addition the status of returns to scale for each bank branch is calculated.
[1] Batir, T.E., D.A. Volkman, and B. Gungor, Determinants of bank efficiency in Turkey: Participation banks versus conventional banks. Borsa _Istanbul Review 2017, 17(2), P. 86-96.
[2] Akther, S., H. Fukuyama, and W.L. Weber, Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking. Omega, 2013. 41(1), P. 88-96.
[3] Ebrahimnejad, A., et al., A three-stage Data Envelopment Analysis model with application to banking industry. Measurement, 2014. 49, P. 308-319.
[4] Widiarto, I., A. Emrouznejad, and L. Anastasakis, Observing choice of loan methods in not-for-profit microfinance using data envelopment analysis. Expert Systems with Applications, 2017. 82, P. 278-290.
[5] Berger, A.N. and D.B. Humphrey, Efficiency of financial institutions: International survey and directions for future research. European journal of operational research, 1997. 98(2), P. 175-212.
[6] Beim, D.O. and C.W. Calomiris, Emerging financial markets. 2001, New York: Irwin Professional Pub.
[7] Eichengreen, B.J., Financial crises: and what to do about them. 2002, Oxford: Oxford University Press.
[8] Fiordelisi, F., Shareholder value efficiency in European banking. Journal of Banking & Finance, 2007, 31(7), P. 2151-2171.
[9] Hughes, J.P., et al., Do bankers sacrifice value to build empires? Managerial incentives, industry consolidation, and financial performance. Journal of Banking and Finance 2003, 27, P.417-447.
[10] Berger, A.N., D. Hancock, and D. Humphrey, Bank efficiency derived from the profit function. Journal of Banking & Finance, 1993, 17(2-3), P. 317-347.
[11] Dietsch, M. and A. Lozano-Vivas, How the environment determines banking efficiency: a comparison between French andSpanish industries. Journal of Banking & Finance, 2000, 24,P. 985-1004.
[12] Beccalli, E., Cross-country comparisons of efficiency: evidence from the UK and Italian investment firms. Journal of Banking& Finance, 2004, 28, P.1363-1383.
[13] Lozano-Vivas, A. and F. Pasiouras, The impact of non-traditional activities on the estimation of bank efficiency: internationalevidence. Journal of Banking & Finance 2010, 34, P.1436-1449.
[14] Chortareas, G.E., C. Girardone, and A. Ventouri, Financial freedom and bank efficiency: evidence from the European Union. Journal of Banking & Finance 2013, 37(4), P.1223-1231.
[15] Beccalli, E., B. Casu, and C. Girardone, Efficiency and stock performance in European Banking. Journal of Business Finance andAccounting 2006, 33, P.218-235.
[16] Gaganisa, C. and F. Pasiouras, Financial supervision regimes and bank efficiency: international evidence. Journal of Banking& Finance, 2013, 7(12), P. 5463-5475.
[17] Leire San-Jose, L., J.L. Retolazad, and J.T. Prunonosae, Efficiency in Spanish banking: A multistakeholder approach analysis. Int. Fin. Markets, Inst. and Money, 2014, 32, P.240-255.
[18] Freixas, X. and J.C. Rochet, Microeconomics of Banking. 1997, Cambridge, MA.: MIT Press.
[19] Hermes, N. and V.T.H. Nhung, The impact of financial liberalization on bank efficiency: evidence from Latin America and Asia. Applied Economics, 2010, 42(26), P.3351-3365.
[20] Coelli, T.J., et al., An introduction to efficiency and productivity analysis. 2005: Springer Science & Business Media.
[21] Isik, I. and M.K. Hassan, Efficiency, ownership and market structure, corporate control and governance in the Turkish banking industry. Journal of Business Finance & Accounting, 2003. 30(9-10), P.1363-1421.
[22] Wang, K., et al., Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA. Omega, 2010, 44, .P.5-20.
[23] Chen, X., M. Skully, and K. Brown, Banking efficiency in China: application of DEA to pre-and post-deregulation eras: 1993-2000. China Economic Review, 2005, 16, P.229-245.
[24] Avkiran, N.K. and H. Morita, Benchmarking firm performance from a multiple-stakeholder perspective with an application to Chinese banking. Omega, 2010, 38,P.501-508.
[25] Luo, D. and S. Yao, World financial crisis and the rise of Chinese commercial banks: an efficient analysis using DEA. Applied Financial Economics, 2010, 20, P.1515-1530.
[26] Avkiran, N.K., Association of DEA super-efficiency estimates with financial ratios: investigating the case for Chinese banks. Omega, 2011, 39, P.323-334.
[27] Feith, M.D. and F. Pasiouras, Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research, 2010, 204, P,189-198.
[28] Ohsatoa, S. and M. Takahashi, Management Efficiency in Japanese Regional Banks: A Network DEA. Procedia - Social and Behavioral Sciences, 2015, 172, P.511-518.
[29] Wanke, P., C.P. Barros, and A. Emrouznejad, Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banks. European Journal of Operational Research, 2016, 249(1), P.378-389.
[30] Hemmati, M., S.A. Dalghandi, and H. Nazari, Measuring relative performance of banking industry using a DEA and TOPSIS. Measurement Science Letters, 2013. 3(2): p. 499-503.
[31] Sherman, H.D. and F. Gold, Bank branch operating efficiency. Journal of Banking and Finance, 1985, 9,P.297-315.
[32] Parkan, C., Measuring the efficiency of service operations: an application to bank branches. Engineering Costs and Production Economics, 1997, 12, P. 237-242.
[33] Schaffnit, C., D. Rosen, and J.C. Paradi, Best practice analysis of bank branches: an application of DEA in a large canadian bank. European Journal of Operational Research, 1997, 98, P. 269-289.
[34] Oral, M. and R. Yolalan, An empirical study on measuring operating efficiency and profitability of bank branches. European Journal of Operational Research, 1990, 46, P.282-294.
[35] Tulkens, H., On FDH analysis: some methodological issues and applications to retail banking, courts, and urban transit. JournalofProductivityAnalysis, 1993, 4, P.183-210.
[36] Sherman, H.D. and G. Ladino, Measuring bank productivity using data envelopment analysis DEA. Interfaces, 1995, 25(2), P. 60-73.
[37] Halme, M., P. Korhonen, and J. Eskelinen, Non-convex value efficiency analysis and its application to bank branch sales evaluation. Omega, 2004, 48, P.10-18.
[38] Isik, I. and M.K. Hassan, Technical, scale and allocative efficiencies of Turkish banking industry. Journal of Banking & Finance, 2002, 26(4), P.719-766.
[39] Casu, B. and P. Molyneux, A comparative study of efficiency in European banking. Applied Economics, 2003, 35(17), P. 1865-1876.
[40] Ismail, F., M.S. Abd Majid, and A. Rossazana, R., Efficiency of Islamic and conventional banks in Malaysia. Journal of Financial Reporting and Accounting, 2013, 11(1), P. 92-107.
[41] Juo, J.C., T.T. Fu, and M.M. Yu, Non-oriented slack-based decompositions of profit change with an application to Taiwanese banking. Omega, 2012, 40(5), P. 550-561.
[42] Izadikhah, M., A. Saeidifar, and R. Roostaee, Extending TOPSIS in fuzzy environment by using the nearest weighted interval approximation of fuzzy numbers. Journal of Intelligent & Fuzzy Systems, 2014, 27, P.2725–2736.
[43] Glass, J.C., D.G. McKillop, and S. Rasaratnam, Irish credit unions: investigating performance determinants and the opportunity cost of regulatory compliance. J. Bank. Finance, 2010, 34(1), P. 67-76.
[44] Devaney, M. and W.L. Weber, Small-business lending and profit efficiency in commercial banking. J. Financ. Serv. Res. , 2002. 22(3), P. 225-246.
[45] Hsiao, H., et al., First financial restructuring and operating efficiency: evidence from Taiwanese commercial banks. J. Bank. Finance, 2010. 34(7), P. 1461-1471.
[46] Sturm, J.E. and B. Williams, Characteristics determining the efficiency of foreign banks in Australia. J. Bank. Finance, 2008, 32(11), P.2346-2360.
[47] Izadikhah, M., R. Farzipoor Saen, and K. Ahmadi, How to Assess Sustainability of Suppliers in the Presence of Dual-Role Factor and Volume Discounts? A Data Envelopment Analysis Approach. Asia-Pacific Journal of Operational Research, 2017, 34(3), P.1-25.
[48] Ahn, H. and M.H. Le, An insight into the specification of the input-output set for DEA-based bank efficiency measurement. Manag.Rev. Q., 2014, 64, P.3–37.
[49] Benston, G.L., Branch banking and economies of scale. J. Finance, 1965, 20(2), P.312-332.
[50] Sealey, C. and J.T. Lindley, Inputs, outputs and a theory of production and cost at depository financial institution. Journal of Finance, 1977, 32, P.1251-1266.
[51] Hancock, D., The financial firm: production with monetary and nonmonetary goods. J Polit Econ, 1985. 93(5), P. 859-880.
[52] Hancock, D., A model of the financial firm with imperfect asset and deposit elasticities. J Bank Financ, 1986, 10(1), P. 37-54.
[53] Hancock, D., A theory of production for the financial firm. 1991: Kluwer Academic Publisher, Norwell.
[54] Christensen, L.R. and D.W. Jorgenson, US real product and real factor input, 1929–1967. Rev Income Wealth, 1970, 16(1), P.19-50.
[55] Fixler, D.J. and K.D. Zieschang, User costs, shadow prices, and the real output of banks. In: Griliches Z (ed) Output measurement in the service sectors. 1992, Chicago: University of Chicago Press.
[56] Izadikhah, M. and R. Farzipoor Saen, A new data envelopment analysis method for ranking decision making units: an application in industrial parks. Expert Systems, 2015, 32(5), P. 598-608.
[57] Izadikhah, M., A Step by Step Method to Improve the Performance of Decision Making Units. Journal of Mathematical Extension, 2015, 9, P. 91-107.
[58] Charnes, A., W.W. Cooper, and E. Rhodes, Measuring the efficiency of decision making units. European Journal of Operational Research, 1978, 2(6), P.429-444.
[59] Banker, R.D., A. Charnes, and W.W. Cooper, Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 1984, 30(9), P.1078–1092.
[60] Forsund, F., On the calculation of scale elasticity in DEA models. Journal of Productivity Analysis, 1996, 7, P.283–302.
[61] Korhonen, P.J., M. Soleimani-damaneh, and J. Wallenius, Ratio-based RTS determination in weight-restricted DEA models. European Journal of Operational Research, 2011, 215, P.431–438.
[62] Fare, R., S. Grosskoph, and C.A.K. Lovell, The Measurement of Efficiency of production. 1985, Boston, USA: kluwer-Nijh off Publishing.
[63] Seiford, L.M. and J. Zhu, Profitability and Marketability of the Top 55 U.S. Commercial Banks. Management Science, 1999, 45(9), P.1270-1288.
[64] Dibachi, H., M.H. Behzadi, and M. Izadikhah, Stochastic Modified MAJ Model for Measuring the Efficiency and Ranking of DMUs. Indian Journal of Science and Technology, 2015, 8(8), P. 549–555.
[65] Dibachi, H., M.H. Behzadi, and M. Izadikhah, Stochastic multiplicative DEA model for measuring the efficiency and ranking of DMUs under VRS technology. Indian Journal of Science and Technology, 2014, 7(11), P.1765-1773.
