Economic Research and Perspectives

Economic Research and Perspectives

The Selection of Evaluation Indicators in Data Envelopment Analysis using Logistic Regression

Authors
Mohammad Rahim Ramazanian 1
Akram Oveysi Omran 2
Keykhosrow Yakideh 3
1 Associate Professor, Department of Management, University of Guilan, E-mail: m_ramazanian391@yahoo.com
2 PhD Candidate in Operations Research, University of Semnan, E-mail: akramoveysi@gmail.com
3 Assistant Professor, Department of Management, University of Guilan, E-mail: yakideh@yahoo.com
Abstract
Banks play substantial role in the national economy and its growth and prosperity. In this regard, recent researches have focused on performance evaluation of banks using “data envelopment analysis” (DEA). However, most of these studies has paid less attention to the selection of input and output variables. Obviously, the change in the variables set makes the efficiency scores and assessments of the decision-making units very different. Hence, in this paper, a logistic regression model is used in order to select the input and output variables. Applying this method indicates that the main variables of model are main source of financing as "input variable" and the bank facilities, resource absorption rate and number of bills as "output variables". These are of the greatest impact on forecasting of units efficiency (inefficiency). Then, we dealt with this set of variables to determine technical, allocative, and overall efficiency of 15 branches of Sepah Bank in Tehran during 2011. The results show that only 27 percent of units are 100% efficient, 20% of the units are 100% inefficient, 20% of units are allocatively inefficient and 34% of them are technically inefficient.
Keywords
Logistic regression
Technical efficiency
Allocative Efficiency
Overall Efficiency
جهانشاهلو، غلامرضا و حسین­زاده، فرهاد (1383) بازده به مقیاس در تحلیل پوششی داده­ها؛ جلد سوم، جزوه درسی (توزیع محدود)، دانشکده ریاضی دانشگاه تربیت معلم.
حبیب پور، کرم و صفری، رضا (1390) راهنمای جامع کاربرد SPSS در تحقیقات پیمایشی؛ تهران: انتشارات متفکران، چاپ چهارم.
Avkiran, N. K. (2001) Investigating technical and scale efficiencies of Australian universities through Data Envelopment Analysis; Socio-Economic planning Sciences 35: 57-80.
Banker, R.D. (1993) Maximum likelihood, consistency and data envelopment analysis: A statistical foundation; Management Science 39 (10): 1265-1273.
Banker, R.D. (1996) Hypothesis tests using data envelopment analysis; Journal of Productivity Analysis 7: 139-159.
Berger, A. & Humphrey, D. (1997) Efficiency of financial institutions: International survey and directions for future research; European Journal of Operational Research, 98: 175-212.
Boussofiane, A.; Dyson, R.G. & Thanassoulis, E. (1991) Applied data envelopment analysis; European Journal of Operational Research 52: 1-15.
Charnes, A.; Banker, R.D. & Cooper, W.W. (1984) Some Models for estimating technical and scale inefficiencies in Data Envelopment Analysis; Management science 30(9): 1078-1092.
Charnes, A.; Cooper, W.W. & Rhodes, E. (1978) Measuring the efficiency of decision making units; Eur. J. Oper. Res. 2: 429-444.
Cook, W.D. and Zhu, J. (2005) Modeling Performance Measurement, Applications and Implementation Issues in DEA; New York, springer.
Debreu, G. (1951), "The coefficient of resource utilization Econometrica", vol 19, pp. 92-273
Färe R, Grosskopf S, Lovell CAK. "Production frontiers". Cambridge University Press, )1994(, pp. 232.
Farrell, M. J. (1957) The measurement of productive efficiency; Journal of the Royal Statistical Society Series a, 120 (III): 253-281.
Field, A., Breakwell, G., Leeuw, J. D., Saris, W., Muircheartaigh, C., Schuman, H. and Meter, K. V. (2000) Discovering Statistics Using SPSS; SAGE Publications.
Golany, B. & Roll, Y. (1989) An application procedure for DEA; OMEGA 17 (3): 237-250.
Jenkins, L. & Anderson, M. (2003) A multivariate statistical approach to reducing the number of variables in data envelopment analysis; European Journal of Operational Research 147: 51-61.
Kittelson, S.A.C. )1993( Stepwise DEA: Choosing variables for measuring technical efficiency in Norwegian electricity distribution; Memorandum No. 06/93, Department of Economics, University of Oslo, Norway.
Klimberg, R. & Puddicombe, M. (1995) A multiple objective approach to data envelopment analysis; working paper 95-105, School of Management, Boston University, MA.
Koopmans, T. (1951), "An analysis of production as an efficient combination of activities", Activity analysis of production and allocation.
Nunamaker, T.R. (1985) Using data envelopment analysis to measure the efficiency of non-profit organizations: A critical evaluation; Managerial and Decision Economics 6 (1): 50-58.
Salinas-Jimenez, J. & Smith, P. (1996) Data envelopment analysis applied to quality in primary health care; Annals of Operations Research 67: 141-161.
Tone, K.; Cooper, W. W. & Seiford, L. M. (2007) Data Envelopment Analysis: A Comprehensive Text with Models; Applications. References and DEA-Solver Software. 2nd Edition. New York: Springer.
Wright, R.E. (1995) Logistic regression; In L.G. Grimm and P.R. Yarnold (Eds.), Reading and Understanding Multivariate Statistics. Washington, DC: American Psychological Association: 217-244.
Economic Research and Perspectives
Volume 14, Issue 3
Autumn 2014
Pages 121-140