Evaluation of Performance of Personnel Units of Management in Mellat Bank with a Combined Approach of Window analysis Models and Malmquist Index
Subject Areas :
Industrial Management
Ezatolah Asgharizadeh
1
,
Masoud Keimasi
2
,
Elnaz Borji
3
1 - Associate professor of faculty of management of Tehran university Department of Industrial Management Iran
2 - Assistant professor of faculty of management of Tehran university Department of MBA Iran
3 - Masters of industrial management of faculty of management of Tehran university
Received: 2016-04-19
Accepted : 2017-01-17
Published : 2017-01-23
Keywords:
Abstract :
The purpose of this paper is to evaluate the performance of personnel units of five regions of Tehran Bank Mellat and investigating their productivity and efficiency by taking advantage of data envelopment analysis (DEA) efficiency as well as using Malmquist index. The study period is 2011-2015.In this study, we track the performance of every decision-making unit over time and to analyze the changes in efficiency and productivity as well as separation of efficiency over time and into two major components: technological developments and changes in efficiency by Malmquist Index and window analysis. The results show that human resources departments of regions 4 and 5, respectively, with 93% and 97% technical efficiency scores are in the first place, and the offices of regions 4 and 5 with the mean efficiency of about 95% have appropriate efficiency. Moreover, human resources departments of all regions with the average efficiency of over 95% are favorable. Based on Malmquist Index values among the regions, Region 3 (1.023) has had efficiency improve in during the study period, and evaluating total efficiency changes show that year 2012 (1.033) has had the greatest growth in productivity.
References:
Aggarwal, A., & Thakur, G. S. M. (2013). Techniques of performance appraisal-a review. International Journal of Engineering and Advanced Technology (IJEAT) ISSN, 2249-8958.
Asmild, M., Paradi, J. C., Aggarwall, V., & Schaffnit, C. (2004). Combining DEA window analysis with the Malmquist nidex approach in a study of the Canadian banking industry. Journal of Productivity Analysis, 21(1), 67-89.
Afkhami, M. (2008). Evaluate the performance of commercial banks in iran Combining DEA window analysis with the Malmquist index approach. Journal of Shahed University, 12, 2-47.
Afkhami,M. (2011).Calulate the productivity growth of human resources knowledge using Dynamic DEA models: Research institute of petroleum industry. Journal of human resources management in petroleum industry, 13.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
Chen, Y., & Ali, A. I. (2004). DEA Malmquist productivity measure: New insights with an application to computer industry. European Journal of Operational Research, 159(1), 239-249.
Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American economic review, 66-83.
Färe, R., Grosskopf, S., & Norris, M. (1997). Productivity growth, technical progress, and efficiency change in industrialized countries: The American Economic Review, 87(5), 1040-1044.
Pasiouras, E. & Sifodaskalakis, E.(2007).Total Factor Productivity Change of Gree Cooperative Banks (Master dissertation).University of Bath, Bath, Somerset, United Kingdom.
Popova, V. & Sharpanskykh, A. (2010). Modeling organizational performance indicators. Information Systems, 35(4), 505–527.
Řepková, I. (2014). Efficiency of the Czech Banking Sector Employing the DEA Window Analysis Approach. Procedia Economics and Finance, 12(6), 587–596.
Sokhanvar,M .,& Mehreghan, M.(2011).using DEA window to analyze the structure and assess the efficiency of electricity distribution companies in iran. journal of economicgrowth and development research, 4 ,161
Staněk, R. (2010). Efektivnost českého bankovního sektoru v letech 2000–2009. Konkurenceschopnost a stabilita, 1, 81-89.
Staníčková, M. I. C. H. A. E. L. A., & Skokan, K. A. R. E. L. (2012). Evaluation of Visegrad Countries Efficiency in Comparison with Austria and Germany by Selected Data Envelopment Analysis Models. In Proceedings of the 4th WSEAS World Multiconference on Applied Economics, Business and Development (AEBD’12). Recent Researches in Business and Economics. WSEAS, Porto.
Stavárek, D., & Řepková, I. (2014). Efficiency in the Czech banking industry: A non-parametric approach. Acta Universitatis Agriculturae ET Silviculturae Mendelianae Brunensis, 60(2), 357-366.
Malayi, M. (2011). Assess the efficiency of research and development centers using DEA WINDOW approach.3conferance on data development analysis
Hachazi, R., & Rostami, E. (2008).analyze the efficiency of export development bank of Iran productivity growth its branches using DEA. Journal of industrial management, 1, 29-50.
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Aggarwal, A., & Thakur, G. S. M. (2013). Techniques of performance appraisal-a review. International Journal of Engineering and Advanced Technology (IJEAT) ISSN, 2249-8958.
Asmild, M., Paradi, J. C., Aggarwall, V., & Schaffnit, C. (2004). Combining DEA window analysis with the Malmquist nidex approach in a study of the Canadian banking industry. Journal of Productivity Analysis, 21(1), 67-89.
Afkhami, M. (2008). Evaluate the performance of commercial banks in iran Combining DEA window analysis with the Malmquist index approach. Journal of Shahed University, 12, 2-47.
Afkhami,M. (2011).Calulate the productivity growth of human resources knowledge using Dynamic DEA models: Research institute of petroleum industry. Journal of human resources management in petroleum industry, 13.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
Chen, Y., & Ali, A. I. (2004). DEA Malmquist productivity measure: New insights with an application to computer industry. European Journal of Operational Research, 159(1), 239-249.
Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. The American economic review, 66-83.
Färe, R., Grosskopf, S., & Norris, M. (1997). Productivity growth, technical progress, and efficiency change in industrialized countries: The American Economic Review, 87(5), 1040-1044.
Pasiouras, E. & Sifodaskalakis, E.(2007).Total Factor Productivity Change of Gree Cooperative Banks (Master dissertation).University of Bath, Bath, Somerset, United Kingdom.
Popova, V. & Sharpanskykh, A. (2010). Modeling organizational performance indicators. Information Systems, 35(4), 505–527.
Řepková, I. (2014). Efficiency of the Czech Banking Sector Employing the DEA Window Analysis Approach. Procedia Economics and Finance, 12(6), 587–596.
Sokhanvar,M .,& Mehreghan, M.(2011).using DEA window to analyze the structure and assess the efficiency of electricity distribution companies in iran. journal of economicgrowth and development research, 4 ,161
Staněk, R. (2010). Efektivnost českého bankovního sektoru v letech 2000–2009. Konkurenceschopnost a stabilita, 1, 81-89.
Staníčková, M. I. C. H. A. E. L. A., & Skokan, K. A. R. E. L. (2012). Evaluation of Visegrad Countries Efficiency in Comparison with Austria and Germany by Selected Data Envelopment Analysis Models. In Proceedings of the 4th WSEAS World Multiconference on Applied Economics, Business and Development (AEBD’12). Recent Researches in Business and Economics. WSEAS, Porto.
Stavárek, D., & Řepková, I. (2014). Efficiency in the Czech banking industry: A non-parametric approach. Acta Universitatis Agriculturae ET Silviculturae Mendelianae Brunensis, 60(2), 357-366.
Malayi, M. (2011). Assess the efficiency of research and development centers using DEA WINDOW approach.3conferance on data development analysis
Hachazi, R., & Rostami, E. (2008).analyze the efficiency of export development bank of Iran productivity growth its branches using DEA. Journal of industrial management, 1, 29-50.