An integrated data envelopment analysis–artificial neural network approach for benchmarking of bank branches

Journal of Industrial Engineering International

دوره 12، شماره 2، شهریور 2016   

نویسندگان

Elsa Shokrollahpour¹؛ Farhad Hosseinzadeh Lotfi^{* 2}؛ Mostafa Zandieh³

¹Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

²Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

³Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran

چکیده

Efficiency and quality of services are crucial to today’s banking industries. The competition in this section has become increasingly intense, as a result of fast improvements in Technology. Therefore, performance analysis of the banking sectors attracts more attention these days. Even though data envelopment analysis (DEA) is a pioneer approach in the literature as of an efficiency measurement tool and finding benchmarks, it is on the other hand unable to demonstrate the possible future benchmarks. The drawback to it could be that the benchmarks it provides us with, may still be less efficient compared to the more advanced future benchmarks. To cover for this weakness, artificial neural network is integrated with DEA in this paper to calculate the relative efficiency and more reliable benchmarks of one of the Iranian commercial bank branches. Therefore, each branch could have a strategy to improve the efficiency and eliminate the cause of inefficiencies based on a 5-year time forecast.

کلیدواژه‌ها

Data envelopment analysis . Artificial neural network . Benchmarking