A novel method for forecasting the Malmquist productivity index by artificial neural network: Evidence from Iranian commercial bank
محورهای موضوعی : International Journal of Data Envelopment Analysis
Elsa Shokrollahpour
1
(Department of Industrial Management, Rudehen Branch, Islamic Azad University, Tehran, Iran)
Fariba Salahi
2
(Department of Industrial Management, Electronic Campus, Islamic Azad University, Tehran, Iran)
کلید واژه: Progress, Regress, Data Envelopment Analysis, Malmquist Productivity Index, Artificial Neural Network,
چکیده مقاله :
Banks are the most important part of today’s economy and society. Therefore, their performance and productivity measurement is crucial. This study attempts to calculate productivity change of one of the Iranian commercial banks for the five years period. The Malmquist productivity index was selected as measurement tool of efficiency and technical changes. In literature mostly a static form for calculating the Malmquist productivity index was available. As few studies have been conducted in dynamic form this, in this study the forecasted progress or regress for bank branches is calculated by integrating artificial neural network and Malmquist index. The results demonstrated that more branches’ productivity would progress in next sixty months.
