Title: Ranking bank branches using DEA and multivariate regression models

Authors: Reza Kiani Mavi; Reza Farzipoor Saen; Neda Kiani Mavi; Sina Saeid Taleshi; Zeinab Rezaei Majd

Addresses: Department of Industrial Management, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University (IAU), Nokhbegan Street, Qazvin, 34185-1416, Iran ' Department of Industrial Management, Faculty of Management and Accounting, Karaj Branch, Islamic Azad University (IAU), Imam Ali Complex, Moazen Blvd, Karaj, 31485-313, Iran ' Department of Physical Education and Sport Science, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University (IAU), Nokhbegan Street, Qazvin, 34185-1416, Iran ' Department of Industrial Management, Sohrevardi University, Imam Khomeini Street, Qazvin, Iran ' Department of Medical Sciences, Qazvin University of Medical Sciences, Bahonar Street, Qazvin, 34197-59811, Iran

Abstract: Service companies continually seek improved methods to measure the performance of their organisations because they are committed to improve efficiency and effectiveness in their operating units. Managers generally regard conventional methods inadequate. DEA has proven itself to be both theoretically sound framework for performance measurement and an acceptable method by those being measured. This paper assesses bank branches efficiency using DEA technique and multivariate regression techniques. Here, we proposed two multivariate regression models. In model (1), we used the exact data and in model (2), we used weighted data for fitting the regression equation. Weights were attributed to input variables based on group analytic hierarchy process. The efficiency of this approach is tested with application in bank branches. According to the results, weighted multivariate regression model has more advantages over conventional methodologies. LINGO software is used for obtaining efficiency scores in DEA.

Keywords: data envelopment analysis; DEA; multivariate regression modelling; weighted multivariate regression; bank efficiency; ranking; banking industry; bank branches; performance measurement; group AHP; analytical hierarchy process.

DOI: 10.1504/IJOR.2015.072230

International Journal of Operational Research, 2015 Vol.24 No.3, pp.245 - 261

Received: 22 Nov 2012
Accepted: 07 Oct 2013

Published online: 06 Oct 2015 *

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