Ranking bank branches using DEA and multivariate regression models

Reza Kiani Mavi, Reza Farzipoor Saen, Neda Kiani Mavi, Sina Saeid Taleshi and Zeinab Rezaei Majd

International Journal of Operational Research, 2015, vol. 24, issue 3, 245-261

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. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.inderscience.com/link.php?id=72230 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:24:y:2015:i:3:p:245-261

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().