A DEA approach for ranking and optimisation of technical and management efficiency of a large bank based on financial indicators
Ali Azadeh,
Seyed Farid Ghaderi,
Maryam Mirjalili and
Mohsen Moghaddam
International Journal of Operational Research, 2010, vol. 9, issue 2, 160-187
Abstract:
This study presents a data envelopment analysis (DEA) approach for ranking and optimisation of branches of a large bank based on financial indicators. The effective financial indicators are evaluated by standard organisational and managerial assessment. Then, robust DEA models are applied to rank and optimise the organisation using output-oriented models to evaluate management and technical efficiency. The models are output-oriented because they are the primary decision variables in banking institutions. Principal components analysis (PCA) and numerical taxonomy (NT) are used and applied to verify and validate DEA findings. The superiority and applicability of the algorithm are shown for various branches of a large private bank in Iran. In summary, the unique features of this study are: (1) utilisation of DEA models for ranking and optimisation of technical and management efficiency in a large private bank. (2) utilisation of a robust PCA–NT approach for verification and validation of DEA approach. The proposed framework can be used to study the behaviour of financial operations in large banks.
Keywords: banking institutions; DEA; data envelopment analysis; DMU; decision making units; financial indicators; numerical taxonomy; optimisation; PCA; principal component analysis; large banks; technical efficiency; management efficiency; bank branches. (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=35043 (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:9:y:2010:i:2:p:160-187
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 ().