Ranking of bank branches with undesirable and fuzzy data: A DEA-based approach

Authors

Abstract:

Banks are one of the most important financial sectors in order to the economic development of each country. Certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. Sometimes the performance of banks must be measured in the presence of undesirable and vague factors. For these reasons in the current paper a procedure based on data envelopment analysis (DEA) is introduced for evaluating the efficiency and complete ranking of decision making units (DMUs) where undesirable and fuzzy measures exist. To illustrate, in the presence of undesirable and fuzzy measures, DMUs are evaluated by using a fuzzy expected value approach and DMUs with similar efficiency scores are ranked by using constraints and the Maximal Balance Index based on the optimal shadow prices. Afterwards, the efficiency scores of 25 branches of an Iranian commercial bank are evaluated using the proposed method. Also, a complete ranking of bank branches is presented to discriminate branches.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

ranking of bank branches with undesirable and fuzzy data: a dea-based approach

banks are one of the most important financial sectors in order to the economic development of each country. certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. sometimes the performance of banks must be measured in the presence of undesirable and vague factors. for these reasons in the current paper a procedure based on data envelopment...

full text

Ranking Bank Branches with Interval Data By IAHP and TOPSIS

This paper proposes a method for ranking decision making units (DMUs) using some of the multiple criteria decision making / multiple attribute decision making          (MCDM /MADM) techniques, namely, interval analytic hierarchy process (IAHP)          and the technique for order preference by similarity to an ideal solution (TOPSIS).          Since the efficiency score of unity is assigned to ...

full text

Ranking Bank Branches with Interval Data By IAHP and TOPSIS

This paper proposes a method for ranking decision making units (DMUs) using some of the multiple criteria decision making / multiple attribute decision making          (MCDM /MADM) techniques, namely, interval analytic hierarchy process (IAHP)          and the technique for order preference by similarity to an ideal solution (TOPSIS).          Since the efficiency score of unity is assigned to ...

full text

Efficiency Measurement of Bank Branches with Undesirable Output Using Non-Radial Models of Data Envelopment Analysis

Today, banks, as intermediaries, seek to attract and allocate resources to obtain greater benefit. Therefore, the bank assessment is considered as an important subject in the banking industry. Data envelopment analysis is an effective technique in evaluating the efficiency of decision-making units. There are factors among banking indices (such as receivables from resource allocation) that are i...

full text

Ranking of Efficient and Non-Efficient Decision Making Units with Undesirable Data Based on Combined Models of DEA and TOPSIS

Data Envelopment Analysis (DEA) is a method for determining the performance of units under evaluation of DMUs. Each decision-making unit using multiple inputs produces multiple outputs whose nature of outputs may be desirable or undesirable. Units whose performance score equals one are efficient. The concept of ranking decision makers because of the useful information they provide to decision m...

full text

Ranking units with fuzzy data in DEA

In this study, both optimistic and pessimistic approaches of data envelopment analysis are applied to propose an equitable ranking method in fuzzy environments. To this end, we suppose that the sum of efficiency scores of all decision making units (DMUs) equals to unity. Using the worst-best and best-worst approaches, the minimum and maximum possible efficiency scores of each DMU are estimated ...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 08  issue 2

pages  71- 77

publication date 2016-12-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023