Banking Performance Measurement for Indian Banks Using AHP and TOPSIS
Multi-criteria decision modelling (MCDM) offers a range of procedures for evaluation problems requiring the ranking of a discrete set of alternatives, including the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). These procedures have...
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| Format: | Article |
| Language: | English |
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Universiti Utara Malaysia
2016-08-01
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| Series: | The International Journal of Banking and Finance |
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| Online Access: | https://www.e-journal.uum.edu.my/index.php/ijbf/article/view/8494 |
| _version_ | 1828069260852723712 |
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| author | Mihir Dash |
| author_facet | Mihir Dash |
| author_sort | Mihir Dash |
| collection | DOAJ |
| description | Multi-criteria decision modelling (MCDM) offers a range of procedures for evaluation problems requiring the ranking of a discrete set of alternatives, including the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). These procedures have been widely applied for banking performance evaluation (Önder & Hepşen, 2013).The present study compared the outcomes of AHP and TOPSIS for evaluation of a sample of 35 Indian banks, including 19 public sector banks and 16 private sector banks. The variables used in the analysis pertained to the financial ratios corresponding to the CAMEL parameters. The weights for different parameters in the CAMEL model were obtained by factor analysis. The results of the study indicated an overall consistency between the rankings, resulting from the models. A significant difference was found in the performance between private sector banks and public sector banks. In particular, banks that were found to be consistently ranked high by both models can be taken as the best performers, and banks that were found to be consistently ranked low by both models can be taken as the worst performers. This would enable regulators and policy makers, on the one hand, to benchmark the performance of banks against that of best performers, and on the other hand, to take steps to improve the performance of worst performers. The results of the study also needed to be examined more carefully to identify the critical performance parameters for banks.
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| first_indexed | 2024-04-11T00:15:21Z |
| format | Article |
| id | doaj.art-6e554c08a20646f18cf2e457d85bcffb |
| institution | Directory Open Access Journal |
| issn | 2811-3799 2590-423X |
| language | English |
| last_indexed | 2024-04-11T00:15:21Z |
| publishDate | 2016-08-01 |
| publisher | Universiti Utara Malaysia |
| record_format | Article |
| series | The International Journal of Banking and Finance |
| spelling | doaj.art-6e554c08a20646f18cf2e457d85bcffb2023-01-09T03:08:05ZengUniversiti Utara MalaysiaThe International Journal of Banking and Finance2811-37992590-423X2016-08-01122Banking Performance Measurement for Indian Banks Using AHP and TOPSISMihir Dash0Alliance University, BangaloreMulti-criteria decision modelling (MCDM) offers a range of procedures for evaluation problems requiring the ranking of a discrete set of alternatives, including the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). These procedures have been widely applied for banking performance evaluation (Önder & Hepşen, 2013).The present study compared the outcomes of AHP and TOPSIS for evaluation of a sample of 35 Indian banks, including 19 public sector banks and 16 private sector banks. The variables used in the analysis pertained to the financial ratios corresponding to the CAMEL parameters. The weights for different parameters in the CAMEL model were obtained by factor analysis. The results of the study indicated an overall consistency between the rankings, resulting from the models. A significant difference was found in the performance between private sector banks and public sector banks. In particular, banks that were found to be consistently ranked high by both models can be taken as the best performers, and banks that were found to be consistently ranked low by both models can be taken as the worst performers. This would enable regulators and policy makers, on the one hand, to benchmark the performance of banks against that of best performers, and on the other hand, to take steps to improve the performance of worst performers. The results of the study also needed to be examined more carefully to identify the critical performance parameters for banks. https://www.e-journal.uum.edu.my/index.php/ijbf/article/view/8494multi-criteria decision modellingAHPTOPSISfactor analysis |
| spellingShingle | Mihir Dash Banking Performance Measurement for Indian Banks Using AHP and TOPSIS The International Journal of Banking and Finance multi-criteria decision modelling AHP TOPSIS factor analysis |
| title | Banking Performance Measurement for Indian Banks Using AHP and TOPSIS |
| title_full | Banking Performance Measurement for Indian Banks Using AHP and TOPSIS |
| title_fullStr | Banking Performance Measurement for Indian Banks Using AHP and TOPSIS |
| title_full_unstemmed | Banking Performance Measurement for Indian Banks Using AHP and TOPSIS |
| title_short | Banking Performance Measurement for Indian Banks Using AHP and TOPSIS |
| title_sort | banking performance measurement for indian banks using ahp and topsis |
| topic | multi-criteria decision modelling AHP TOPSIS factor analysis |
| url | https://www.e-journal.uum.edu.my/index.php/ijbf/article/view/8494 |
| work_keys_str_mv | AT mihirdash bankingperformancemeasurementforindianbanksusingahpandtopsis |