Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking Sector
The present paper examined the review of literature related to measuring relative efficiency of banks using Data Envelopment Analysis (DEA). The efficiency of banks is measure through the ability of the individual bank to maximise output given a certain level of input. By measuring its efficiency,...
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| Format: | Article |
| Language: | English |
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EconJournals
2016-07-01
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| Series: | International Journal of Economics and Financial Issues |
| Online Access: | https://www.econjournals.com/index.php/ijefi/article/view/2246 |
| _version_ | 1797918357892104192 |
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| author | Filzah Mohamed Othman Nor Aiza Mohd-Zamil Siti Zaleha Abdul Rasid Amin Vakilbashi Mozhdeh Mokhber |
| author_facet | Filzah Mohamed Othman Nor Aiza Mohd-Zamil Siti Zaleha Abdul Rasid Amin Vakilbashi Mozhdeh Mokhber |
| author_sort | Filzah Mohamed Othman |
| collection | DOAJ |
| description |
The present paper examined the review of literature related to measuring relative efficiency of banks using Data Envelopment Analysis (DEA). The efficiency of banks is measure through the ability of the individual bank to maximise output given a certain level of input. By measuring its efficiency, it can serves as early warning or benchmark of its performance and it can define future improvement in various area such as managerial, technology or socio-economic. DEA is comprises of two basic model that are DEA CCR (Charnes-Cooper-Rhodes) Model with constant return to scale (CRS) assumption and DEA BCC (Banker-Charnes-Cooper) Model with variable return to scale (VRS) assumption. In banking industry, DEA is using two approaches that are production or intermediation approach. The former highlights banks as delivering services in the form of transaction and the later assumes banks intermediate funds between surplus units to deficit unit. The study of efficiency in banks with similar economic and political condition is important as banks operate in parallel.
Keywords: Data Envelopment Analysis (DEA), Efficiency, Banking
JEL Classifications: G2, M2, M4
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| first_indexed | 2024-04-10T13:27:53Z |
| format | Article |
| id | doaj.art-652eebcc9a034a8fac5b736ad3ee2303 |
| institution | Directory Open Access Journal |
| issn | 2146-4138 |
| language | English |
| last_indexed | 2024-04-10T13:27:53Z |
| publishDate | 2016-07-01 |
| publisher | EconJournals |
| record_format | Article |
| series | International Journal of Economics and Financial Issues |
| spelling | doaj.art-652eebcc9a034a8fac5b736ad3ee23032023-02-15T16:11:47ZengEconJournalsInternational Journal of Economics and Financial Issues2146-41382016-07-0163Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking SectorFilzah Mohamed Othman0Nor Aiza Mohd-Zamil1Siti Zaleha Abdul Rasid2Amin VakilbashiMozhdeh MokhberInternational Business School, Universiti Teknologi Malaysia (UTM IBS), MalaysiaInternational Business School, Universiti Teknologi Malaysia (UTM IBS), MalaysiaInternational Business School, Universiti Teknologi Malaysia (UTM IBS), Malaysia The present paper examined the review of literature related to measuring relative efficiency of banks using Data Envelopment Analysis (DEA). The efficiency of banks is measure through the ability of the individual bank to maximise output given a certain level of input. By measuring its efficiency, it can serves as early warning or benchmark of its performance and it can define future improvement in various area such as managerial, technology or socio-economic. DEA is comprises of two basic model that are DEA CCR (Charnes-Cooper-Rhodes) Model with constant return to scale (CRS) assumption and DEA BCC (Banker-Charnes-Cooper) Model with variable return to scale (VRS) assumption. In banking industry, DEA is using two approaches that are production or intermediation approach. The former highlights banks as delivering services in the form of transaction and the later assumes banks intermediate funds between surplus units to deficit unit. The study of efficiency in banks with similar economic and political condition is important as banks operate in parallel. Keywords: Data Envelopment Analysis (DEA), Efficiency, Banking JEL Classifications: G2, M2, M4 https://www.econjournals.com/index.php/ijefi/article/view/2246 |
| spellingShingle | Filzah Mohamed Othman Nor Aiza Mohd-Zamil Siti Zaleha Abdul Rasid Amin Vakilbashi Mozhdeh Mokhber Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking Sector International Journal of Economics and Financial Issues |
| title | Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking Sector |
| title_full | Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking Sector |
| title_fullStr | Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking Sector |
| title_full_unstemmed | Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking Sector |
| title_short | Data Envelopment Analysis: A Tool of Measuring Efficiency in Banking Sector |
| title_sort | data envelopment analysis a tool of measuring efficiency in banking sector |
| url | https://www.econjournals.com/index.php/ijefi/article/view/2246 |
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