Improving the discrimination power through compromise solution approach: Malaysian banks as illustration
The conventional DEA gives each DMU an extreme flexibility in selecting its own weights in order to get its optimal efficiency score, which may result in a relatively high number of efficient DMUs, and prevents DEA from being a robust approach in determining the most efficient unit. Moreover, this f...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/42113/2/improving_discrimination_compiled.pdf http://irep.iium.edu.my/42113/3/DEA2014-P253.pdf http://irep.iium.edu.my/42113/ http://www.deaconference.com/dea2014/ |
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| Summary: | The conventional DEA gives each DMU an extreme flexibility in selecting its own weights in order to get its optimal efficiency score, which may result in a relatively high number of efficient DMUs, and prevents DEA from being a robust approach in determining the most efficient unit. Moreover, this flexibility hampers a common base for comparison and leads to a weak discrimination power among all DMUs as well as unrealistic weights allocation among inputs and outputs for all or part of DMUs. In this paper we show that these drawbacks can be satisfactorily overcome by compromise solution approach (Kao and Hung, 2005). We extend the Kao and Hung’s approach to the BCC model and scale efficiency computation. To compare the proposed models with the conventional DEA models, a sample of 30 Malaysian commercial banks is examined for the period 2006 to 2011, in terms of efficiency scores, ranking and returns to scale. |
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