Multiobjective data envelopment analysis
Data envelopment analysis (DEA) is popularly used to evaluate relative efficiency among public or private firms. Most DEA models are established by individually maximizing each firm’s efficiency according to its advantageous expectation by a ratio. Some scholars have pointed out the interesting re...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Palgrave Macmillan
2009
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/13481/1/JORS_DEA_Published.pdf http://irep.iium.edu.my/13481/ http://www.palgrave-journals.com/jors/journal/v60/n11/full/jors200992a.html |
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| Summary: | Data envelopment analysis (DEA) is popularly used to evaluate relative efficiency among public or private
firms. Most DEA models are established by individually maximizing each firm’s efficiency according to its
advantageous expectation by a ratio. Some scholars have pointed out the interesting relationship between the multiobjective linear programming (MOLP) problem and the DEA problem. They also introduced the common weight approach to DEA based on MOLP. This paper proposes a new linear programming problem for computing the efficiency of a decision-making unit (DMU). The proposed model differs from traditional and existing multiobjective DEA models in that its objective function is the difference between inputs and outputs instead of the outputs/inputs ratio. Then an MOLP problem, based on the introduced linear programming problem, is formulated for the computation of common weights for all DMUs. To be precise, the modified
Chebychev distance and the ideal point of MOLP are used to generate common weights. The dual problem of this model is also investigated. Finally, this study presents an actual case study analysing R&D efficiency of 10 TFT-LCD companies in Taiwan to illustrate this new approach. Our model demonstrates better performance than the traditional DEA model as well as some of the most important existing multiobjective DEA models.
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