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Increasing the Discriminatory Power of DEA Using Shannon's Entropy
Xie, Qiwei; Dai, Qianzhi; Li, Yongjun; Jiang, An
2014
Source PublicationENTROPY
ISSN1099-4300
Volume16Issue:3Pages:1571-1585
AbstractIn many data envelopment analysis (DEA) applications, the analyst always confronts the difficulty that the selected data set is not suitable to apply traditional DEA models for their poor discrimination. This paper presents an approach using Shannon's entropy to improve the discrimination of traditional DEA models. In this approach, DEA efficiencies are first calculated for all possible variable subsets and analyzed using Shannon's entropy theory to calculate the degree of the importance of each subset in the performance measurement, then we combine the obtained efficiencies and the degrees of importance to generate a comprehensive efficiency score (CES), which can observably improve the discrimination of traditional DEA models. Finally, the proposed approach has been applied to some data sets from the prior DEA literature.
Department环境化学与生态毒理学国家重点实验室
KeywordData Envelopment Analysis (Dea) Discrimination Improvement Shannon's Entropy
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Document Type期刊论文
Identifierhttps://ir.rcees.ac.cn/handle/311016/9390
Collection环境化学与生态毒理学国家重点实验室
Recommended Citation
GB/T 7714
Xie, Qiwei,Dai, Qianzhi,Li, Yongjun,et al. Increasing the Discriminatory Power of DEA Using Shannon's Entropy[J]. ENTROPY,2014,16(3):1571-1585.
APA Xie, Qiwei,Dai, Qianzhi,Li, Yongjun,&Jiang, An.(2014).Increasing the Discriminatory Power of DEA Using Shannon's Entropy.ENTROPY,16(3),1571-1585.
MLA Xie, Qiwei,et al."Increasing the Discriminatory Power of DEA Using Shannon's Entropy".ENTROPY 16.3(2014):1571-1585.
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