A clustering method for evaluating the environmental performance based on slacks-based measure

被引:21
作者
Bi, Gong-bing [1 ]
Song, Wen [1 ]
Wu, Jie [1 ]
机构
[1] Univ Sci & Technol China, Sch Management, Hefei 230026, Anhui, Peoples R China
关键词
Data envelopment analysis; Clustering approach; Environmental performance; DATA ENVELOPMENT ANALYSIS; FACTOR ENERGY EFFICIENCY; CHINA; DEA; ALGORITHM; PROGRESS; REGIONS; OUTPUTS; LINKAGE;
D O I
10.1016/j.cie.2014.03.016
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The conventional clustering algorithms are mostly distance-based, which can lead to distorted results in the evaluation of production unit's performance. As a non-parametric method, data envelopment analysis (DEA) has become a popular approach to measuring the production process performance. However, few researchers paid attention to the relationship between clustering approach and DEA. In this paper, we use a non-radial DEA framework (slacks-based measure, SBM) to classify the environmental performance of Chinese industry, forming a benchmark-based clustering approach. Additionally, we employ the contextdependent DEA method to get the sub-clusters for detailed managerial meaning. An application in real world is given to explain the usage and effectiveness of the proposed SBM-based clustering method, and the result is compared with the conventional distance-defined k-means clustering approach. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:169 / 177
页数:9
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