A hybrid data envelopment analysis and multi-attribute decision making approach to sustainability assessment

被引:10
作者
Keshavarz, Esmaeil [1 ]
Toloo, Mehdi [2 ]
机构
[1] Islamic Azad Univ, Dept Math, Sirjan Branch, Sirjan, Iran
[2] VSB Tech Univ Ostrava, Dept Syst Engn, Ostrava, Czech Republic
关键词
CRITIC method; cross-efficiency; data envelopment analysis; selective measure; sustainability; SELECTING PERFORMANCE-MEASURES; DETERMINING ATTRIBUTE WEIGHTS; CROSS-EFFICIENCY; DEA; MODEL;
D O I
10.1111/exsy.12347
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The concept of sustainability consists of three main dimensions: environmental, techno-economic, and social. Measuring the sustainability status of a system or technology is a significant challenge, especially when it needs to consider a large number of attributes in each dimension of sustainability. In this study, we first propose a hybrid approach, involving data envelopment analysis (DEA) and a multi-attribute decision making (MADM) methodologies, for computing an index for each dimension of sustainability, and then we define the overall sustainability index as the mean of the three measured indexes. Towards this end, we define new concepts ofefficiency and cross-efficiency of order(p, q)wherepandqare the number of inputs and outputs, respectively. For a given(p, q), we address the problem of finding efficiency of order(p, q)by developing a novel DEA-based selecting method. Finally, we define the sustainability index as a weighted sum of all possible cross-efficiencies of order(p, q). Form a computational viewpoint, the proposed selecting model significantly decreases the computational burden in comparison with the successive solving of traditional DEA models. A case study of the electricity-generation technologies in the United Kingdom is taken as a real-world example to illustrate the potential application of our method.
引用
收藏
页数:17
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