TY - JOUR
T1 - Distinctive data envelopment analysis model for evaluating global environment performance
AU - Shabani, Amir
AU - Torabipour, Seyed Mohammad Reza
AU - Farzipoor Saen, Reza
AU - Khodakarami, Mohsen
N1 - Publisher Copyright:
© 2014 Elsevier Inc.
PY - 2015/8/1
Y1 - 2015/8/1
N2 - Evaluations of world environmental activities comprise an important research area when obtaining a better understanding of global efforts. However, some environmental criteria might include imprecise data. Environmental criteria can be classified according to four categories: discretionary, non-discretionary, desirable, and undesirable factors. The data envelopment analysis (DEA) technique has been applied widely to assess environmental performance. Classical DEA models evaluate performance of decision making units (DMUs) individually. However, the classical DEA models have some weaknesses. First, they focus on individual DMUs, where they freely assign weights to DMUs to obtain the best efficiency scores. Second, classical DEA models do not aggregate the performance of all DMUs to obtain an overall performance score. Finally, the calculations employed by classical DEA models are very long. To overcome these weaknesses, we propose DEA models for evaluating the individual and overall environmental performance of countries. The proposed models consider discretionary, non-discretionary, desirable, and undesirable factors simultaneously. Countries (DMUs) are ranked using a minimax regret-based approach (MRA). We provide a numerical example that illustrates the application of the proposed models.
AB - Evaluations of world environmental activities comprise an important research area when obtaining a better understanding of global efforts. However, some environmental criteria might include imprecise data. Environmental criteria can be classified according to four categories: discretionary, non-discretionary, desirable, and undesirable factors. The data envelopment analysis (DEA) technique has been applied widely to assess environmental performance. Classical DEA models evaluate performance of decision making units (DMUs) individually. However, the classical DEA models have some weaknesses. First, they focus on individual DMUs, where they freely assign weights to DMUs to obtain the best efficiency scores. Second, classical DEA models do not aggregate the performance of all DMUs to obtain an overall performance score. Finally, the calculations employed by classical DEA models are very long. To overcome these weaknesses, we propose DEA models for evaluating the individual and overall environmental performance of countries. The proposed models consider discretionary, non-discretionary, desirable, and undesirable factors simultaneously. Countries (DMUs) are ranked using a minimax regret-based approach (MRA). We provide a numerical example that illustrates the application of the proposed models.
KW - Data envelopment analysis
KW - Global environmental performance
KW - Imprecise data
KW - Minimax regret-based approach
KW - Non-discretionary factor
KW - Undesirable factor
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U2 - 10.1016/j.apm.2014.12.053
DO - 10.1016/j.apm.2014.12.053
M3 - Article
AN - SCOPUS:84937642055
SN - 0307-904X
VL - 39
SP - 4385
EP - 4404
JO - Applied Mathematical Modelling
JF - Applied Mathematical Modelling
IS - 15
ER -