A Novel Stochastic Two-Stage DEA Model for Evaluating Industrial Production and Waste Gas Treatment Systems

Meiqiang Wang, Yingwen Chen and Zhixiang Zhou
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Meiqiang Wang: School of Management, Guizhou University, Guiyang 550025, China
Yingwen Chen: School of Management, Guizhou University, Guiyang 550025, China
Zhixiang Zhou: School of Economics, Hefei University of Technology, Hefei 230601, China

Sustainability, 2020, vol. 12, issue 6, 1-17

Abstract: In recent decades, the high-speed development in China has caused serious air pollution in China. The present paper proposes a stochastic data envelopment analysis (DEA) model based on a general two-stage structure with comprehensively considering the randomness in both desirable and undesirable outputs to calculate the environmental efficiency of the industry system. The new proposed model is more applicable to practical system, and is applied to evaluate the performance of production and waste gas treatment in the industrial sector for China’s regions along the “One Belt and One Road” in 2015. The results show that about half of the regions along “One Belt and One Road” in China are inefficient, where the performance on waste gas treatment is significantly worse than that of industrial production. Further, the managers should take different strategies for efficiency improvement in different areas because of the obvious differences in efficiency scores, in which the regions in the southeast area should pay more attention to improving waste gas treatment efficiency while that in the northwest area need to focus on industrial production efficiency.

Keywords: stochastic two-stage DEA; one belt and one road; industrial production and waste gas treatment; undesirable output (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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