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

机译:一种新型随机两级DEA模型,用于评估工业生产和废气处理系统

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摘要

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.
机译:近几十年来,中国的高速发展导致了中国的严重空气污染。本文提出了一种基于一般两级结构的随机数据包络分析(DEA)模型,其全面考虑了所需和不期望的输出中的随机性,以计算工业系统的环境效率。新的拟议模型更适用于实际系统,应用于评估2015年“一带和一条路”的中国地区生产和废气处理的性能。结果表明大约一半在中国“一带和一条路”的地区效率低下,废气处理的性能明显比工业生产更糟糕。此外,管理人员应采取不同的策略,因为效率分数明显差异,在东南部地区的区域应该更加关注改善废气处理效率,而在西北地区需要焦点论工业生产效率。

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