Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspective

Wu, Jie; Yin, Pengzhen; Sun, Jiasen; Chu, Junfei; Liang, Liang

doi:10.1016/j.ejor.2016.04.034

Cited by 119 publications

(45 citation statements)

References 69 publications

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“…In which, the performance of waste gas treatment is weaker than that of industrial production. Besides, similar to the results in [30] and [43] there are significant differences between the efficiency scores in different areas, where the southwest is the area with the best efficiency score while the southeast is the poorest performance area. Further, there are still differences between the performances for different stages in these areas that might guide the managers to take effective ways to improve efficiency.…”

Section: Discussionsupporting

confidence: 82%

“…Song et al [29] compose DEA models based on the two-stage structure to measure the environmental efficiency score of the industry in which the pollution emitted in the first stage is used as input for the second stage. From an interest preference perspective which changes weights of two sub-stage in turn, Wu et al [30] study the environmental efficiency of 30 provinces. Under the two-stage DEA framework, Chen et al [31] evaluate the environmental efficiency of 30 provinces from a cooperative and non-cooperative perspective, respectively.…”

Section: Introductionmentioning

confidence: 99%

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

2020

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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.

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Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

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

2020

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“…DEA is widely applied to efficiency measurement of decision making units (DMUs) in various industries, including agriculture [6,7], industry [8,9] and service industry-such as finance [10,11], education [12,13], retail [14,15], healthcare service and so on. Thereby, in the field of healthcare service, the applications of DEA method mainly focus on the simple efficiency measurement of medical and healthcare institutions or organizations.…”

Section: Introductionmentioning

confidence: 99%

Performance Measurement of Healthcare Service and Association Discussion between Quality and Efficiency: Evidence from 31 Provinces of Mainland China

2017

Sustainability

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Performance of healthcare service includes quality and efficiency, so there is inevitably an association between them. In general, it is believed that there is a trade-off between quality and efficiency; however, we prove that it is not completely accurate. We take the quality as an additional output to measure the healthcare service efficiency creatively, and discuss the association between quality and efficiency based on the effect of quality on relative efficiency. Firstly, we use TOPSIS method to calculate relative quality index values of healthcare service of 31 provinces of mainland China. This practice ensures the consistent comparison of 31 provinces' qualities. Subsequently, we measure the 31 provinces' relative performances and efficiencies of healthcare service with consideration of quality or not, by constructing DEA models. Then, we analyze the association between quality and efficiency from each group of the national, east, central and west, and conclude that the association between them is different along with their advantage degrees of quality and efficiency. Finally, we use the Tobit regression method to test 12 environment variables' net impacts on efficiency values both with consideration of quality or not. The results indicate that the main drivers of healthcare service efficiency are different when we take quality as an additional output or not. This article contributes to the field of performance measurement of healthcare service, puts forward a new method to integrate quality and efficiency and provides management guidelines.

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“…Undesirable Outputs Production Inputs [34] GDP SO 2 , COD, Nitrogen Labor, capital, energy, water [35] GDP CO 2 Labor, capital, energy [36] GDP CO 2 , SO 2 Labor, capital, coal, crude oil, natural gas [37] Industrial added value CO 2 Labor, capital, energy [38] GDP Labor, capital, energy [39] GDP Waste water, waste gas, solid waste Labor, capital, energy [40] Industrial added value CO 2 , SO 2 Labor, capital, energy [41] Industrial added value NO 2 Capital, electricity [26] GDP CO 2 Labor, capital, energy [42] GDP CO 2 , SO 2 Labor, capital, coal, electricity [4] GDP CO 2 Labor, capital, energy [43] GDP CO 2 Labor, capital, energy [44] GDP Solid waste Labor, capital, coal [45] GDP, primary secondary and tertiary industry PM 10 , SO 2 , NO 2 Coal, oil, gas, electricity, energy investment [46] Industrial added value Waste water, solid waste Labor, capital, coal [22] Industrial added value CO 2 Labor, capital, energy [47] GDP SO 2 , solid waste Labor, capital, energy [48] GDP CO 2 , SO 2 , COD Labor, capital, energy [49] GDP CO 2 , SO 2 , solid waste, industrial dust Labor, capital, energy [50] GDP CO 2 Labor, capital, energy [6] GDP CO 2 Labor, capital, energy [51] GDP CO 2 , SO 2 Labor, capital, energy [52] GDP SO 2 , waste water, solid waste Labor, capital, energy …”

Section: Authors Desirable Outputsmentioning

confidence: 99%

Social Sustainability Assessment across Provinces in China: An Analysis of Combining Intermediate Approach with Data Envelopment Analysis (DEA) Window Analysis

Zhang

Gao

2018

Sustainability

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There are two categories (i.e., radial and non-radial category) in conventional DEA (Data Envelopment Analysis). Recently, intermediate approach was put forward as a new third category. Intermediate approach is a newly proposed approach and there are quite limited related studies. This study contributes to the DEA studies by putting forward an analytical framework of combining intermediate approach and DEA window analysis along with the concepts of natural and managerial disposability. Such combination is quite meaningful and this new approach has three important features. To the best of our knowledge, such type of research has never been investigated by the existing studies. As an application, this approach is used to evaluate the performance of provinces in China from 2007 to 2014. Furthermore, this study develops a series of performance indices from different perspectives. This study identifies the three important findings. Firstly, eco-technology advancements can achieve economic prosperity and environmental protection simultaneously, and thus should become a new direction of climate policies. Secondly, considerable differences exist in a series of indices that evaluates the performance of various provinces and pollutants from different respective. Then, sufficient attention should be given to the provinces and the pollutants with poor performance. Finally, the Chinese government should promote efficiency improvement by "catching up" for provinces with poor performance in the short term. In addition, the central government should reduce regional disparity in order to promote the social sustainability in the long term.

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Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspective

Cited by 119 publications

References 69 publications

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

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

Performance Measurement of Healthcare Service and Association Discussion between Quality and Efficiency: Evidence from 31 Provinces of Mainland China

Social Sustainability Assessment across Provinces in China: An Analysis of Combining Intermediate Approach with Data Envelopment Analysis (DEA) Window Analysis

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