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China's economy has experienced rapid development in the last several decades. However, environmental problems emerge along with the fast economic growth. Industrial pollutions and wastes have attracted much concern from the government and the public. In this paper, we propose a modified distance friction minimization model with undesirable outputs to evaluate the environmental efficiency of China's regional industry from 2011 to 2015. We then provide benchmarking targets for inefficient regions. Our approach can not only analyze the internal factors of the poorly performing regions but also set the benchmarking targets in which the inefficient regions need the least effort to be efficient. The analysis results indicate that the developed regions perform better than the developing ones. In particular, the regions that have always been efficient from 2011 to 2015 are all developed ones to our knowledge. Moreover, the gap in environmental performance tends to extend between developed and developing areas every year. We suggest that the Chinese government should formulate and perfect relative regulations and laws on environmental protection and take measures to reduce the unbalanced trend of its regional industry. [ABSTRACT FROM AUTHOR]

An increasing amount of resources is being utilized to combat the pollution problem in China. Measuring and improving the efficiency of this resource allocation is an effective way to promote pollution treatment at the present technical level. This paper utilizes a two-stage data envelopment analysis (DEA) model to attain allocation results based on the zero-sum gain and fixed-sum gain assumptions. We divide all the inputs into discretionary and non-discretionary inputs and construct two models for allocating resources based on the environmental efficiency scores. The new models are applied to calculate the performance and resource allocation scheme of 30 Chinese provinces from 2011 to 2015. Most provinces are inefficient at controlling pollution emission or treating pollution while using the given level of input resources. Based on the production possibility set of each province in 2015, the processing capacity of wastewater and gas could be increased by 1% and 3%, respectively, by reallocating resources for pollution treatment among different provinces. Environmental efficiency scores and resource allocation plans based on various assumptions are obtained in this paper to enlighten the corresponding decision-makers. Image 1 • The paper constructs two resource allocation models based on the DEA approach. • This research considers the allocation of public pollution treatment resources between different sectors. • Two strategies for resource allocation are composed to deal with different conditions relating to resources. • We apply the new models to measure the performance of 30 regions in China. [ABSTRACT FROM AUTHOR]

Over recent decades, China's economy has continued to develop steadily and rapidly, contributing to a large environmental cost. Therefore, many researchers propose various methods to evaluate environmental efficiency to deal with these serious issues accurately. This paper is the first to evaluate environmental efficiency using a model featuring not only a parallel structure with three component processes (primary, secondary, and tertiary industries) in the first stage but also a sewage treatment process in the second stage. Simultaneously, we propose radial but also nonradial versions of the Environmental Multiple Variable Return to Scale (EMVRS) model. These two models both consider shared inputs as well as shared outputs, and the proportion of the shared inputs and shared outputs utilized in each component process is assumed to be unknown. Additionally, we further analyze the factors influencing environmental efficiency by utilizing the Tobit model. The results when EMVRS is applied to Chinese provinces can be divided into 3 parts: (1) Most provinces do not purify wastewater appropriately contributing to the bad environmental efficiency. (2) The efficiency values of the three industry types are similar or identical to each other in most provinces. (3) The population of people employed negatively impacts environmental efficiency. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of transportation industry brings economic benefits, at the same time, the problem of environmental pollution is becoming more and more serious. The emission of CO 2 intensifies the trend of global warming. How to measure the development of environment and economy is a huge challenge for us. This paper proposes a data envelopment analysis (DEA) method based on slacks-based measure (SBM) to evaluate the environmental and economic performance of the transportation industry from 2015 to 2017. According to the economic region, 30 provinces in China are divided into northeast, east, central and western regions for efficiency analysis. The model can determine the low efficiency decision units and finally put forward improvement suggestions for the low efficiency areas. [ABSTRACT FROM AUTHOR]

This paper suggests that the efficiency of a system (decision-making unit) and its subsystem cannot be properly measured using a two-stage data envelopment analysis (DEA) model either in cooperative or non-cooperative evaluation. Indeed, the existing methods subjectively determine the status of the subsystems in the whole system. The two-stage DEA models, either cooperative game or non-cooperative game, are used to analyze the environmental efficiency. However, when the actual relationship between the two subsystems is inconsistent with the subjective relationship assumptions, the overall efficiency of the system and the efficiency of each subsystem will be biased. The conventional two-stage DEA models require predetermining the relationship between the subsystems within the system based on the subjective judgment of the decision-maker. Based on this, this paper proposes a three-step method to solve the two-stage DEA. First, the position relation among subsystems is determined according to the optimal weights through the model. According to the status relationship among subsystems, the decision units are grouped, and the two-stage DEA model of cooperative game or non-cooperative game is used to analyze the efficiency in each group. This method reduces the subjectivity of decision making and analyzes the efficiency of each decision unit applying the most appropriate two-stage DEA model to find the source of inefficiency. Finally, this paper verifies the rationality and validity of the method by analyzing the water use efficiency of industrial systems in China. It is found that most regions in China value economic development more than environmental protection (as evidenced by the DEA weights). What is more, the method proposed by the paper can be generalized for any two-stage DEA problem. [ABSTRACT FROM AUTHOR]

Since the 1980s, many electricity markets around the world have undergone restructuring aimed at improving efficiency. In 2002, the Chinese government also introduced a vertical unbundling reform to dismantle vertical monopolies and boost efficiency in the power sector. This study estimates the unified, operational, and environmental efficiency to comprehensively assess the impact of China's vertical unbundling on the production performance of thermal power firms. A non-radial data envelopment analysis (DEA) approach is employed to measure these efficiencies. Subsequently, a difference-in-difference model is used to assess the reform's effects. Empirical results show that the vertical unbundling improved the unified efficiency of firms. Further analysis indicates that the reform improved the operational efficiency of firms by increasing their capacity utilization and coal quality. Additionally, we find that the reform led to an increased utilization of source control technologies but resulted in a reduction in the use of end-of-pipe treatments. Due to the opposing effects on different pollution treatment stages, the reform did not have a significant impact on environmental efficiency. [ABSTRACT FROM AUTHOR]

Environmental efficiency improvement has played a crucial role in the theory and practice of stimulating clean production. This paper analyzes the interaction between environmental efficiency and output efficiency, particularly whether they reinforce each other or compete with each other, on the basis of a data set of 137 firms in the textile industry in China's Jiangsu Province. In the first stage, generalized data envelopment analysis is applied to calculate efficiency measures of energy, waste water, waste gas, soot, and output efficiency taking capital, labor, water, and energy as inputs, industrial output value as desirable output, and waste water discharges, waste gas and soot emissions as undesirable outputs. In the second stage analysis, a structural equation model with latent variables is applied to analyze the interaction between the latent variable environmental efficiency, measured by the four observed environmental indicators, and output efficiency, taking also into account the endogenous variable profit. The main outcomes of the structural equation model are the following. Firstly, environmental efficiency negatively impacts on profit while profit positively impacts on environmental efficiency. In a similar vein, output efficiency is found to depress profit while profit increases output efficiency. Thirdly, environmental efficiency has a positive impact on output efficiency while there is no effect of output efficiency on environmental efficiency. Fourthly, taxes impair a firm's output efficiency. From the findings it follows that a swap of general taxes for an energy tax is likely to improve both output efficiency and energy efficiency. The latter outcome implies a win–win situation which will facilitate the further implementation and adoption of environmental policy. Finally, the paper illustrates the applicability of structural equation modeling in efficiency analysis. [ABSTRACT FROM AUTHOR]

Abstract The green efficiency of water resources is important for industrial cleaner production and sustainable development. Existing studies pay much attention to the economic efficiency of water resource utilisation, ignoring its green efficiency. In order to solve this problem, an index of green total factor water efficiency (GTFWE) that can reflect the economic efficiency and green efficiency of water resources is constructed based on the DEA-SBM model with undesirable output. In addition, GTFWE is comprised of green total factor water management efficiency (GTFWME) and green total factor water environmental efficiency (GTFWEE) using the four-stage DEA model. The empirical results show that GTFWE in China's industry is at a low level, the effect of GTFWEE on GTFWE is generally increasing, and GTFWME is decreasing. However, there are large differences in these trends between regions and provinces in China. The GTFWME of Beijing, Tianjin, and seven other provinces needs improvement, while the GTFWME and GTFWEE of Hebei, Inner Mongolia, and other 15 provinces is low and also need improving. In contrast, both GTFWME and GTFWEE are high in the Shandong and Guangdong provinces. This paper provides a method for assessing GTFWE in China's industry and proposes some important policy implications for promoting the efficiency of China's industrial green total factor water resources. [ABSTRACT FROM AUTHOR]

The increasingly high frequency of heavy air pollution in most regions of China signals the urgent need for the transition to an environmentally friendly production performance by socioeconomic sectors for the sake of people's health and sustainable development. Focusing on CO 2 and major air pollutants, this paper presents a comprehensive environmental efficiency index based on evaluating the environmental efficiency of major socioeconomic sectors, including agriculture, power, industry, residential and transportation, at the province level in China in 2010 based on a slack-based measure DEA model with non-separable bad output and weights determined by the coefficient of variation method. In terms of the environment, 5, 16, 6, 7 and 4 provinces operated along the production frontier for the agricultural, power, industrial, residential and transportation sectors, respectively, in China in 2010, whereas Shanxi, Heilongjiang, Ningxia, Hubei and Yunnan showed lowest efficiency correspondingly. The comprehensive environmental efficiency index varied from 0.3863 to 0.9261 for 30 provinces in China, with a nationwide average of 0.6383 in 2010; Shanghai ranked at the top, and Shanxi was last. Regional disparities in environmental efficiency were identified. A more detailed inefficiency decomposition and benchmarking analysis provided insight for understanding the source of comprehensive environmental inefficiency and, more specifically, the reduction potential for CO 2 and air pollutants. Some specific research and policy implications were uncovered from this work. [ABSTRACT FROM AUTHOR]

Improvement of coal consumption efficiency is very important both for China in solving its problems of energy security and environmental pollution and for the world in addressing the issue of greenhouse gas emissions. Using a total-factor framework, this paper employs a data envelopment analysis (DEA) approach to evaluate the coal consumption efficiency of six energy intensive sub-industries in China in 2015. Coal consumption efficiency is factorized into economic efficiency and environmental efficiency, with sulfur dioxide, nitrogen oxide, and industrial smoke, dust and soot emissions treated as undesirable outputs of energy consumptions. The results show the following. (1) Of the six energy intensive sub-industries studied, two exhibit both DEA-effective coal economic efficiency and coal environmental efficiency. Coal economic efficiency is found to be greater than coal environmental efficiency, indicating that the benefits of economic efficiency have masked the negative effects of the environmental impact. China should therefore pay more attention to the clean utilization of coal. (2) Low environmental efficiency mainly resulted from the joint effects of pure technical efficiency and scale efficiency; therefore, enterprises in these industries must engage in management efforts to improve their ability to manage large enterprises. (3) The energy intensive industries characterized by coal environmental efficiency that failed to achieve pure technological effectiveness all exhibited input redundancy or output inadequacy of varying degrees while showing a potential for energy conservation and emissions reductions. [ABSTRACT FROM AUTHOR]

China's economic has got remarkable achievements during the past 30 years, which has brought tremendous pressure on natural resources and serious environmental pollution at the same time. In this paper, we aim to make environmental efficiency analysis of China's regional industry. Data envelopment analysis (DEA) method is incorporated and the slacks-based measure (SBM) model considering undesirable outputs is introduced to measure the environmental efficiency of different regions. Big data theory is introduced in the collection and selection of the input and output data of the regions. Further, we evaluate the environmental efficiencies of China's industry using data from 2008 to 2012. The results show that apart from several developed provinces, the environmental efficiencies of China's industry are generally low. And the environmental efficiencies of the regions did not show any increasing trend through the past 5 years. Additionally, lager differences exist in environmental efficiencies between the regions in China. Finally, we suggest the Chinese government to focus on the low environmental efficiencies and the unbalanced development of its regional industry. [ABSTRACT FROM AUTHOR]

There is great interest in measuring energy efficiency of China's industry using data envelopment analysis (DEA) approaches. This paper proposes a new exponential transformation of undesirable outputs into desirable outputs as part of a DEA approach for calculating environmental efficiency by using all kinds of classic models. Different from the existing transformations, the exponential model should provide a more flexible way to deal with undesirable outputs, allowing the user to adjust the slope and distribution of the transformation function by setting a parameter. A strategy for maximizing the standard variance among the undesirable outputs after transformation is employed in this paper to determine the optimal parameter value for the exponential model. This paper empirically examines the energy performance of sectors in Chinese industry from 2010 to 2014 using the proposed DEA model and the results show that most sectors in Chinese industry have not performed well, especially the sectors concerned with energy extraction. Based on the results of the efficiency evaluation, this paper calculates how can each sector achieve efficiency improvement through energy conservation and emission reduction, and propose specific improvement target values for each sector accordingly. Image 106227 • Alternative approach is constructed to deal with undesirable output in DEA models. • A new transformation is provided to reflect the exponential relationship between desirable and undesirable outputs. • The slope and distribution of data under the new transformation function are controllable. • The new presented approach is applied to measure the performance of 38 industries in China. [ABSTRACT FROM AUTHOR]

Although many studies have analyzed the environmental efficiency of coal-fired power plants in China with the aim of reducing CO2 emissions, there has been much less focus on the locations of the plants and their spatial pattern. In this study, we investigate the spatial dependence of environmental efficiency for coal-fired power plants in China from 2002 to 2011. We apply an integrated framework of data envelopment analysis and spatial autocorrelation analysis. We deduce the following three main findings from our empirical analysis: (1) the overall environmental efficiency of power plants increased during the study period, and the gap between the environmental efficiency of coastal and inland areas was reduced; (2) there is a positive spatial autocorrelation among the environmental efficiency levels of coal-fired power plants in China, and this spatial agglomeration has increased annually; and (3) high-efficiency power plants are spatially clustered in coastal areas while low-efficiency power plants are clustered in inland areas. Based on these findings, we conclude that cooperation among neighboring power plant managers is crucial to achieving effective environmental efficiency improvements, and that central and local governments should facilitate knowledge and technology spillover among the power plants. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization in China in recent years has resulted in the production of large amounts of construction waste, which has placed certain constraints on the sustainable development of the construction industry. This study measures the environmental efficiency of construction waste generated in China from static and dynamic perspectives using the data envelopment analysis and the Malmquist index with data from 30 Chinese provinces during the period from 2011 to 2020. The results showed that, from a static perspective, the environmental efficiency of China's construction waste generation has been on a generally declining trend year by year, and the overall level is still not too high. At the regional level, there is a stepwise decline in the eastern, central, northeastern, and western regions. From a dynamic point of view, the overall Malmquist index in China has an average value of 1.016, indicating that the level of environmental efficiency of construction waste generation in China is in a state of improvement. From a regional perspective, the Malmquist index is highest in the east, indicating that the level of environmental efficiency of construction waste generation in the eastern region is developing well. [ABSTRACT FROM AUTHOR]

As a main method for achieving environmental protection, improvement of environmental efficiency is vitally important for reducing environmental risk and level of ecological scarcity. Thus, quantitative analysis of environmental efficiency is not only an important premise for understanding the situation of regional environmental protection, but also a prerequisite for designing and adjusting relevant policies. In this paper, we treat the undesirable output in an economic activity by a linear monotonic decreasing transformation approach. We employ data envelopment analysis (DEA) technique to evaluate environmental efficiency in 30 provinces of China during the period 2001–2010, and conduct hypothesis tests on these environmental efficiencies. Furthermore, we investigate the horizontal differences of environmental efficiency in six regions of China and the vertical differences among different years. The results show that our empirical tests have a high statistical reliability that provides support for prompting environmental policies in different parts of China. [ABSTRACT FROM AUTHOR]

Improving the express industry's environmental efficiency is of practical significance to green and sustainable economic development. The development of internet may help achieve this goal. However, previous studies have not provided a consistent result about the relationship between internet development and the express industry's environmental efficiency. This paper provides a deeper understanding of this relationship by analyzing the threshold effects from the perspectives of road network density, openness to international trade and competition, and e-commerce level. Based on Chinese provincial data from 2012 to 2017, we first use a range directional data envelopment analysis model to evaluate the express industry environmental efficiency. Then, a threshold model is constructed to analyze the threshold effects in the relationship between internet development and environmental efficiency. The results show that: (1) The impact of internet development on the express industry's environmental efficiency shows a single threshold effect as road network density increases, which indicates that internet development significantly improves that environmental efficiency when the road network density is above a threshold value. (2) The impact of internet development on express industry environmental performance shows a dual-threshold effect as the degree of openness increases. (3) There is also a dual-threshold effect in this relationship as the proportion of e-commerce business transactions increases, but this effect is not significant. Based on these results, suggestions are given for the express industry to improve its environmental efficiency in China. [ABSTRACT FROM AUTHOR]

The ecological compensation mechanism is regarded as the direction for the future management of the ecological environment of the river basin, which has become a global concern. Ex-post assessments on the performance of ecological compensation programs contribute to further improvement and optimization in the process of exploration. This study proposes a novel performance assessment approach to address the issue of environmental efficiency evaluation with uncertainty by systematically integrating data envelopment analysis (DEA), bootstrap, regression, and exponential smoothing. The last two methods are used to fill in missing data, DEA super-SBM is applied to measure the performance, and bootstrap is adopted to stimulate more data. This approach is applied to performance measurement of Xin'an river basin in China. Validated by benchmark comparisons and statistical tests, the outcomes indicate that this integrated conceptual method can serve as an effective way to gauge environmental efficiency with ecological compensation when missing data are presented. The results obtained from the case highlight the limited positive effect of ecological compensation. Marginal utility brought about by the ecological compensation investment fund is declining, and the fund utilization in some projects also appears to be low. Consequently, suggestions for future optimization on fund and performance management, evaluation method and compensation mode are provided. [ABSTRACT FROM AUTHOR]

By-production (BP) technologies, modeled as an intersection of intended production technologies (production efficiency) and nature's residual-generation technologies (environmental efficiency), was applied in this paper to estimate the regional eco-efficiency in China during 2008–2017. This model is firstly formulated by directional-distance-function (DDF) and Färe-Grosskopf-Lovell (FGL), and then modified by bootstrap sensitivity analysis. The empirical results demonstrate that: (i) BP technologies based on the multiple production relations tend to produce lower efficiency scores than conventional model based on a single production relation. Moreover, BP-FGL can be a better choice for the measurement of efficiency index; (ii) The low economic development level is not necessarily associated with low environmental efficiency. Most of the eastern provinces had superior production efficiencies while inferior environmental efficiencies compared with inland provinces; (iii) At the regional level, a greater improvement in environmental efficiency than in production efficiency can be observed, and the gaps on the latter had widened over time among these regions; (iv) The great efficiency gaps between production efficiency and environmental efficiency appeared in the North Coast and Northwest, which are disadvantage to the inter-regional coordinated development. The results indicate that promoting production performance is crucial to improve the eco-efficiency for sustainable development in China. Image 10492 • BP technologies based on multiple production relation is applied. • Most of the eastern provinces have superior production efficiency. • Some western provinces perform well in environmental efficiency. • A greater improvement in environmental efficiency than in production efficiency. • Great efficiency gaps appeared in North Coast and Northwest regions. [ABSTRACT FROM AUTHOR]

China is now facing the formidable tasks of saving energy and reducing emissions, so it is very important to analyze China's energy and environmental efficiency. However, previous studies have rarely paid attention to the cross-impacts that different forms of public environmental concern (PEC) have simultaneously on energy and environmental efficiency. To investigate how these two types of efficiency change along with PEC variations, this paper employs six extended programming models which are developed based upon the theory of Data Envelopment Analysis (DEA) and the directional distance function (DDF). An empirical analysis of data from 239 Chinese prefecture-level cities demonstrates the techniques. The empirical results show that PEC variations can significantly affect the environmental efficiency only if the city is experiencing unsustainable development. This work also shows that PEC about input resources may exaggerate the environmental efficiency, implying that the public may be more tolerant of resource over-consumption than of pollutant over-emission. • How public environmental concern (PEC) affects environmental efficiency is studied. • A series of PEC-based DDF-DEA models are proposed. • An empirical analysis of data from 239 Chinese prefecture-level cities demonstrates. • PEC variations affect environmental efficiency only if it is unsustainable. • PEC over input resource may exaggerate environmental efficiency. [ABSTRACT FROM AUTHOR]

This paper presents new evidence on the impact of industrial agglomeration on environmental performance with a sample of prefectural-cities in China. When environmental performance is represented by pollution intensity, the impacts of industrial agglomeration on pollution intensity in terms of sulfur dioxide and soot show the heterogeneous pattern. The results support the existence of a non-linear pattern between agglomeration and emission intensity of sulfur dioxide, whereas the non-linear model could not hold for the emission intensity of soot. However, when we measure environmental performance with environmental efficiency estimated by a data envelopment analysis approach, it documents a U-shape relationship between industrial agglomeration and environmental efficiency. Specifically, environmental efficiency deteriorates in the early stage of industrial agglomeration and then improves as local industrial agglomeration proceeds. Different estimation strategies provide consistent evidence to verify such U-shape pattern. • The impact of industrial agglomeration on environment performance in China is examined. • DEA window analysis approach is used to measure environment efficiency. • Robustness checks are adopted to investigate the agglomeration effect. • Industrial agglomeration is measured with micro firm data. [ABSTRACT FROM AUTHOR]