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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]

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]

In the conventional data envelopment analysis (DEA) window analysis, a decision-making unit (DMU) in each window is treated as different units in each period so that the evaluation for one unit is performed on different scales over time. This paper proposes a novel window analysis based on common weight across time (CWAT), which evaluates each unit in each window by its common scale independent of time. The model for obtaining common weights is described as linear programming. And the paper suggests the Malmquist productivity index (MPI) on CWAT, CWAT MPI, to analyze productivity change by inheriting the result of window analysis. The numerical experiments are illustrated to examine the validity of CWAT and MPI, and the result shows that the proposed method provides a new evaluation scale compared to previous studies. The proposed model is applied to evaluate the performance of China 45 iron and steel enterprises during 2009–2017. The energy and environmental efficiency are calculated using CWAT, and CWAT MPI analyzes the productivity change. • We study a DEA window analysis based on common weights. • The proposed DEA window is represented by linear programming. • We discuss the Malmquist index in the DEA window. • The MPI is the geometric mean of all indices calculated in individual windows. • The performance of the iron and steel enterprises is evaluated. [ABSTRACT FROM AUTHOR]

Because of China’s rapid economic development, its transportation system has become one of China’s high-energy-consumption and high-pollution-emission sectors. However, little research has been done which pays close attention to China’s transportation system, especially in terms of energy and environmental efficiency evaluation. In this paper, data envelopment analysis (DEA) is applied to measure the energy and environment performance of transportation systems in China with the goal of sustainable development. This paper treats transportation as a parallel system consisting of subsystems for passenger transportation and freight transportation, and extends a parallel DEA approach to evaluate the efficiency of each subsystem. An efficiency decomposition procedure is proposed to obtain the highest achievable subsystem efficiency. Our empirical study on 30 of mainland China’s provincial-level regions shows that most of them have a low efficiency in their transportation system and the two parallel subsystems. There are large efficiency differences between the passenger and freight transportation subsystems. In addition, unbalanced development has occurred in the three large areas of China, with the east having the highest efficiency, followed by central China and then west. Therefore, more measures should be taken to balance and coordinate the development between the three large areas and between the two subsystems within them. Our analysis approach gives data for determining effective measures. [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]

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]

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]

Railway is one of the most efficient and environmental-friendly ways to transport people and goods. High-speed railway has been developing rapidly and the railway mileage has increased by 21.18% in China during the period of 2006–2011 and thus it is interesting to evaluate whether the railway transportation has reduced the environmental impact of transport in China. In this paper, we first use a non-radial DEA under managerial disposability to measure the environmental efficiency of 30 regions in China; then we propose a panel beta regression with fixed effects to model the impact of railway transportation on environmental efficiency. The results indicate that the environmental efficiency slowly increased during 2006–2011 and it exhibits regional disparities with the eastern area having the highest environmental efficiency and the western area being the lowest one; Moreover, we also find a significant positive impact of railway transportation on higher environmental efficiency. [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]

Abstract: Recently, environmental pollution has attracted a lot of attention domestically and internationally. It is known that energy utilization is a major source of China’s environmental pollution. Measuring environmental efficiency of energy utilization in Chinese provinces first, the paper then offers decision supports for relevant departments in order to achieve sustainable development of energy and environment in China. This research chooses CO2 emission as a substitute variable for environmental effects of energy utilization and puts it into the study framework based on total-factor production theory to measure the environmental efficiency of energy utilization of each province and three major regions. On the basis of the above results this research further measures the cost of environmental regulation for each province. Provincial panel data during the period of 2000–2007 are used to carry out empirical study. The analysis indicates that the environmental efficiency of energy utilization in Chinese provinces varies greatly from each other, meaning that both economic output and CO2 emissions need considerable improvement. In addition, the results of empirical study also show that the environmental efficiency of energy utilization in China is quite low. Therefore, to ensure sustainable development of China’s energy, economy and environment, we should resort to advanced technology as the support to promote the efficient and clean utilization of energy resources. Besides, most Chinese provinces have spent quite a lot on environmental regulation, implying that in these provinces development of the economy and the environment are not in harmony. The contributions of this research are as follows: it constructs the models for measuring environmental efficiency of energy utilization in Chinese provinces; it introduces the idea of “environmental regulation” into research system and measures the environmental regulation cost of each Chinese province. [Copyright &y& Elsevier]

Abstract: In this paper, the environmental efficiencies of 39 industrial sectors are measured using a non-radical, non-oriented slacks-based measure (SBM) model that considers the environmental impact of each industry. The economic efficiency of each industrial sector is measured using traditional data envelope analysis (DEA) methods and the differences between environmental efficiency and economic efficiency are analyzed using the transverse analysis method. A total of 39 industrial sectors are examined within three main industrial sectors (mining, manufacturing, and supply). Using the longitudinal analysis method, the environmental efficiencies of the three main industrial sectors from 2002 to 2009 are analyzed using the average value of their sub-industries’ environmental efficiencies. The time regression equation of the three industrial fields’ environmental efficiencies is examined using a regression analysis method. Based on these results, tactics for enhancing the environmental efficiency of Chinese industries are suggested in accordance with the characteristics of each industrial sector’s environmental efficiency. [Copyright &y& Elsevier]

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]

The output loss between cooperation and non-cooperation strategies for areas 1–4 (2012–2016). • Environmental control parameters are set to manipulate multiple situations. • Non-equal proportional change of indices and preference coefficient for ports are proposed. • A distance formula of expected output for PM emission reallocation is provided. • New DEA models are applied to 11 Chinese main ports. The emission of particulate matter (PM) and other atmospheric pollutants in port operations and shipping have caused a huge negative impact on the environment. Consequently, how to evaluate the environmental efficiency of ports and put forward corresponding countermeasures on this basis is becoming a more important issue than ever before from the perspectives of the government, academia, and society. We construct three data envelopment analysis (DEA) models to evaluate the environmental efficiency of ports under the circumstances of environmental control, non-environmental control and PM emission through inter-ports cooperation. The innovation of the DEA models constructed in this paper lies in: (1) Setting environmental control parameters to uniformly manipulate the situations of environmental control and non-environmental control, etc.; (2) Allowing non-equal proportional change of input index, expected output and non-expected output index; (3) Setting preference coefficients for ports to admit favorable decisions; (4) Providing a distance formula of expected output for PM emission reallocation. Further, data from 11 major ports in China are collected to compare the expected output under different PM emission standards assuming the situation of environmental control and non-environmental control, port cooperation, and non-cooperative sewage discharge. The empirical results show that: (1) Ports in the eastern China (Shanghai, Ningbo, and Nanjing) have higher port efficiency; (2) Port cooperation can improve the overall expected output but it will lose its edge with the improvement of PM emission standards. (3) Ports follow the same trend of output loss regardless of favorable decisions. In the end, the author makes a summary, puts forward relevant policy suggestions and makes the recommendation for future research. [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]