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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]

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]

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]

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]

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]