Search

The metal industry (MI) in China is energy and emissions intensive. This paper tries to provide guidance for the green development transformation of China's MI, by investigating the green total-factor productivity (GTFP) and its influencing factors using a global data envelopment analysis and a spatial Tobit regression model. The estimation results show that: (1) from 2000 to 2015, GTFP of China's MI enjoyed a considerable improvement. However, the current value of GTFP of China's MI is still less than 0.5, indicating that GTFP of China's MI is far from efficient; (2) the spatial correlation test shows that GTFPs of China's provincial MIs have positive spatial correlations. Most of the provinces scattered in "high-high" and "low-low" agglomerations; (3) GTFP of China's MI is significantly positive related to the degree of marketization, fiscal decentralization, environmental regulation, industrial scale, is significantly negative related to resources endowment and product structure, and has "U" shaped relationship with the level of economic development. The above results suggest that China already has made remarkable achievements in promoting green development of its MI. However, there is much room for further improvement. Policy options for the green development transformation of China's MI include but are not limited to promoting market-oriented and financial system reforms, strengthening environmental supervision, and optimizing industrial scale and product structure. Finally, recommendations for the effective implementation of these policies are provided at the end of the study. • This paper analyzed the historical performance and influencing factors of GTFP of China's MI. • Results show that GTFP of China's MI achieved considerable improvement in the past few years. • However, the current level of GTFP of China's MI is still very low. • There are many effective policy options for further promoting GTFP growth of China's MI. • Some implications for the implementation of these policies are provided in this paper. [ABSTRACT FROM AUTHOR]

With the completion of the poverty alleviation task in China, the Chinese economy has made great breakthroughs. Meanwhile, the implementation of Chinese "dual carbon" goal has entered an important window period of both strategic opportunities and difficulties. The emission of carbon dioxide (CO2) leads to the greenhouse effect, which affects the sustainable development of society. Therefore, this paper proposes an improved analytic hierarchy process (AHP) with Slacks-based measure integrating data envelopment analysis (SBMDEA) (AHP-SBMDEA) based efficiency evaluation model for different provincial-level administrative regions in China, which is used to analyze and optimize the Chinese energy structure of different provincial-level administrative regions. With coal, gasoline, petroleum, fuel oil, diesel, crude oil and natural gas as inputs, the per capita Gross Domestic Product (GDP) as the desired output and the CO2 as the undesired output, after linear weighted calculation of the results of the AHP-SP model and the SBMDEA model, the energy efficiency evaluation model of different provincial administrative regions in China is established. The results show that there is a large difference in efficiency between Chinese northern and southern regions, and the overall efficiency of southern regions is higher than that of northern regions. In addition, it is easier to find out the optimal energy efficiency benchmark, which can provide suggestions and help to guide the energy consumption input structure improvement of other inefficient provincial-level administrative regions. Furthermore, the energy structure can also be adjusted through the redundant variable calculated by the SBMDEA model. For example, Sichuan Province can reduce the consumption of the coal, the gasoline, the diesel, the fuel oil, the crude oil and the natural gas by 5269.95 × 10000 tons (WT), 513.01 WT, 59.05 WT, 34.37 WT, 4,73.33 WT and 130.37 billion cubic meters (BCM), respectively. Its CO2 emissions can be reduced by 1925.4 WT, and raise the efficiency of energy utilization in the province. [Display omitted] • Novel economy and CO 2 emissions evolution model based on a AHP-SBMDEA is proposed. • The proposed model can identify the optimal energy efficiency benchmark. • GDP per capita can be increased and CO 2 emissions can be decreased. [ABSTRACT FROM AUTHOR]

Improving the deployment and penetration of renewable energy is considered to be the fundamental way to solve environmental problems, but whether higher penetration of renewable energy means higher energy efficiency remains to be empirically tested. To reveal the relationship between cleanliness and efficiency in the energy sector, this paper first uses the three-stage data envelopment analysis (DEA)method to measure the total factor energy efficiency (TFEE) of 30 provinces in China, and then applies static and dynamic panel threshold regression (PTR)models to estimate the nonlinear effect of renewable energy share on TFEE. The results show that renewable energy is usually beneficial for improving TFEE, but there are prominent heterogeneity and nonlinear characteristics in net electricity exporting and net electricity importing provinces. Renewable energy in low rather than high regimes can significantly improve energy efficiency, indicating that provinces with lower levels of economic development and energy consumption receive higher marginal energy efficiency and are more likely to achieve sustainable development goals. More renewable energy quotas should be given to economically developed and high energy consuming provinces, and comprehensive energy efficiency guarantees and improvement measures must be provided to achieve optimal emission mitigation. [ABSTRACT FROM AUTHOR]

In the face of environmental degradation, sustainable development has become a common goal across the globe. Making a scientifically based investment scheme is of great significance to promote the sustainable development of China's economy. However, there is scarce research related to such an investment scheme of sustainable development. This paper proposes a new inverse data envelopment analysis method with undesirable outputs to make several scientifically based investment schemes from different perspectives, namely, the natural, regulation, and optimal perspectives. By this method, decision makers can scientifically forecast the specific amount of investment based on their actual sustainable development objectives, which is conducive for reducing the blindness of investment in the future. In addition, a new ideal perspective is defined to guide a definite direction for improving the level of sustainable development. Combined with the gray forecasting model GM(1,1), the methods proposed by this paper were then applied to analyze the investment problem for China's sustainable development during the 2015–2024 period. The results show that: the unbalanced distribution of labor investment and the excessive investment in capital and energy are serious barriers to China's sustainable development in the short term; and in the long term, the demand for investment in labor and capital will continue to increase along with a lower demand for energy investment, and that appropriately strengthening environmental regulations will not affect the overall demand for investment. Meanwhile, improvement directions for improving China's sustainable development are discussed, and the results show that most of developing and undeveloped regions in China have great potential for improvement. Finally, some suggestions are proposed in order to create better conditions for China's sustainable development. [ABSTRACT FROM AUTHOR]

Obtaining the most economic benefits while using the least resources and causing the least environmental damage is an urgent and key problem in achieving sustainable development. The concept of eco-efficiency provides a comprehensive perspective for observing and solving this problem. This paper proposes an extended data envelopment analysis model, named the WIN-US-SBM, as a comprehensive eco-efficiency evaluation method that can accommodate undesirable outputs, all the identification problems of decision-making units (DMUs), possible slacks of variables, and the problems of an insufficient number of available DMUs and intertemporal comparability. China's Western Taiwan Straits Economic Zone (WTS Economic Zone) is an important regional economic growth center. By applying WIN-US-SBM and ArcGIS software, we investigated data on the temporal and spatial evolution characteristics of eco-efficiency in the WTS Economic Zone for the years 2009–2016. Later, the global Malmquist–Luenberger index was used to decompose the sources of growth in eco-efficiency. Finally, the main driving factors of eco-efficiency were explored through a Tobit regression analysis. The empirical results show that: (1) The overall eco-efficiency of the WTS Economic Zone had greatly improved, increasing by 11.46% annually, and the cumulative growth rate of eco-efficiency was 110.84% from 2009 to 2016. (2) The eastern area had the highest average eco-efficiency, followed by the western area and the middle area in that order. Also, the growth rate of the middle area ranked first (16.68%), whereas the eastern area had the slowest growth in eco-efficiency (7.22%). (3) On the whole, the growth of eco-efficiency was driven mainly by technological progress and was restricted by the decrease in management level, which implies that policy makers should focus on improving management and technical levels. (4) High levels of economic development, population density, market openness, and industrial structure had positive effects on the eco-efficiency of the WTS Economic Zone, whereas energy intensity and expenditure on science and technology had negative impacts. • An extended DEA model is proposed to measure eco-efficiency more comprehensively. • The proposed model can be widely applied to input-output efficiency evaluations. • The eco-efficiency of the WTS Economic Zone was evaluated based on a novel model. • The growth of eco-efficiency was driven mainly by technological progress. • The eco-efficiency level is negatively related to energy intensity. [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]

This paper proposes a meta-frontier nonparametric approach to construct the slacks-based composite indicator considering heterogeneity. The meta-frontier approach is useful to control and study the impact of potential heterogeneity in constructing composite indicator. In virtue of the Malmquist index, we further study tracking the evolvement of the constructed meta-frontier slacks-based composite indicator over time, and quantifying the driving forces behind the change. The proposed approach has been applied to assess China's regional sustainable energy utilization capacity during 2005–2010. Our empirical results show that all the three regions, i.e. the eastern, central and western, in China experience deterioration in sustainable energy development level. The best practice gap change and technology gap change are identified as the main contributors to the declining trend. Hence, improving the general production technology and enhancing technology diffusion among regions can help to promote China's overall sustainable energy development level. At the provincial level, Beijing is found to maintain a good balance in improving efficiency and absorbing advanced technology, while other provinces show diverse performance during this time period. More results and discussions are presented in this paper. [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]

Currently, the iron and steel industry (ISI) accounts for more than 16% of China's total energy consumption. Improving energy efficiency (EE) and promoting energy savings in this industry have vital significance for China's further sustainable development. Using provincial panel data from 2000 to 2014 and meta-frontier data envelopment analysis (DEA), this paper investigates EE and the energy-saving potential (EP) of China's ISI by considering regional technology heterogeneities. The results show that (1) from 2001 to 2014, EE in China's ISI achieved significant improvement. Technological progress is the most powerful driving factor, while the declines in scale efficiency and pure technical efficiency are two obstructive factors; (2) the sources of energy inefficiency (EI) show distinct spatial difference characteristics. EI in the eastern region mainly stems from scale inefficiency and pure technical inefficiency, while that in the central and western regions stems from three aspects of scale inefficiency, pure technical inefficiency, and technology gap; and (3) there is considerable EP in China's ISI, which represents nearly 80% of ISI's current total energy consumption. Because the sources of EP vary across regions, the focus of future work for China's regional ISI should also vary. [ABSTRACT FROM AUTHOR]

Manufacturing industry is the pillar industry in China, making China become the world's manufacturing center. While, the rapid development of manufacturing industry in China not only promotes the economic growth, but also consumes lots of resources and generates too much carbon dioxide. To make a sustainable development, this paper adopts a non-radial DEA model with natural and managerial disposability to examine the energy-environmental performance of China's manufacturing industry during the 2006–2014 period. The energy-environmental performance is evaluated by the unified efficiency under natural and managerial disposability (UENM). Additionally, the investment strategy is confirmed by industrial types of damages to return (DTR). The empirical results indicate that the unified efficiencies of most manufacturing industries present a rising trend in the sample interval. Moreover, the unified efficiency of most manufacturing industries in light industry have a little higher value than the efficiency of those in heavy industry. Besides, the light industry presents more investment effect than the heavy industry, and many industries in heavy industry have little potential for investment in terms of developing the green growth. According to these results, China should increase investment and enhancing the R&D input to improve the unified efficiency of light industry. Policy support need focus on boosting innovation in strategic emerging industries instead of traditional manufacturing industries. Part of industries with excess capacity should be transferred to other countries through outbound investment. [ABSTRACT FROM AUTHOR]

Eco-efficiency is of great significance in facilitating a region’s sustainable development. However, there are some inconsistencies among the concepts and also relationships of eco-efficiency and its relevant efficiencies in recent studies. This paper integrates eco-efficiency and three related-efficiencies (economic efficiency, energy efficiency, and environmental efficiencies) into a total-factor analysis framework, regarding them as composite eco-efficiency indicators. Employing a new data envelopment analysis approach, named Meta-US-SBM, which considers meta-frontier, undesirable outputs, super efficiency, and slacks simultaneously, the measure system of these four efficiencies is established. An empirical study is conducted using Chinese provincial data from 2001 to 2014. Results indicate that, overall, the regional economic efficiency is better than other related efficiency indicators. Furthermore, different provinces are adopting different development modes, as denoted by significant heterogeneity among eco-efficiency indicators. [ABSTRACT FROM AUTHOR]

Global carbon emission control and resource conservation are important measures to realize sustainable development goals. There are few researches on carbon emissions from the perspective of congestion with the data envelopment analysis method. Congestion effects not only help us to reduce carbon emissions, but also achieve reasonable allocation of resources. This paper expands traditional congestion into undesirable congestion and desirable congestion, and both are divided into undesirable congestion of energy (capital) and desirable congestion of energy (capital) in 30 Chinese provinces with a two-stage model. So, purely technical inefficiency is separated from congestion, and energy and capital utilization can be analyzed simultaneously. The results show that: (1) China has a higher carbon emission reduction potential under natural disposability than that under managerial disposability. (2) The number of provinces with undesirable congestion of energy in the eastern region is small, while that with undesirable congestion of capital in the western region is small. (3) The number of provinces with desirable congestion increases. Desirable congestion of energy and capital is mainly concentrated in the eastern and central regions. Exploring the congestion effects of energy and capital will help China to achieve "dual carbon" targets and promote the environmental, social, and governance investment. • Carbon emission reduction potential is studied from the perspective of congestion. • Two-stage undesirable and desirable congestion models are constructed innovatively. • Energy and capital inputs are separated from other inputs in the congestion model. • Rational allocation of resources is realized based on energy and capital congestion. [ABSTRACT FROM AUTHOR]

Because industrial sectors in China are energy-intensive, improving energy efficiency and promoting energy savings in these sectors are of great importance for the further sustainable development of China’s economy. Using a proposed meta-frontier data envelopment analysis (DEA), this paper analyzes the total-factor energy efficiency and energy savings potential in China’s provincial industrial sectors for the years 2000–2014 from three perspectives, namely, the technology gap, management, and scale. The results indicate that (1) driven by technological progress, energy efficiency during the sample period was greatly improved, though the expansion of technology gaps between regions and the decline in scale efficiency represented two significant handicaps; (2) the current energy efficiency in China’s industrial sectors remains extremely low, indicating that there is considerable potential for energy efficiency improvement and energy savings; and (3) the sources of energy inefficiency and energy savings potential in China’s industrial sectors exhibit spatially distinct characteristics. Accordingly, it is determined that most of China’s eastern provinces should focus on improving scale and management efficiency, whereas most of its central and western provinces should concentrate on three factors: narrowing the regional technology gap, improving management efficiency, and optimizing the industrial scale. [ABSTRACT FROM AUTHOR]

Improving energy efficiency has been recognized as the most effective way to reduce the greenhouse effect and achieve sustainable development. From the perspective of air emissions, this paper adopts data envelopment analysis approach to evaluate the energy efficiency in China’s coastal areas over the period of 2000–2012. Carbon dioxide, sulfur dioxide and nitrogen oxide are treated as undesirable outputs of energy consumptions. The proposed global Epsilon-based measure is used to estimate the static energy efficiency with an annual cross-section of data. The weights of the three undesirable outputs are determined according to their treatment costs. A global Malmquist-Luenberger productivity index based on directional distance function is employed to dynamically evaluate the energy efficiency. The results indicate the following in China’s coastal areas: (1) the level of economic development is positively related to energy efficiency scores; (2) energy efficiency scores decrease when considering undesirable outputs except Beijing and Hainan; (3) the Circum-Bohai Sea Economic Region greatly improves energy efficiency and has great potential of air emission; (4) the annual growth rate of Malmquist-Luenberger productivity index change is overestimated; (5) energy efficiency improvement is mainly driven by technological improvement, and scale efficiency and management level are the main obstacles. [ABSTRACT FROM AUTHOR]

Data envelopment analysis has recently gained popularity and attention in operational and environmental assessment. A common feature of previous studies is decreasing an input vector to decrease the vector of undesirable outputs which is referred to as natural disposability. However, little research has considered how to increase the amount of capital input for clean production technology to decrease the amount of undesirable outputs in a data envelopment analysis framework, which is referred to as managerial disposability. Thus, this paper proposes an improved approach that considers measuring unified (operational and environmental) efficiency for managerial disposability, and compares this approach with the one for natural disposability. The proposed approach provides a positive strategy to reduce undesirable outputs and improve unified efficiency through increasing capital investment in clean production technology. A case study of regional industries in China in 2006–2010 utilizing this approach is also presented. The empirical study shows that the unified efficiencies of regional industries in China have relatively high scores for managerial disposability, and increasing capital investment is vital to achieve sustainable development in clean production technology. [ABSTRACT FROM AUTHOR]

The highly fragmented coal industry in China has experienced a consolidation process since late 2008. Major coal-rich provinces have adopted nationalization and market-oriented approaches to reduce the number of small coal mines, leading to a marked increase in the proportion of the total output produced by large and medium-sized coal mines. Relying on a Range-Adjusted Measure model of the Data Envelopment Analysis, this article constructs three indicators, namely operational efficiency, environmental efficiency, and unified efficiency, to reflect sustainability impact of this consolidation policy. By comparing two representative provinces – Shanxi and Inner Mongolia over the period 2005–2012, this paper assesses the policy effectiveness on the transition of coal mining industry to sustainable development. The results suggest that the consolidation reform in China has a negative impact on coal productivity, but significantly it improves the environmental performance of the coal industry. However, the nationalization approach does not prove to outweigh market-oriented approach, because the inefficiency in the capital factor offsets efficiency-improving outcome. The market-driven regulation can reduce the negative impact of the market restructuring on the operational efficiency and thus achieve a higher unified efficiency from both operational and environmental perspectives. [ABSTRACT FROM AUTHOR]

In recent years, the economic performance of Chinese industry has improved significantly; however, the congestion caused by excessive investment has plagued its sustainable development. In order to make full use of resources, it is necessary for the Chinese government to measure industrial congestion from different perspectives. However, most studies for measuring congestion only consider desirable outputs, even if, in practice, these are always accompanied by undesirable outputs. In this paper, three policy objectives are proposed for industrial development in China: the economic priority, the environmental priority, and the economic and environmental win-win. Three new data envelopment analysis (DEA) models with undesirable outputs were built for measuring undesirable congestion, desirable congestion, and double-congestion, respectively, for these policy objectives. These approaches can, not only identify congestion situation, but also calculate the total amount of congestion, and were applied to an analysis of the congestion of regional industries in China. Results show that most regions have some form of longstanding input congestion under different policy objectives, with this resulting in serious waste of resources. Based on the results obtained, some suggestions for sustainable industrial development in China are proposed. [ABSTRACT FROM AUTHOR]

The energy conservation has become a considerable issue in construction industry for achieving sustainable development. Therefore it is crucial for policy-makers to look for optimized and flexible tools to measure the total energy consumption efficiency in construction industry. Data envelopment analysis (DEA) can be applied for multiple input and output decision-making units (DMUs) productivity measurement. DEA-based Malmquist productivity index (MPI) can be used as a tool for measuring the productivity change longitudinally. In this paper, we use input-oriented model to measure the energy consumption productivity change of the construction industry from 2004 to 2009 with data in 26 provinces of China. It is found that only Guangdong demonstrated effective energy improving in the whole reference period. It also identified the regional groups always lie on the efficiency frontier of energy consumption as benchmarks. Regional analysis shows that energy conservation gaps exist between northeastern, western region and central, eastern region. DEA-based Malmquist productivity index provides a good way to measure the energy consumption efficiency and can help policy-makers to improve strategies of sustainable development in China. [ABSTRACT FROM AUTHOR]

Excessive CO 2 emissions from manufacturing has become a major factor that constrains China's sustainable economic development. Therefore, considering the regional and industrial heterogeneities, this paper introduces a global multi-hierarchy meta-frontier Data Envelopment Analysis approach to analyze the dynamic performance of CO 2 emissions and to estimate the current CO 2 emissions inefficiency and reduction potential in the manufacturing industry of China's 30 provinces, which are separated into three components, namely, structural characteristics, technology gaps, and resource allocation levels. The results show that: (1) From 2003 to 2015, the CO 2 emissions efficiency of China's manufacturing industry increased by a factor of 4.7, of which technological progress and optimization of industrial structure were the main driving forces. (2) At present, the CO 2 emissions inefficiency of the manufacturing industry in mainland China is 0.7804, reflecting that 78.04% of its total CO 2 emissions is excessive emissions, which is mainly caused by the low allocation efficiency. (3) The heavy sub-industry and the east region have the greatest potential for CO 2 emissions reduction in the manufacturing and in the three regions of the country, respectively. In addition, by promoting the industrial restructuring, regional coordinated development, and strengthening the environmental regulations and promoting market-oriented reforms, China's manufacturing industry could reduce 29.65%, 11.55% and 36.84%, respectively, of its current CO 2 emissions. Based on the estimation results, this paper also points out the short-term and long-term directions for industrial structure adjustment and develops the specific paths for China's 30 provinces to achieve CO 2 emissions reduction in manufacturing industry. • CO 2 emissions efficiency of China's manufacturing industry increased by 4.7 times. • Technological progress are the primary driving force for efficiency improvement. • CO 2 inefficiency and reduction potential show a spatial difference characteristic. • 78.04% of the total CO 2 emissions can be reduced by corresponding measures currently. • The CO 2 emissions reduction strategies are formulated for China's 30 provinces. [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: This paper computes the three major types of efficient electricity, coal, and gasoline oil savings for 27 regions in China during the period 2000–2003. The data envelopment analysis (DEA) with a single output (real GDP) and five inputs (labor, real capital stock, coal consumption, gasoline oil consumption, and electricity consumption) is used to compute the energy-saving targets of each region for each year. The efficient energy-saving ratios of each region in each year are obtained by comparing the actual energy inputs to target energy inputs. Our major findings are as follows: 1. The east area contains most of the efficient regions with respect to the three major types of energy in every year during the research period. 2. The east, central, and west areas have 2000–2003 average target saving ratios of coal consumption at 18.58%, 44.00%, and 59.80%, gasoline consumption at 13.43%, 22.70%, and 45.04%, and electricity consumption at 8.55%, 16.42%, and 43.70%, respectively. 3. Compared to the cases of gasoline oil and electricity, coal consumption saving is China’s most urgent task. [Copyright &y& Elsevier]

Accurate evaluation of emission governance efficiency can build fundament to develop haze control strategy towards sustainable development. By features of the haze, we view the haze formation stage as the first sub-process and the haze control stage as the second sub-process. This paper proposes an additive aggregation network data envelopment analysis (DEA) model with undesirable intermediate measures and undesirable outputs, which have not been thoroughly studied in previous literature. We found the newly developed network DEA model was nonlinear and cannot be converted into a linear program, and then developed an improved second-order cone programming approach to solve this problem. After analyzing the data of haze control in China, we drew the following conclusions: Firstly, different weights of preference for two sub-process can lead to the variation in the overall efficiency. Under different weights of preference, although the efficiency of the haze formation has a very small change in some provinces, the efficiency of the haze control has a large change. Secondly, decision makers can achieve the adjust goal of reducing haze by adjusting their preferences on the information of the haze formation and haze control stages, which are helpful for policy making in haze control strategy and sustainable development. [ABSTRACT FROM AUTHOR]

While shouldering the burden of economic development, China's industrial sector has significant water consumption and wastewater discharge, which has intensified the country's water shortage. To improve the efficiency of industrial water resource utilization system, data envelopment analysis (DEA) has been widely used to assess the performance of the system. The current network DEA approaches adopted to investigate the system all belong to the self-evaluation mode, and existing network DEA cross-efficiency evaluation approaches have shortcomings. Therefore, a two-stage DEA approach with game cross efficiency is proposed to evaluate the system. First, according to the operation process of the system, this paper decomposes the system into a general two-stage network structure: water use stage and wastewater treatment stage. Second, the DEA game cross-efficiency model is improved to the general two-stage DEA game cross-efficiency model to evaluate the overall efficiency of the system. Third, given the overall efficiency, an efficiency decomposition model is proposed to determine a set of weights for each decision-making unit to evaluate water use efficiency and wastewater treatment efficiency. Finally, the rationality of the proposed approach is illustrated by model comparison, and the efficiencies of industrial water resource utilization systems in 31 regions of China from 2010 to 2015 are evaluated based on the proposed approach. The results indicate that, from the overall efficiency perspective, no region in China is always evaluated as being overall efficient and the overall efficiencies of 17 regions show an increase before a decreasing trend or decreasing trend during the study period. In 11 regions, wastewater treatment efficiency is far lower than water use efficiency, and in 11 other regions, both sub-stages are inefficient. In terms of the three areas, the eastern area has the highest water use efficiency, the central area has the lowest efficiency of both sub-stages, and the western area has the highest wastewater treatment efficiency. Some recommendations are presented to ensure China's sustainable development. [ABSTRACT FROM AUTHOR]

• We measure the green growth degree of China's industrial sectors by considering the constraint of total energy consumption. • We proposed a new common equilibrium efficient frontier, which considers each DMU's own adjustment strategy on fixed-sum energy input. • The proposed approaches are applied to analyze the green growth and energy and environmental efficiency of 36 of China's industrial sectors. Tight energy constraints and severe environmental pollution are two main problems affecting economic growth and sustainable development. As an important economic growth mode, green growth seeks to achieve both economic growth and environmental sustainability. Previous studies on the efficiency evaluation of green growth ignored fixed-sum energy consumption; this is a significant omission because this constraint is general in China: the government has set targets to reduce energy consumption by 20% and 16% per unit of GDP during its the eleventh (2006-2010) and twelfth (2011-2015) five-year plans. To fill this gap, we propose a new data envelopment analysis (DEA) model to analyze the green growth degree of China's industrial sectors. The proposed DEA model considers the constraint of total energy consumption in order to conform to the policy of energy and emission reduction. Previous theoretical studies on fixed-sum output construct the common equilibrium efficient frontier (CEEF) only by considering the minimal reduction strategy for the fixed-sum output of all decision making units (DMUs), while ignoring each DMU's adjustment strategy for fixed-sum input/output. In this paper, we construct a new CEEF by considering each industrial sector's adjustment of energy consumption. The new CEEF not only guides the industrial sectors to alter their energy consumption structure to achieve green growth but also allows a more accurate evaluation of the energy and environmental efficiency (EEE) of industrial sectors. Last, our proposed model is applied to analyze the green growth and EEE of 36 of China's industrial sectors. [ABSTRACT FROM AUTHOR]

China's transport sector has been attracting great attention for its excessive energy consumption and ever-increasing pollution emissions. Thus, reducing energy intensity is one of the top priorities of China's ongoing transport upgrade. In this paper, by establishing a panel data regression model derived from the Cobb–Douglas cost function, we focus on investigating the impacts of energy price and transport productivity on transport energy intensity at the national and regional levels. The study uses the provincial panel data for 2005–2016 to perform regression analysis. The results show that: (1) energy price has a significantly negative effect on transport energy intensity in the whole China and the eastern region, whereas it has no significant impacts in the central and western China. (2) Improvements in transport productivity can effectively decrease transport energy intensity in the whole China and the three major regions. (3) Applying an extended data envelopment analysis (DEA) approach, we decompose transport productivity into four components (i.e., technical change, technology gap change, scale efficiency change, and pure efficiency change) and further differentiate their impacts in different regions. The results indicate that these four components have substantially different impacts in each region. These results provide some valuable insights for policymakers and enterprise entities aiming to adopt measures to reduce energy intensity and achieve sustainable development in China's transport sector. • The regional heterogeneous impacts of energy price and productivity on transport energy intensity in China are examined. • The transport productivity change is further decomposed into four components. • Energy price has a significantly negative effect on transport energy intensity in eastern region. • The impacts of four components of transport productivity change on energy intensity vary by region. [ABSTRACT FROM AUTHOR]

Using panel data from 2003 to 2016, this paper estimates the green development efficiency of 34 cities in Northeast China based on the SBM-DEA model and determines whether industrial agglomeration promotes or impedes green development efficiency. The results show the following: (1) The average green development efficiency of Northeast China exhibits a fluctuant upward trend in 2003–2016, and there are significant spatial differences. (2) During the revitalization period, industrial agglomeration hinders green development efficiency. A U-shaped relationship exists between industrial agglomeration and green development. (3) Economic development level and foreign direct investment are positively related to green development efficiency, while industrial structure, energy consumption structure and environmental regulation are negatively related. Economic development level has the greatest positive influence and environmental regulation the strongest negative influence on green development. Several corresponding policy implications are proposed for promoting green development and revitalization. • The average green development efficiency of Northeast China exhibits a fluctuant upward trend. • Significant spatial differences exist in the green development efficiency in Northeast China. • A U-shaped relationship exists between industrial agglomeration and green development. • Economic development has the greatest positive effect on the green development. • Environmental regulation has the strongest negative influence on green development. [ABSTRACT FROM AUTHOR]

How to use foreign direct investment (FDI) to achieve sustainable development of resources, environment and economy in China has become an increasingly important proposition. Previous studies mainly focused on the relationship between FDI quantity and energy efficiency, and neglected the important role of FDI quality in improving energy efficiency. Based on the panel data on 30 provinces in China from 2003 to 2016, this paper uses slacks-based measure data envelopment analysis (SBM-DEA) method to estimate energy efficiency, and then uses seemingly unrelated regression (SUR) method to empirically study the influence of FDI quality on energy efficiency. The results are presented as follows: (1) From the national level view, FDI quality plays a significant role in promoting China's energy efficiency; (2) From the regional-level view, FDI quality plays a significant role in promoting China's energy efficiency in coastal and inland areas, but its role in the inland area is significantly greater than that in the coastal area. The results indicate that China should make full use of the opportunity of global economic integration and pay more attention to the improvement of FDI quality, so as to promote energy efficiency and low-carbon economic development. • The important role of FDI quality in improving energy efficiency is studied. • SUR method is used to avoid autocorrelation between data sections. • SBM-DEA method is used to estimate energy efficiency. [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]