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China's paper industry accounts for a larger proportion of the global paper industry and consumes large amounts of energy. Energy conservation and pollution reduction of the industry have become the focus of China's national development strategy. Energy efficiency is an important index which directly determines the amounts of energy consumption and pollution emissions. To understand the energy efficiency evolution of China's paper industry, this paper establishes an input-output data of the paper industry for 29 provinces in China and applies DEA method and econometric models to estimate and comprehensively discuss the energy efficiency issues based on the framework of total factor efficiency. Our results indicate that China's paper industry has a large energy saving potential even though its energy efficiency has improved during the period 1990–2013. The saving potential is about 65% under the meta-frontier and 44% under the group-frontier. Moreover, there are significant differences between different regions in production technology and energy efficiency. The performance of eastern China is better than other regions. But the technology gaps between the different regions are shrinking and converging over time. Finally, some policy recommendations are proposed to improve the energy efficiency of the industry. [ABSTRACT FROM AUTHOR]

The paper reports results from a use of non-radial DEA i.e., range adjusted measure (RAM) which belongs to data envelopment analysis to evaluate the performances of the truck restriction policy in China. We try to explore what is inside the "black box" on the restriction policy by empirical study. Using the non-radial DEA model, we work with an approach that allows a flexible designation of three input variables and two output variables based on varying perspectives in China. The multipurpose approach reveals whether one policy is truly beneficial instead of officials' arguments, captured in the form of DEA scores. The modified model can better reflect macro-transportation process while earlier relevant models ignored truckers. This paper contributes to increasing traffic volumes and decreasing traffic accidents from the point of technical efficiency. The results of our paper reveal that: (a) China's truck restriction policies have achieved a significant "level effect" on efficiency improvement. (b) There are remarkable provincial differences in the effectiveness of the restriction policy. (c) Slack decomposition shows that excessive investment is the main source of inefficiency. Moreover, we delivery policy implications that: (a) the restriction policies greatly contribute to the efficiencies, and stringent policies are still needed in the following days; (b) the policy-making should suit local conditions, according to our classification of 30 provinces; (c) based on the worst performance of capital stock variable, the authorities should focus more on regulation of investment in transportation sector at a latter stage. [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]

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]

Aquavoltaic is an essential tool in overcoming the ground-based photovoltaic (PV) development barrier and achieving China's carbon neutrality target. After summarizing aquavoltaic technologies and global cases, this paper assesses the effectiveness of 292 aquavoltaic plants in China using the data envelopment analysis (DEA) method. Six essential input and output variables are included: installed capacity, power generation, occupied water area, construction cost, PV modules, and global horizontal irradiation to offer an appropriate measure of aquavoltaics efficiency in China. This study also performed correlation analysis for PV module type, PV mounting mode, and ownership based on a Tobit regression model. The results show that the efficiencies of China's aquavoltaics have improved significantly between 2014 and 2022, with the emergence and popularity of high-power PV modules playing a pivotal role. Furthermore, the regional study discovered provincial efficiency varies substantially. This paper also gives two reference indicators for new aquavoltaics in the future. • The global aquavoltaic technologies and cases were summarized. • The history and status quo of aquavoltaics in China were reviewed. • Aquavoltaics' energy efficiency has increased significantly in China. • The high-power PV modules have a positive impact on efficiency growth. [ABSTRACT FROM AUTHOR]

China has developed a remarkable economic growth in the past 30 years by accompanying with undesirable outputs. The assumptions of weak and strong of undesirable outputs have become the focus discussion in data envelopment analysis (DEA) models. To have a comprehensive environmental efficiency measurement, this paper proposes three DEA models considering weak disposability, strong disposability and distinguishing weak and strong disposability of undesirable outputs, respectively. We further combine with the Malmquist-Luenberger productivity index to assess the environmental efficiency and the dynamic change trend of 30 provinces in China from 2005 to 2014. The results show that distinguishing technical features of undesirable outputs makes a significant difference to final environmental efficiency score at different regions. The environmental efficiency of the whole nation, however, does not show any increasing trend during the ten years. Enhancing environmental efficiency of central and west area is an urgent task for Chinese government. The change trend of Malmquist-Luenberger productivity index and technological change shows a similar shape. Technical progress is the main driving force to enhance the environmental efficiency. Relevant suggestions are presented for improving the regional environmental efficiency in China in the future. [ABSTRACT FROM AUTHOR]

This paper utilizes the slacks-based measure (SBM) undesirable model to analyze the environmental regulation efficiency (ERE) from 2003 to 2013, and uses the Data Envelopment Analysis (DEA) Malmquist productivity index to divide the environmental regulation total factor productivity (ERTFP) into a technical progress index, pure technical efficiency index and a scale efficiency index from the perspective of scale change. The results show that the ERE presents “polarized” effect and the ERTFP has an obvious “agglomeration” effect in China. There is also a very significant “match-up” effect between the ERE and economic development level. In addition, the paper also finds that the technical progress index has the largest contribution to ERTFP, followed by pure technical efficiency index and then the scale efficiency index. The preceding results can provide scientific suggestions for regional environmental departments. [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]

• A high spatial resolution CO 2 emissions inventory of 280 Chinese cities was compiled. • Three methods were compared to evaluate the carbon efficiency of Chinese cities. • The best and worst-performing cities were consistent regardless of different methods. • Top-ranking cities were located in the coastal regions of China. • Lagging-behind cities were located in the central and western regions of China. Comprehensive and accurate city-level carbon dioxide emissions inventory is key to success in China's pursuit of low-carbon development. Based on a high-resolution gridded data, this paper evaluates and benchmarks the carbon emissions efficiency of 280 Chinese cities using three different methods, i.e., composite index, data envelopment analysis and stochastic frontier analysis. The comparative analysis reveals that the average carbon emissions efficiency of Chinese cities is about 70–90%, with only 9 efficient cities (3%). Although the ranking of intermediate cities varies greatly according to the method employed, the most and least carbon-efficient cities remain consistent. While the best-performing cities are found in the coastal regions, the worst-performing cities are located in the central and western regions, which suggests an imbalanced low-carbon development in China. Guided by the results, local governments are encouraged to compete and learn from similar ranking benchmarks in a new regime of "Top Runner City". Finally, the scores of carbon emissions efficiency can provide a scientific basis for the bottom-up allocation of carbon emissions rights to boost the development of the nationwide carbon market in China. [ABSTRACT FROM AUTHOR]

The development of transport infrastructure is characterized by intensive capital input, intensive energy consumption, and pollution emissions. Against the background of the continuous intensification of resource and energy constraints in China. Therefore, the analysis of China’s regional transport efficiency and its determinants has practical significance. This paper attempts to evaluate regional total factor transport efficiency in China based on the Super-SBM DEA model considering undesirable output and explores the influence factors of transport efficiency in China during the period 1995–2012. The empirical results indicate that during the research period, most provinces in China are not performing efficiently in transport systems. Additionally, the overall average level of China’s total factor transport efficiency is low and the spatial pattern of the total factor transport efficiency demonstrates a declining trend from eastern to western China, which coincides with the spatial pattern of economic development in China. The analysis of the influence factors by the regression model shows that economic development and government influence can decrease overall transport efficiency, while industrial structure, population density, and geographical position can influence transport efficiency. The influence of these factors varies by region. Finally, this paper provides policy recommendations to improve transport efficiency in China. [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]

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]

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]

Alleviating energy poverty is a significant issue in many countries, for which effective energy poverty measurement is the prerequisite. This paper seeks to make a comprehensive and systematic assessment of the energy poverty performance of 30 provinces in China for 11-year period (2007–2017) by emphasizing their spatial-temporal changes. The paper firstly constructed energy poverty measurement conceptual framework based on overviewing previous studies. Secondly, a technique based on the integrated fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) and Data Envelopment Analysis - Assurance Region (DEA-AR) for performance assessment was proposed. Then, the energy poverty performance was assessed, and clustering analysis was conducted to investigate the spatial-temporal changes of energy poverty in China. Finally, sensitivity analysis was applied for verifying the robustness of the proposed method. It is found that the energy poverty condition in China tends to be similar among most regions, but the gap between the best and worst performers gets wider. In addition, provinces with better economic conditions, have higher performance and are classified into the progressive group for alleviating energy poverty. On the contrary, provinces, whose economy lags, have regressed the most and are also the worst performers in reducing energy poverty. Thus, policies to improve household energy cleanability in high-income provinces and increase energy affordability in low-income regions would help reduce energy poverty in China. • A comprehensive energy poverty assessment framework was proposed. • An integrated Fuzzy DEMATEL/DEA-AR was proposed to evaluate the performance. • The comparison between the proposed Fuzzy DEMATEL/DEA-AR model and conventional DEA was conducted. • Spatial and temporal analysis of energy poverty performance in China was conducted. [ABSTRACT FROM AUTHOR]

Based on energy and CO 2 emission efficiencies, this paper proposes a definition of the elasticity of the potential of emission reduction to energy saving ( E peres ), and measures the elasticity in China’s 30 provincial regions. Although E peres is a relative definition, it can be used (1) to measure the amount of reduced CO 2 emissions per unit fossil energy saving, (2) to reflect the effectiveness of fossil energy saving for CO 2 emission reduction in different regions, and (3) to provide decision-making criteria for selecting pathways for emission reductions in different regions. The results show that compared with energy saving, emission reduction is a more serious issue in China. This indicates that energy saving policies have been highly effective since their implementation during the 11th “Five-Year Plan”. With respect to provincial disparities, the emission reductions caused by fossil energy saving are not significant in Beijing, Shanghai, and Guangdong. Fujian province has significant E peres , indicating that emission reduction causing by fossil energy saving is effective. E peres has been increasing over time in Hunan and Hubei. Hainan’s E peres has remained less than 1, indicating that its emission-reduction effect of fossil energy saving is worse than in other provinces. Moreover, the elasticity of Eastern China is greater than that of Central China and Western China. This finding sheds light on pathway selection for energy saving and emission reduction in China: it would be more appropriate to encourage fossil energy saving in Eastern China, and to promote clean energy use (e.g., water electricity and solar energy) in Central China and Western China. [ABSTRACT FROM AUTHOR]

This paper proposes a total-factor energy consumption performance index (TEPI) for measuring China's energy efficiency across 30 provinces during the period 1997 to 2012. The TEPI is derived by solving an improved non-radial data envelopment analysis (DEA) model, which is based on an energy distance function. The production possibility set is constructed by combining the super-efficiency and sequential DEA models to avoid “discriminating power problem” and “technical regress”. In order to explore the impacts of technological progress on TEPI and perform statistical inferences on the results, a two-stage double bootstrap approach is adopted. The important findings are that China's energy technology innovation produces a negative effect on TEPI, while technology import and imitative innovation produce positive effects on TEPI. Thus, the main contribution of TEPI improvement is technology import. These conclusions imply that technology import especially foreign direct investment (FDI) is important for imitative innovation and can improve China's energy efficiency. In the long run, as the technical level of China approaches to the frontier, energy technology innovation and its wide adoption become a sustained way to improve energy efficiency. Therefore, it is urgent for China to introduce measures such as technology translation and spillover policies as well as energy pricing reforms to support energy technology innovation. [ABSTRACT FROM AUTHOR]

The use of data envelopment analysis (DEA) in China’s regional energy efficiency and carbon emission efficiency (EE&CE) assessment has received increasing attention in recent years. This paper conducted a comprehensive survey of empirical studies published in 2006–2015 on China’s regional EE&CE assessment using DEA-type models. The main features used in previous studies were identified, and then the methodological framework for deriving the EE&CE indicators as well as six widely used DEA models were introduced. These DEA models were compared and applied to measure China’s regional EE&CE in 30 provinces/regions between 1995 and 2012. The empirical study indicates that China’s regional EE&CE remained stable in the 9th Five Year Plan (1996–2000), then decreased in the 10th Five Year Plan (2000–2005), and increased a bit in the 11th Five Year Plan (2006–2010). The east region of China had the highest EE&CE while the central area had the lowest. By way of conclusion, some useful points relating to model selection are summarized from both methodological and empirical aspects. [ABSTRACT FROM AUTHOR]

This paper estimates water use efficiency of 31 provinces in China during 2004–2013 using slack based measure-data envelopment analysis (SBM-DEA) model which takes consideration of sewage. By using panel data model, factors that influence water use efficiency are explored. The results show that: (1) water use efficiency is higher in economically developed provinces such as Beijing, Shanghai and Tianjin. (2) In general, inefficiencies of labor input and water input are larger than that of capital input. (3) After taking into account sewage as unexpected output, inefficiency of gross domestic product (GDP) for each province is quite low, but most provinces have inefficient sewage emission. (4) It is found in the analysis of influencing factors that the ratio of added value of agricultural sector, water usage per capita and sewage per unit of output have negative impact on water resources use efficiency, while the import dependence and export dependence have positive impact. The results are robust. [ABSTRACT FROM AUTHOR]

Abstract: The suitability of the project delivery system (PDS) selected for a project greatly influences the efficiency to conduct a project. It is not an easy task to select an appropriate PDS as a large amount of ambiguous information exists. The paper aims to develop a PDS selection model to help owners to make a decision. The similar projects are identified through the similarity metrics between the target project to be predicted and those in the database. In addition, some of the indicator values are examined and modified through DEA-BND model, and then they are trained by ANN model to predict an appropriate PDS for the target project. A survey was conducted by postal questionnaire to empirically validate the reliability of the model in China. The indicator system for the selection of an appropriate PDS is established. Through the comparison of results predicted by different models, it is found that the PDS selection model developed in this paper can predict PDS precisely, and shows higher reliability than the ANN model. A PDS selection model is developed by inputting project-specific data, which proves to be more accurate and less dependent on experts’ judgment. Its practical application will benefit the owner’s decision making in the selection of the PDS. [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]

This paper introduces an improved total-factor ESTR (energy-saving target ratio) index, which combines the sequence technique and the “energy direction” to a DEA (data envelopment analysis) model, in order to measure the possible energy saving potential of a manufacturing sector. Afterward, the energy saving potentials of four different energy carriers, namely coal, gasoline, diesel oil and electricity, for 27 manufacturing sectors during the period of 1998–2011 in China are calculated. The results and its policy implications are as follows: (1) the average ESTRs of coal, gasoline, diesel oil and electricity are 1.714%, 49.939%, 24.465% and 3.487% respectively. Hence, energy saving of manufacturing sectors should put more emphasis on gasoline and diesel oil. (2) The key sectors for gasoline saving is the energy-intensive sectors, while the key sectors for diesel oil saving is the equipment manufacturing sectors. (3) The manufacture of raw chemical materials and chemical products sector not only consumes a large amount of oil, but also has a low efficiency of oil usage. Therefore, it is the key sector for oil saving. (4) Manufacture of tobacco and manufacture of communication equipment, computers and other electronic equipment are the benchmark for the four major energy carriers of energy-saving ratios. [ABSTRACT FROM AUTHOR]

With the growing expenditure on the R&D activities of industrial enterprises above designated size (IEDSs) in China, it is important to evaluate the R&D efficiency of the Chinese IEDSs. However, few studies about R&D efficiency measurement of Chinese IEDSs have considered the internal structure of the R&D production process. To fill this gap, this paper investigates the R&D performance of IEDSs of 30 sample provinces on China's mainland from 2009 to 2014, based on a two-stage data envelopment analysis (DEA) model. The major findings from the empirical results are shown as follows: (i) serious imbalance exists in the R&D resources among Chinese IEDSs of 30 provinces; (ii) there is a decline in the average overall efficiencies after 2012; (iii) there are great differences regarding the performances of R&D activities among the Chinese IEDSs of 30 provinces; (iv) high attention to the R&D activities or strong scientific research atmosphere may promote the R&D efficiency of Chinese IEDSs; and (v) the IEDSs with the relatively high profitability or high government support in terms of R&D activities have relatively poor performance. Based on these findings, several policy suggestions are proposed for the R&D activities of Chinese IEDSs. • Few studies about R&D efficiency evaluation of Chinese IEDSs considered the internal production structure. • We investigate the R&D performance of IEDSs of 30 sample provinces on China's mainland. • A two-stage data envelopment analysis model is used in this paper. • We have several important findings from the empirical results. • Several policy suggestions are proposed for the R&D activities of Chinese IEDSs. [ABSTRACT FROM AUTHOR]

Emissions trading system (ETS) is a cost-effective way towards achieving the carbon neutrality goal. Based on the gaps in the research on carbon allowance allocation vis-à-vis the carbon neutrality target, this study examines how to allocate carbon allowances equitably and effectively among Chinese provinces. Different from the previous research that mainly considers responsibility, ability, and potential of equity dimensions, this paper proposes a composite indicator allocation approach based on the equity of history, demand, contribution, and guarantee, and it also employs the entropy method and expert survey method to obtain the indicator weight values in different scenarios. Results show that the carbon allowances of some provinces, such as the forest-rich province of Yunnan, vary significantly in five scenarios, but little differences are observed for some provinces, such as the high historical emissions province of Shanxi. More provinces achieve data envelopment analysis efficiency in the preferred scenario. Compared with the objective scenario, the required emission reduction in the preferred gross domestic product (GDP) scenario is 231 million tonnes less, and the emission reduction cost is 190 billion yuan less. It is suggested that the Chinese government should adopt the allocation scheme in preference for the GDP scenario. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a non-radial DEA approach consisting of both a static and a dynamic environmental performance index (EPI) for measuring environmental performance. The static EPI is defined as the ratio of a non-radial efficiency measure for reducing undesirable outputs to that for increasing desirable outputs. The proposed non-radial DEA approach has been applied to model the environmental performance of industrial sectors in different provinces of China from 1998 to 2009. It has been found that the static non-radial EPI has a higher discriminating power than the EPI derived from the non-radial undesirable outputs orientation DEA models. Our empirical results also show that the environmental performance of industrial sectors in China improves by 58% in 1998–2009 that is mainly driven by the technological change. [Copyright &y& Elsevier]

Abstract: Evaluation of the energy and emissions efficiency of Chinese regions has recently attracted increasing interest. A number of previous studies have contributed to the measurement of energy efficiency using various types of data envelopment analysis (DEA) techniques. However, most of these DEA-based energy efficiency analyses were restricted to the radial expansions of outputs or radial contractions of inputs. In this paper, we utilize the multi-directional efficiency analysis (MEA) approach instead of the traditional radial DEA to investigate Chinese regional energy and emissions efficiency. Since MEA selects benchmarks such that the input contractions or output expansions are proportional to the potential improvement identified by considering the improvement potential in each input or output variable separately, not just the efficiency status but also the efficiency patterns of different Chinese regions and areas can be detected. The empirical study results indicate that, in general, the MEA efficiency of China experienced an increasing process over the study period 1997–2010; the east area overall is more MEA efficient than the central area and the west area of China during the study period; the significant higher MEA efficiency of the east area to the central area and the west area are due to both the higher energy specific efficiency and the higher emissions specific efficiency of the east area compared to the other two areas; the provinces of Hebei, Shanxi, Inner Mongolia, Shandong, Henan, and Hubei etc. have both high energy saving potentials and high emissions reduction potentials, thus they will play the most important roles in China’s effort on energy conservation and CO2 emissions mitigation. [Copyright &y& Elsevier]

Abstract: This paper uses nonparametric efficiency analysis technique to estimate the energy efficiency, potential emission reductions and marginal abatement costs of energy-related CO2 emissions in China. We employ a non-radial slacks-based data envelopment analysis (DEA) model for estimating the potential reductions and efficiency of CO2 emissions for China. The dual model of the slacks-based DEA model is then used to estimate the marginal abatement costs of CO2 emissions. An empirical study based on China’s panel data (2001–2010) is carried out and some policy implications are also discussed. [Copyright &y& Elsevier]

Abstract: Eco-efficiency is an instrument for sustainability analysis, indicating how efficient the economic activity is with regard to nature''s goods and services. This paper conducts an eco-efficiency analysis for regional industrial systems in China by developing data envelopment analysis (DEA) based models. Using real data of 30 provinces in China, an empirical study is employed to illustrate the pattern of regional industrial systems'' eco-efficiency. The results indicate that Tianjing, Shanghai, Guangdong, Beijing, Hainan and Qinghai are relatively eco-efficient. The results also show that, provinces with higher level GDP per capita will have higher eco-efficiency relatively with an exception of Hainan and Qinghai. The study provides deeper insights into the causes of eco-inefficiency, and gives further implications on environmental protection strategies in China. In the article, we also discuss the advantages and disadvantages of using DEA in eco-efficiency analysis and areas that require further work are presented. [Copyright &y& Elsevier]

Hospital efficiency and equity in health care delivery are two enduring research topics. Yet little research has been done to examine the relationship between them. This paper studies the impact of hospital efficiency on equity in health care delivery based on a proprietary dataset of hospital characteristics and 630,000 inpatient records from 149 public hospitals in a representative Chinese city. To measure the hospitals' efficiencies, this study takes the hospitals' operational features and case-mix indexes into account, and computes the efficiency levels using data envelopment analysis with bootstrapping. Through regressions that control for a variety of the patients' personal characteristics (e.g., age, disease, residence, hospital visit frequency), this study shows that the gap between hospitalization expenses of urban and rural inpatients in more efficient hospitals is smaller than those in less efficient hospitals. Thus efficiency enhances equity in expenditure between urban and rural patients. But the dwindling urban-rural gap in expenditure is achieved by raising the spending of rural patients, thereby undermining their access to health care. This pattern is more conspicuous in large and sophisticated high-tier hospitals. Further analysis shows that hospital efficiency impacts equity of health care delivery by inducing different lengths of stay and uncovered parts of total expenditure for urban and rural groups. The findings imply that an efficiency-oriented health care policy may lead to social benefit loss. • The link between hospital efficiency and equity of medical expenditure is studied. • Hospital efficiency and urban-rural spending gap show an inverse relationship. • Falling urban-rural spending gap occurs with impaired access from rural patients. • An efficiency-oriented health care policy may lead to social benefit loss in China. [ABSTRACT FROM AUTHOR]

• City-level agricultural production efficiency is mapped by Super-Efficiency Data Envelopment Analysis model. • The agricultural production efficiency is featured as spatial agglomerations. • The OLS and GWR models are used to explore the spatial heterogeneity and driving mechanisms of agricultural production efficiency. • Series of policy recommendations are provided. The level of agricultural production efficiency (APE) affects farmers' livelihood decisions and the transformation and reconstruction of the rural territorial system. This paper constructs an evaluation index system of China's APE from the perspective of input–output. The spatial autocorrelation model and econometric model are used to calculate the spatio-temporal evolution characteristics and influencing factors of China's APE in 1990 and 2017. The results show that China's APE level is relatively low, and there are significant spatial differences. The extremely high efficiency regions are distributed in the eastern plains of China; the regions with extremely low efficiency are mainly distributed in the southwest and the western regions of China. The results of the spatial correlation effect show that the H-H agglomeration regions of APE are usually distributed in the eastern coastal areas and northeastern areas, while the L-L agglomeration regions are mainly distributed in the central mountainous areas and the border areas of western Yunnan. From 1990 to 2017, the influencing factors of APE have gradually changed, and showing a more complex trend, mainly including farmland management scale , multiple crop index, rural per capita net income, population density, and precipitation per unit area. Finally, the corresponding policy and suggestions are provided. [ABSTRACT FROM AUTHOR]

To our knowledge, the previous studies did not answer the following questions: how much does window analysis differ from the original Data Envelopment Analysis (DEA) approaches and how to develop DEA window analysis? To address these questions, we propose three intermediate approaches (cross-sectional approach, window efficiency analysis and window index approach) and statistically compare their performances. The underlying concern is that we need to examine whether a metrological bias exists in our study. The concern is important in guiding policy issues such as energy policy and climate change. Empirically, the proposed approaches are applied to measure the unified efficiency of fossil fuel power plants at a provincial level in China from 2007 to 2017, since these plants are important energy consumers and CO 2 emitters. We obtain two important implications. First, considerable differences were confirmed among the three approaches, thus implying an existence of the methodological bias. Second, Beijing (the capital of China) outperformed the other provinces in terms of their measures, since the government has paid serious attention to air pollution emitted from fossil fuel power plants. The governmental regulation in Beijing is a good example of pollution prevention in China. It is expected that the success on Beijing will be disseminated to the other provinces. This paper proposed three approach, i.e. one conventional approach (cross-sectional approach) and two new approaches (window efficiency analysis and window index approach). The two new approaches were capable of measuring efficiency shifts or technology shifts over time. Empirically, these approaches were adopted to evaluate the performance of Chinese fossil fuel power plants. Image 1 • We evaluate the performance of China's fossil fuel power plants from 2007 to 2017. • Three formulations are utilized for DEA intermediate approach. • The first policy effort was put on Beijing and gradually on other provinces. • China made a progress on economic and environmental measures during this period. [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]

• The potential gains and carbon emissions reduction of carbon trading are detected. • Three scenarios of carbon trading schemes are considered and compared. • Sectoral trading may create potential gains of 268.02 trillion yuan in 2006–2015. • Carbon emissions may decrease by 17.17 billion tonnes under sectoral trading scheme. • Sectoral trading decreases industrial carbon intensity by 19.80% during 2015–2020. Carbon trading is an important market tool in driving growth and carbon dioxide emissions reduction in industrial sectors in China. This paper attempts to assess the impacts of carbon trading on economic output and carbon dioxide emissions reduction in China's industrial sectors by employing the data envelopment analysis (DEA) based optimization models, based on three carbon trading schemes, i.e., no trading (NT), sectoral trading (ST), and sectoral-and-temporal trading (STT) during 2006–2015. Comparing with the no-trading scheme, the results indicate that, (1) the ST and STT schemes may create potential gains of 268.02 and 612.26 trillion yuan in the whole industrial during the study period, i.e., the industrial value-added would be increased by 55.17% and 73.76%, respectively; (2) the ST and STT schemes could reduce 17.17 and 19.22 billion tonnes of carbon dioxide emissions, respectively, accounting for 58.30% and 65.25% of emissions reduction in the whole industry; and (3) if carbon trading were adopted in China since 2006, its carbon intensity of industrial sectors would decrease by 34.89%, 47.44% and 19.80% under the ST scheme, and 58.93%, 31.50% and 10.25% under the STT scheme during the11th, 12th and 13th Five-Year Plan periods, respectively. [ABSTRACT FROM AUTHOR]