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The frequent trade within and beyond the Belt and Road Initiative (BRI) has prospered the economy but has also expanded carbon emissions. Here, through a multi-regional environmental input-output analysis framework, we explore the patterns and inter-sectoral linkage of trade-embodied carbon emissions among BRI countries during 2015-2019. Then, a dynamic data envelopment analysis model considering carbon inequality as a non-discretionary input is constructed to assess the carbon emission efficiency of the identified key sector. We find that trade-embodied carbon emissions in the BRI steadily increased during 2015-2019. The manufacturing sector was identified as the key sector, exhibiting an overall efficiency of 0.6268 on average, with significant efficiency disparities. Moreover, we validate the positive role of efficiency enhancement in carbon emission mitigation, as well as the negative moderating effect of carbon inequality. Overall, this study provides optimal collaboration and initiatives to mitigate trade-embodied carbon emissions among BRI countries deeply.

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The improvement of energy-related efficiency has promoted energy-sustainable development in China; however, it may be inhibited by energy poverty. This paper constructs an index system to measure China's energy poverty. Subsequently, we evaluate energy-related efficiency towards SDG7 comprised of energy production efficiency and energy sustainable utilization efficiency using a dynamic two-stage data envelopment analysis model. Furthermore, we adopt fixed effect models to quantify the impact of energy poverty on improving energy-related efficiency and the underlying mechanism. The findings indicate that: (1) China's energy poverty situation gradually improves from 2011 to 2020. The energy-related system's performance is medium due to the poor performance in its energy production stage in 30 provinces during 2011-2020. Energy-related efficiency is greater in areas with a higher response to SDG7. (2) The impact of energy poverty on improving energy-related efficiency is significantly negative. Addressing energy poverty significantly improves energy-related efficiency in regions characterized by a high energy poverty index and low energy-related efficiency. However, it bears no impact in regions with a low energy poverty index and high energy-related efficiency. (3) The moderating effect of technological innovation effectively improves energy-related efficiency, whereas the marketization level has an inverse effect. Consequently, this paper suggests several policy implications.

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Under the goal of sustainable development, coping with the increase in social security and healthcare expenses caused by population aging is becoming increasingly important, but it is rare in the literature to evaluate the impact of social security efficiency on healthcare efficiency. This research uses the dynamic SBM two-stage model to observe the efficiencies of social security and healthcare in OECD countries. There are two findings as follows. First, the higher social security efficiency is, the better is the healthcare efficiency of countries with lower per capita GDP. Second, higher social security efficiency of National Health Service (NHS) countries denote better healthcare efficiency. When the financial source of the social security system is taxation, then it is more likely to bring higher efficiency to healthcare.

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China is the world's largest carbon emitter and also one of many countries most affected by extreme weather. Although its government has set carbon reduction targets, the public has not established a connection between carbon reduction and coping with extreme weather. This study aims to help establish the above connection and applies a dynamic two-stage undesirable non-radial directional distance function to evaluate energy performance in the first stage while establishing CO2 emissions as a link to evaluate coping with extreme weather performance in the second stage. From empirical results, the average efficiency of 30 provinces in China in coping with extreme weather from 2011 to 2020 is only 0.484, or far lower than the energy efficiency value of 0.709. Based on the differences in performance between the two stages and the changing trends in the room for improvement of CO2 emissions, this study proposes policy options to promote the participation of the entire society in the emission reduction process.

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With the inclusion of "Building Inclusive, safe, Resilient and Sustainable Cities and human Settlements" (SDG11) in the United Nations Sustainable Development Goals (SDGS), the movement to promote sustainable development from an urban perspective is growing globally. Many studies examine urban sustainability efficiency from multiple dimensions, but scant attention targets the interaction among various dimensions. This research combines the water-energy-industry subsystem to evaluate the sustainable development performance of 29 provinces in China from 2018 to 2020. The results show that 1) a water system plays an important role in promoting a city's overall sustainable performance. 2) Urban sustainable efficiency has the characteristics of low value aggregation and high value dispersion in space. 3) Regional and sub-system sustainability efficiencies exhibit clear heterogeneity. 4) Rainfall improves the sustainable efficiency of cities, mainly through water systems. 5) The coupling between water and industrial subsystems is better than that between energy and industrial subsystems, and the coupling between the central region subsystem is the best. This paper offers a new perspective for understanding the current state of sustainability in China's provinces and provides more specific suggestions for improving regional sustainability efficiency in the future.

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For decades, the construction industry has contributed significantly to China's economic growth. The heavy energy consumption inevitably leads to the release of large amounts of carbon emissions. Improving energy efficiency has been a crucial solution for mitigating the environmental impacts while boosting its green economy in the construction industry. Measuring the energy efficiency in the construction industry considering the quality of government sector is still limited. Using panel provincial data in China from 2011 to 2020, this paper proposes a two-stage dynamic data envelopment analysis (DEA) framework integrating the government sector with the production sector in the construction industry, and calculates energy efficiency. The spatial Durbin model is used to analyze the driving forces of energy efficiency. The research findings include (1) the energy efficiency in the eastern region is higher than that in the central and western regions. The mean values of energy efficiency in the eastern, central, and western regions are 0.42, 0.34, and 0.37. (2) Even though governance efficiency is lower than production efficiency, there is a positive correlation between governance efficiency and production efficiency with a correlation coefficient of 0.48. Improving governance efficiency is a significant step to increase the production efficiency and further increase energy efficiency of the construction industry. (3) Digital transformation has a positive effect on governance efficiency but has no effect on production efficiency. The government-production nexus framework provides implications for clarifying the role of government intervention in improving energy efficiency.

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Despite the great number of applications of bootstrapping data envelopment analysis (DEA) with a one-stage structure, there are limited attempts for approximating the distribution of the DEA estimator considering the two-stage structure across multiple periods. This research develops the dynamic two-stage non-radial DEA model based on smoothed bootstrap and subsampling bootstrap. Then, we run the proposed models on assessing the efficiency of China's industrial water use and health risk (IWUHR) systems and compare them with the bootstrapping results on standard radial network DEA. The results are as follows. (1) The proposed non-radial DEA model based on smoothed bootstrap can adjust original over-estimated and under-estimated values. (2) China's IWUHR system has good performance, and its HR stage performs better than the IWU stage for 30 provinces from 2011 to 2019. The poor performance of the IWU stage in Jiangxi and Gansu needs to be noticed. The provincial differences of the detailed bias-corrected efficiencies expand in the later period. (3) The rankings of IWU efficiency in the three regions are in agreement with that of HR efficiency: eastern, western, and central regions in this order. Particular attention should be paid to the downward trend of the bias-corrected IWUHR efficiency in the central region.

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The essence of efficiency measurement is to model and estimate the performance of a complex system in a comparable form, and the key to modeling is to make the model as close to reality as possible. Based on data envelopment analysis (DEA) methods, this research proposes a layer-by-layer investigation framework for the black box. To illustrate the rationality of this logical framework, this paper presents a triple-opened dynamic recycling model with a series-parallel structure that allows us to assess the efficiency of the industrial water-related system in China. We obtain and compare the system efficiency under different scenarios for opening the black box. The results show that: (1) China's efforts to improve the performance of the resource use sub-stage through industrial production technology and management have been effective. (2) The performance of China's industrial water-related system strongly relates to the water supply subunit with a positive linear correlation. (3) The water supply subunit is the main foot-dragger in the system, and the government needs to place particular attention on improving the performance of labor in this subunit.

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The circular economy has been incorporated into China's Five-Year Plan as an important policy tool for sustainable development with the aim of resolving the conflicts among economic growth, energy shortages, and environmental pollution. This research introduces industrial waste emission and recycling indicators into the window two-stage DDF recycle model, explores industrial circular economy efficiency in 30 provinces of China from 2011 to 2019 in the two stages of production and recycle, and focuses on efficiency improvement and stability during the 13th Five-Year Plan period. The results show the following. (1) During the study period, especially during the 13th Five-Year Plan, the circular economy efficiency in most provinces is positively improved, and its improvement is more significant in the central and western provinces. (2) Production stage efficiency is higher than recycle stage efficiency. Whether measured in the overall process, the production stage, or the recycle stage. In mean efficiency, the east is better than the central, and the west is the worst. (3) In terms of efficiency stability during the policy period, the central is the most stable, the east is the second most stable, and the west is the least stable. Shanghai and Tianjin present high efficiency and high stability; Zhejiang, Anhui, and Qinghai present high efficiency, but low stability; and Ningxia, Yunnan, and Xinjiang perform poorly in terms of efficiency values and stability. (4) Each province could adapt to its own situation, accelerate the adjustment of the industrial structure, optimize the energy consumption structure, and improve the overall resource utilization efficiency and recycling efficiency. The government could tilt the resource layout towards provinces with development difficulties, and meanwhile promote efficient development of recycling policies with dividends that address regional imbalances.

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Chinese coal enterprises are facing severe challenges due to low-carbon economy requirements and capacity reductions. This paper adopts a dynamic SBM model to compare the mining efficiency of each mining area of a coal company in China. We use total excavation footage, number of working platforms, and machine quantities as input indicators, and coal sales and CO2 emissions as output indicators. It was found that (1) both high efficiency and low efficiency mines maintained their production status each year and did not actively improve over time; (2) energy consumption was the primary indicator affecting comprehensive mining efficiency; and (3) while changes in the market environment did not have any significant impact on coal mining efficiency, coal mine characteristics were found to have some correlations with efficiency.

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With the influence of climate change resulting in more extreme days, a rise in the number of work-related injuries could be expected. The literature has addressed the performance evaluation of a work-related injury insurance (WII) system via a two-stage structure with input/output correlation as well as the impact of extreme temperatures under different scenarios. This article thus evaluates the performance of a system comprised of operational and service sub-systems under three scenarios of extreme temperatures and proposes a hybrid two-stage dynamic data envelopment analysis (DEA) model with nondiscretionary variables for measuring integrated WII efficiency under the three scenarios. The results are as follows: (1) the poor performance of the operational and service sub-systems leads to the integrated WII system's low efficiency for 30 provinces in China during 2010-2019, except for Zhejiang, Hainan, and Qinghai. (2) Extreme temperatures must be considered when measuring WII efficiency and its stage efficiencies, or otherwise WII efficiency and operational efficiency will be underestimated in 19 provinces. (3) The negative impacts of extreme temperatures on the efficiency of the integrated WII system should be taken notice of, especially for Sichuan.

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As the leading financial institutions in China, it is crucial for commercial banks to pay attention to environmental protection (E), social responsibility (S), and corporate governance (G) in order to enhance operational efficiency and to advance the high-quality development of the country's social economy. This research explores the market share of banks as exogenous variables in the profit stage and the market and sustainability stage to investigate the efficiency of 20 listed banks in China over 2016-2020 and innovatively incorporates indicators such as green credit, social giving, executive compensation, and ESG score into the meta-dynamic two-stage SBM under the exogenous variable DEA model. The results demonstrate the following. (1) By integrating market share as an exogenous variable in the model, the efficiency estimate is more precise. (2) In overall, UCBs are the most efficient type of banks, JSCBs are the second, SOCBs are the least efficient. All three types of banks are more efficient in profit stage versus the market and sustainability stage, JSCBs perform best in the profit stage, where SOCBs perform best in the market and sustainability stage. The three different bank types' TGR performance is comparable to their efficiency value performance. (3) SOCBs lead in ESG investment and have the best ESG performance due to their distinct state-owned background. With their ongoing dedication to profit maximization and disregard for social responsibility and sustainable development, JSCBs have the worst ESG performance. (4) Policy recommendations are made based on the study's findings for commercial banks, stakeholders, and regulators to support ESG investment and to bring about long-term sustainable development. Finally, as ESG develops in China, future research can consider longer time scales and larger perspectives to investigate the sustainability efficiency of commercial banks themselves, as well as their role in the local economy and industrial transformation.

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The purpose of this paper is to strengthen research concerning the impact of climate change on China's water resources, in order to avoid extreme weather events such as regional rainstorms and floods affecting the stable supply of energy and electricity. The goal is to reorganize energy industry allocation to make China's energy the most efficient, which would thus help achieve sustainable development goals. The biggest contribution and of this paper is not only to enlarge the scale and take into account the sustainable aspects, but also to consider climate change factors that have been ignored in the past as exogenous variables. For the first time, we take stock of the optimal allocation of new and tradition energy sources and carbon dioxide. This study uses the Dynamic ZSG-DDF model with exogenous variables and undesirable outputs to find a way to redistribute carbon dioxide, new energy, and tradition energy from different provinces on the premise of maximizing efficiency, thus achieving the goal of reducing carbon and saving the earth. The research results show that the energy efficiency of tradition energy is higher than that of new energy in various provinces. At the same time, the China government must comprehensively review the quota targets of new energy, tradition energy, and carbon dioxide (CO2) in each province as quickly as possible. Currently, the quotas of various provinces are seriously misplaced, and 26 provinces in total have great room for improvement.

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Countries are now struggling to improve their recycling efficiency of an industrial operational system to achieve the Sustainable Development Goals, yet scant studies have viewed the series-parallel recycling structure of the system based on data envelopment analysis (DEA). This research divides the system into industrial production and industrial waste treatment (IWT) processes connected serially, while the IWT process is further separated into treatment sub-units for wastewater, waste gas, and solid wastes connected in parallel. We propose a dynamic series-parallel recycling DEA model within a directional distance function to measure efficiency and discuss the efficiency relationship among the system, processes, and sub-units. By using the spatial Durbin model, we explore factors that mainly influence the efficiency for the 30 provinces during 2011-2019. The results show the following. (1) The medium performance of the industrial operational system with an average overall recycling efficiency of 0.69 is mainly caused by the poor performance of the IWT process with a score of 0.61. (2) The highest performance is observed in the wastewater treatment sub-unit, followed by waste gas treatment and solid waste treatment sub-units. (3) Market-based environmental regulations significantly promote local IWT efficiency, while command-and-control environmental regulations have no significant effect on local IWT efficiency. But they all have significant spatial spillovers. The voluntary environmental regulations have no significant impact.

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Numerous studies have divided industrial water use system into stages of industrial water use (IWU) and wastewater treatment (IWT) subsystems, named as the IWUWT system, yet scant studies have examined its dynamic recycling efficiency with non-discretionary variables. This paper proposes a dynamic two-stage recycling model with non-discretionary variables to compare and analyze the basin differences of the efficiency, and further reveal the driving forces of this efficiency in the Yangtze River basin and Yellow River basin. The results are as follows. (1) The average overall efficiency of the IWUWT system for the 30 provinces during 2011-2018 was 0.79 due to the bad performance of the IWT subsystem with an efficiency score of 0.74, especially for Yunnan and Guangxi. (2) The influence of economic policy uncertainty on circulating industrial water use is more significant in the south basin. (3) Economic development and water use intensity were the main drivers of IWUWT efficiency in the Yangtze River basin, while economic development and environmental consciousness were for the Yellow River basin. The results have important implications for Chinese government and different provinces to improve IWUWT efficiency by policy-making.

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This study employed dynamic three-stage network data envelopment analysis (DEA), considering parallel production in the agricultural and industrial sectors, to assess the impact of greenhouse gas emissions on the climate change and natural disaster stages. The results revealed the following: (1) The dynamic overall efficiencies of more countries are decreasing than are increasing. The seven countries with the poorest overall efficiency ranking (Myanmar, Vietnam, Thailand, Bangladesh, the Philippines, Pakistan, and India) are mostly located in Southeast Asia. (2) The number of countries that maintained low efficiency over the long term is greater than those that retained high efficiency over the long term. Myanmar, Mexico, India, the Philippines, Thailand, and Vietnam maintained efficiency scores below 0.5, whereas South Korea, Japan, China, and New Zealand maintained efficiency scores above 0.8. (3) More than one-third of countries exhibited declines in efficiency over time, and half were European countries. Less than one-third of countries maintained their efficiency, and less than one-third of countries gradually improved. (4) Approximately half of the countries' efficiency scores were lower than the global average. The efficiency scores of the industrial sector exhibited a greater room for improvement on the input factors than did those of the agricultural sector. (5) Total factor energy efficiency analysis revealed that methane emissions and CO2 emissions have a similar level but large room for improvement across countries. Improving input factors in the production stage can ultimately mitigate inefficiencies in the climate change and natural disaster stages. There are still other important factors related to climate change, such as sea surface temperature, forest areas, or air pollution indicators, that could be considered in future research. The occurrence of global disasters could also be discussed in groups according to the region where the countries are located in the future.

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This paper applies the modified undesirable dynamic data envelopment analysis (DEA) model by considering the role of forest carbon sinks to evaluate European countries' carbon dioxide (CO2) emissions and productivity efficiency. Taking population and energy consumption as input variables, gross domestic product (GDP) as the desirable input, CO2 as the undesirable output, and fixed assets as an inter-temporal carry-out input variable, our results suggest considering the fixed amount of the forest carbon sinks significantly affects efficiency rankings. The overall efficiency rankings for Ireland, Austria, Italy, Germany, Spain, and Belgium look to be overrated, while those of Finland, France, and Netherlands are apparently underrated. In terms of Total-Factor Efficiency analysis, countries with the best performance in efficiency ranking are Denmark, Luxembourg, Norway, Sweden, and the UK, thanks to their long-term effort at addressing the impact of forest carbon sinks and the effect of CO2 emissions on efficiency.

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BACKGROUND: Rapid economic growth in China has resulted in a commensurate increase in energy consumption, which in turn has seen an increase in environmental pollution problems. Past research has tended to focus on energy and environmental efficiency analyses and has rarely examined the media influence on environmental protection efforts. Further, most studies have used static models and ignored the dynamic changes over time. METHODS: To go some way to filling this research gap, this study developed a modified undesirable Dynamic DEA model that included air quality index (AQI) and CO2 indicators to explore the relationships between energy, the environment, and media report efficiencies in 31 Chinese cities from 2013 to 2016. RESULTS: It was found that: (1) Chongqing, Guangzhou, Nanjing and Shanghai had efficiencies of 1, but Lanzhou, Shijiazhuang, Taiyuan, Xining and Yinchuan needed significant improvements; (2) Chongqing, Guangzhou, Kunming, Nanning and Shanghai had relatively high media efficiencies, but the other cities had low efficiencies and required improvements; (3) the CO2 emissions efficiencies in most cities were better than the air quality index efficiencies; and 4. the media reports in most cities were found to have a more positive impact on the CO2 emissions efficiency than on the AQI efficiency. CONCLUSIONS: Environmental awareness enhances civilian health and promotes economic growth. Therefore, as the news media should be responsible for promoting environmental protection, they need to increase their environmental pollution coverage. It was found that the environmental pollution media report quality and especially air pollution reports needed improvements, and greater media coverage on environmental pollution and awareness was needed.

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Improving water use efficiency from a recycling perspective is claimed to be a better way to ensure prosperity in a water-stressed world. Although many studies have focused on the efficiency of integrated water use system, such as a water use and wastewater treatment (WUWT) system, few studies have observed the dynamic change involving a two-stage recycling structure. This research thus proposes a dynamic two-stage recycling model within the directional distance function (DDF) by taking reused water in the WT stage as a recycled product for WU stage's input in the next period. This paper reveals the dynamic evolution and spatial migration path of this efficiency in China. Results are as follows. (1) The average overall efficiency of the urban WUWT system for 30 provinces during 2011-2018 was 0.78. The central region's lower WUWT efficiency was caused by the expanding provincial differences in WU efficiency. (2) The urban WU sub-system performed poorer than that of the urban WT sub-system due to underutilizing reused water, such as in Jiangxi, Guangxi, Yunnan, and Jilin. (3) Narrowing the spatial imbalance of economic development and water use between the eastern and western regions is of great importance for promoting China's spatial imbalance of urban WUWT efficiency.

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In the past, energy and environmental research focused on the performance of individual efficiencies. In order to make up for the research deficiencies, this research uses SBM (slack-based measures) dynamic network DEA (DN-SBM) to assess energy, health efficiency, and DN-TFP productivity changes from 2011 to 2015. This research uses forest area as the carryover that can objectively measure the performance of OECD energy, health, and total efficiency, and calls for the importance of forest protection and planting. The empirical results show that Estonia, Finland, Hungary, Iceland, Mexico, New Zealand, Portugal, Slovenia, Sweden, and Turkey have the best overall efficiency performance, while Ireland (0.4469), Israel (0.4179), and the Netherlands (0.3697) are the three worst. In total, 29 economies show progress in terms of productivity. Moreover, Chile (0.9706), Mexico (0.9995), Slovak Republic (0.9942), Turkey (0.9815), and the UK (0.9886) exhibit a slight decline. The overall efficiency value of 20 countries is greater than the average, and their productivity is showing an upward trend. Only the UK (0.5081, 0.9886) has an overall efficiency value that is less than the overall average with productivity that is showing a drop. About research method, this study utilizes dynamic intertemporal data to evaluate the changes in the overall efficiency and productivity of OECD members with DN-SBM and DN-TFP indices in order to offer more objective research results for various economies that are useful for formulating policies related to energy, national health, and forest conservation.

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