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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. • A dynamic two-stage recycling model with non-discretionary variables is proposed. • Basin differences of the IWUWT efficiency and its stage efficiencies are provided. • Driving factors of the IWUWT efficiency in typical river basins are revealed. • The influences of EPU on IWUWT efficiency are highlighted. [ABSTRACT FROM AUTHOR]

China is developing wind energy and solar power as the main channels to deal with climate warming and has put forward the goal of achieving peak carbon emissions by 2030 and carbon neutralization by 2060. Previous studies evaluating the nation energy efficiency rarely consider the impact of wind and solar power. Thus, different from past literature, this research introduces Carbon Emission Reduction Capacity (CERC) by wind and solar power as a new output variable and applies a dynamic non-radial directional distance function to evaluate China's energy efficiency from 2011 to 2019. The empirical results show that northwest provinces with their high proportion of wind and solar power present better energy performance, while some eastern and central provinces with high efficiency as seen in previous study have greater room for improvement of wind and solar power. It is suggested that the China government formulate more flexible policies to support the sustainable development of wind and solar power, so as to reduce the consumption of fossil energy and cope with climate warming. • Applies a directional distance function to evaluate China's energy efficiency. • Northwest provinces with wind and solar energy present better energy performance. • Some eastern and central provinces have greater room for improvement of wind power. [ABSTRACT FROM AUTHOR]

With a total length of 35,000 kilometers, China has the world's largest high-speed rail network. Due to the deepening of China's "Internet +" strategy, new opportunities and challenges have emerged for China's railway system. While railway transportation industry efficiency has been widely discussed, most previous studies have focused on railway transportation industry operations and have generally ignored the important influence of internet technology on the industry. Therefore, to go some way to filling this gap, this study took the number of Chinese internet users as an investment indicator and integrated big data and the Internet of Things (IoT) concepts into a dynamic directional distance function-data envelopment analysis (DDF-DEA) model to comprehensively measure the impact of internet technology on railway transportation industry efficiency in 31 Chinese provinces from 2011 to 2016. It was found that (1) when the internet influence was considered, the overall railway transportation industry efficiency in most regions significantly improved, with Heilongjiang Province having the largest increase; (2) the labor input, passenger traffic, freight volume, railway turnover, and freight turnover input efficiencies in most provinces were significantly higher when the internet influence was considered; and (3) the internet has had a positive impact on railway transportation. [ABSTRACT FROM AUTHOR]

With the change of environment and the rapid development of economy, the problems of low effective utilization rate and uneven spatial distribution of agricultural irrigation water in the Yangtze River Economic Belt (YREB) are becoming increasingly prominent. This paper takes precipitation as an environmental exogenous variable into the measurement of water resource utilization efficiency. Data Envelopment Analysis (DEA) window model is applied to evaluate the agricultural water resource utilization efficiency（AWUE） of the YREB from 2010 to 2019 while Social Network Analysis (SNA) method is used to explore characteristics of the spatial network correlation. The conclusions are as follows: (1) In terms of AWUE, it showed a fluctuating development trend of first rising and then falling, rising with time under the change of precipitation during 2010–2019. However, it did not achieve the effectiveness of DEA in general, and AWUE still had the potential and room for improvement. (2) From the perspective of spatial network structure, the overall network density of spatial correlation of agricultural water resource utilization efficiency showed an evolutionary trend of first increasing then decreasing. The agricultural water resource utilization efficiency among provinces and cities had significant but relatively loose spatial correlation, but the spatial relationship was relatively loose. Based on the research results, this paper puts forward relevant policy suggestions from the aspects of promoting agricultural water-saving technology innovation, giving full play to the role of macro-control and market mechanism, and strengthening the connection among the upstream, middle and downstream regions of the YREB, so as to promote the improvement of AWUE and coordinated development of the YREB. [ABSTRACT FROM AUTHOR]

This study adopts the Modified Dynamic Three-stage Circular Data Envelopment Analysis (DEA) Model to explore food production, consumption, and waste recycling in 27 European countries from 2008 to 2016 and use food waste recycling as the circular link to the production stage as the circular economy. According to the empirical results, Germany and Malta have the best overall efficiency. In the three stages, the primary governance stage is the food waste recycle stage, and the second one is the food production stage. According to the Pearson's correlation coefficient test, the agriculture output, food waste, food waste recycling, CO 2 , and Methane are all highly correlated with extremely significant. The study is closer to the phenomena presented in the real world and the empirical results could be used to illustrate the corresponding strategies for national food security. [ABSTRACT FROM AUTHOR]

Reducing embodied energy inequality is the key to achieve sustainable development. However, research on the spatial-temporal impacts of embodied energy transfer within inter-provincial trade and regional energy inequality is insufficient. Taking the embodied energy inequality of China as the research object, this research establishes the environmentally extended multi-regional input-output model, traces the transfer path of embodied energy and value-added along the national supply chain, and calculates the embodied energy inequality using the regional environmental inequality index. The results show that the developed eastern coastal provinces mainly outsourced the consumption-based embodied energy to the developing regions, such as the northern provinces. Among them, S3 and S4 were the key sectors responsible for embodied energy consumption. Furthermore, when the developed regions traded with the developing regions, the value-added brought by their final demand was mainly retained locally. Some developing regions suffered double losses of embodied energy and value-added, leading to embodied energy inequality. From 2012 to 2017, China's inter-provincial trade witnessed a slight increase in the degree of embodied energy inequality. This study helps to understand the mismatch between domestic environmental burden and economic benefits from the perspective of inter-provincial trade, and provides a decision-making basis for realizing regional equity. • The embodied energy and value-added flows of China are tracked based on the EE-MRIO. • The embodied energy inequality is revealed from the perspective of economic-resource trade-off. • The temporal-spatial characteristics of the embodied energy inequality are explored. • The key sectors and regions of embodied energy inequality are investigated. [ABSTRACT FROM AUTHOR]

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. • A dynamic recycling DEA model within directional distance function is proposed. • The urban WUWT system from a recycling dynamic perspective is assessed in China. • Dynamic evolution and spatial migration path of efficiencies are further revealed. • Urban WU system performs poorer than WT system due to underutilizing reused water. • Spatial imbalance of efficiencies between the eastern and western regions is large. [ABSTRACT FROM AUTHOR]

This paper constructs a two-stage undesirable and desirable congestion model, which distinguishes purely technical inefficiency from congestion, to study the energy congestion of 30 transportation sectors in China from 2011 to 2020. The Heckman model is used to analyze the influence mechanism of various factors on the undesirable congestion of energy, which avoids sample selection bias. The results show that: (1) The undesirable congestion of energy mainly exists in the transport sector of the western region, while the desirable congestion of energy only exists in the transport sectors of the eastern and central regions. (2) Purely technical inefficiency in the transportation sector does not usually occur in isolation. (3) Population density and the proportion of clean freight turnover have a negative impact on the undesirable congestion of energy. • A two-stage undesirable and desirable congestion model is designed innovatively. • Energy efficiency in transport sector is assessed from the perspective of congestion. • The factors affecting the undesirable congestion in transport sectors are analyzed. • Rational allocation of energy in transport sector is realized based on congestion. [ABSTRACT FROM AUTHOR]

With its rapid economic development in the last 40 years, China's environmental pollution has begun to seriously affect its citizens' lives as well as domestic business expansion. The problems of water pollution, increasing population, acceleration of urbanization, and strong GDP growth have made this critical issue increasingly more prominent. Recent related literature has mostly focused on economic production development and water pollution separately without systematically considering the relevant links between the former and sewage treatment capacity. Therefore, based on data of 30 provinces in China from 2011 to 2017, this paper uses a modified undesirable dynamic network Slacks-Based Measure (SBM) model to look into each province's economic production stage efficiency and sewage treatment stage efficiency. The research findings show big differences in input and output efficiencies for each region from 2011 to 2017 and a distinct mismatch between economic production stage efficiency and sewage treatment stage efficiency, with the former higher and the latter lower. Lastly, sewage treatment stage efficiency is a major drag on overall efficiency. Each province should thus follow the key indicators to improve efficiency according to local conditions. • Explores China provinces' production stage and sewage treatment stage efficiencies. • Sewage treatment stage efficiency is a major drag on overall efficiency. • Each province should follow the key indicators to improve efficiency as per local conditions. [ABSTRACT FROM AUTHOR]

Although China is the largest energy consumer and carbon emitter in the world, it also has experienced the largest increase in green leaf area, as evidenced from 2007 to 2017 when it hit 66.156 million hectares, accounting for 6.891% of the country's total land area. This study considered carbon sequestration in afforestation and introduced it as an exogenous variable into a modified dynamic Slacks-Based Measure (SBM) model to find the change in China's energy and carbon emissions efficiency. Different from previous studies, China's western region had the best efficiency value of 0.718, while the eastern and central regions were 0.699 and 0.590. In some provinces with more restoration of trees, their efficiency value changed greatly, such as Yunnan, Qinghai, Inner Mongolia and Guizhou. The results highlighted that afforestation has become the most effective strategy for China to improve energy and carbon emissions efficiency and for dealing with climate change, which can be ensured through carbon tax and market mechanism policies. • By introducing exogenous variables based on traditional methods of energy and carbon emission research. • Afforestation in the central and western regions will be conducive to the improvement of China's overall energy. • Western China has the best performance, in which it is better in absorbing CO 2 by implementing afforestation. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the water-energy-food nexus (WEFN) system, focusing on its interlinked structure and dynamic characteristics. This paper proposes a dynamic series-loop data envelopment analysis (DEA) model with a directional distance function for measuring WEFN efficiency in China. A spatial Durbin model is constructed to investigate the impact of extreme temperatures on WEFN efficiency. The results are as follows. (1) Compared with the black-box DEA model and series network DEA model, a series-loop network DEA model can reflect the "networking effect" and "looping effect" in the WEFN system. (2) The WEFN system performs well with an average series-loop efficiency of 0.875, but the efficiency of the water subsystem scores low and needs improvement. (3) At the national level, extremely high and low temperatures have no significant effect on the WEFN efficiency in local or adjacent provinces, whereas average temperature promotes the WEFN efficiency in local provinces but hinders it in neighboring provinces. In the regions with a low temperature difference, average temperature has no impact on the WEFN efficiency of both the province itself and its neighboring provinces. Overall, this study provides valuable insights into the complex interlinkages within the WEFN system and highlights the importance of considering these relationships when improving the system efficiency. [ABSTRACT FROM AUTHOR]

Cities play a pivotal role in China's sustainable economic progress, serving as focal points for various developmental elements. This study offers a novel perspective, delving into two crucial dimensions of urban advancement: industrial infrastructure and economic growth. This research assesses the sustainable development efficiency of 36 cities within the Yangtze River Delta urban agglomeration (YRDUA) and the Pearl River Delta urban agglomeration (PRDUA), using specific indicators aligned with SDG9 and SDG8. To conduct this evaluation, the study employs the Meta-Frontier Window Network DDF Data Envelopment Analysis considering both the stability and enhancements in urban sustainable development efficiency over a five-year policy span. The key findings are as follows: 1) Urbanization emerges as a driver of sustainable development efficiency. However, while Shenzhen, Dongguan, and Zhuhai have attained optimal levels, their internal efficiency stability remains a concern; 2) During the 13th Five-Year Plan, Nantong, Changzhou, and Wuxi showcased significant performance improvements. In contrast, Jiangmen experienced a notable decline of 64.72%; 3) Focusing on subsystems, the Resilient Industrial and Infrastructure Subsystem displays superior efficiency compared to the Sustainable Economic Growth Subsystem. Yet, it's essential to note that neither subsystem has achieved optimal efficiency across most regions; 4) Geographically, the urban sustainable efficiency of YRDUA appears evenly distributed, with ample room for improvement in most cities. In contrast, PRDUA demonstrates an efficiency increase from its periphery to its core. Through this comprehensive exploration, the study provides valuable insights into the intricate relationship between urbanization, sustainable development efficiency, and regional disparities. • Developed comprehensive indicators tailored to China's situation referring to the SDG framework. • A novel model addressing the efficiency and internal stability of different periods is proposed. • Urbanization enhances the efficiency, yet the promotion of internal stability is unobvious. • Setting a five-year plan is an enduring and effective policy. [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]

China is the world's largest consumer of fossil energy and CO 2 emitter, as well as the country with the fastest growth of forest cover. While the China government regards forest carbon sequestration as one of the paths to achieve carbon neutrality, the existing research on energy efficiency measurement in China rarely takes it into account. Thus, this research introduces forest carbon sequestration as a new desirable output variable and applies a meta dynamic non-radial directional distance function to measure China's energy efficiency from 2010 to 2019, which effectively improves the accuracy of the assessment while providing dynamic comparison results. Different from previous studies, findings shows that, with the improvement of forest carbon sequestration, the technology gap ratio between the central and western regions and the eastern region has narrowed from 0.4 to 0.23 and 0.36 to 0.2 on average in 2015–2019. In addition, this study obtains the room for improvement of China's provinces in forest carbon sequestration and puts forward policy suggestions for its long-term sustainable development of forest carbon sequestration, including establishing responsibility objectives of annual minimum growth of forest carbon sequestration by provinces, accelerating the construction of forest carbon sequestration trading system, and developing urban green space carbon sequestration. • Applies a meta dynamic non-radial directional distance function to measure China's energy efficiency. • The central and western regions have narrowed their technology gap with the eastern region. • This research introduces forest carbon sequestration as a new desirable output variable. [ABSTRACT FROM AUTHOR]

The Yangtze River Economic Belt (YREB) is one of the most energy-consuming regions in China, accounting for 36% of the nation's total energy consumption in 2019. The fundamental purpose of productive activities in production sectors is to meet the increasing consumption demand of the household sector. The household sector plays an important role in promoting energy consumption. Taking the household energy consumption in the YREB as the research object, we establish a hybrid multi-regional input-output model and analyze the drivers of the household energy consumption by using the structural decomposition analysis method. The results show that the energy intensity is the main factor inhibiting energy consumption while the energy structure and the urban-rural consumption per capita are the main factors promoting the energy consumption. Furthermore, we use the structural path betweenness method to identify the critical transmission sectors and the key pathways. It can be found that energy sectors, manufacturing sectors and transportation sectors play important roles in energy transfer. Among them, energy from sector S1 mainly flows to sector S4, energy from sector S2 mainly flows to sector S3, while energy from sector S3 and sector S4 mainly flows to manufacturing sectors. The above results are expected to provide strong evidence for energy consumption reform in the YREB. • Highlight of research. • Drivers and key pathways of the household energy consumption are explored. • The energy intensity is the main factor inhibiting the household energy consumption. • The household energy consumption structure has improved, but it still needs to rise. • The energy sectors and the manufacturing sectors are critical transmission sectors. [ABSTRACT FROM AUTHOR]

Carbon emissions from industrial production affect agricultural production, and forests have the benefit of being carbon neutral. Therefore, this study adopts the dynamic network data envelopment analysis (DEA) model, takes carbon emissions as the link between industry and agriculture, and explores the production efficiency of industry and agriculture. It further incorporates forest area as a carry-over for evaluation and discusses 27 EU members' dynamic overall efficiency and productivity changes in 2014–2018. The empirical results are as follows. 1) The EU countries' industrial stage efficiency is better than their agriculture efficiency, with Germany, Luxembourg, Malta, and the Netherlands exhibiting the best efficiency performance. 2) The overall efficiencies of the Czech Republic, Portugal, and Croatia are the worst, because their misallocation of resources and excessive energy input cannot improve their output value. 3) The agricultural productivity of EU countries is better than that of industry productivity. 4) The EU has made great efforts at planting forests. 5) As energy consumption and carbon emissions are still rising, the EU still needs to do more to achieve the carbon reduction goals of the Paris Agreement and the Eu's 2030 zero carbon emissions. • A dynamic network model assesses industrial and agricultural efficiencies in the EU. • Forests in the EU have grown slightly over time. • It is difficult for high-income economies to cut and reduce carbon emissions. • The EU members still need to do more to achieve their carbon reduction goals. [ABSTRACT FROM AUTHOR]

Faced with water shortage, China has set a control target of 7000 × 108 m3 of water use in 2030. In the future, how to realize the 2030 water use peak target has become an urgent problem for China to solve. This study aims to predict total water use trend by 2030 under different scenarios and determine the magnitude and time of water use peak. This paper uses the LMDI (Logarithmic Mean Divisia Index) method to decompose the driving factors of the production water use and domestic water use in 2003–2017, and for the first time, combines the scenario analysis and Monte Carlo simulation to analysis the potential evolution trend of production and domestic water use. We found that: (1) Economic development is the primary factor in promoting the increase in total water use, domestic intensity and population scale play a role in promoting increase, production intensity is the primary factor in inhibiting the increase in total water use, industrial structure promotes the decrease of total water use; (2) There are significant differences in the decomposition effects among the three industries; (3) The evolution trend of production and domestic water use is different under the three scenarios. Compared with the baseline scenario, the primary and secondary industry water use decreased more, and the tertiary industry and domestic water use increased less, under the general water-saving scenario and the enhanced water-saving scenario; (4) During the period of 2003–2030, the total water use in all three scenarios experienced an inverted U-shaped. The peaks appeared in 2013, and the total water use (excluding ecological water consumption) was 6078.28 × 108 m3. The current total water use has reached its peak and been in a stage of stable or even declining stage. Some policy implications are put forward related to our empirical results. [ABSTRACT FROM AUTHOR]

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., (© 2024. The Author(s).)

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., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s).)

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., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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., (© 2023 Society for Risk Analysis.)

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., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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 (CO 2 ) 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., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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 (CO 2 ) emissions and productivity efficiency. Taking population and energy consumption as input variables, gross domestic product (GDP) as the desirable input, CO 2 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 CO 2 emissions on efficiency., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

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., (© 2021. The Author(s), under exclusive licence to Springer Nature B.V.)

With per capita water resources at only around a quarter of the world average, China's water resources are limited and unevenly distributed. Past research on water resource utilization has mainly focused on industrial water use (agriculture and industry), water plant ownership efficiencies (private or public operation), or water resources and economic production; however, there have been few studies focused on water supply livelihood. Therefore, this paper considered both industrial production water services, non-production water services (public sector and residential water use), and water leakage losses, which is a water supply problem seldom mentioned in other studies. An undesirable directional distance function (DDF) dynamic data envelopment analysis (DEA) model was employed for the dynamic analysis as it was able to deal with both desirable and undesirable outputs at the same time. The model examined collected water supply and water leak efficiency data from 30 Chinese provinces/municipalities from 2007 to 2018, from which it was found that (1) Beijing, Gansu, Guangdong, and Ningxia had efficient water supply and water leak losses from 2007 to 2018 and the most improved province was Jiangxi; (2) the eastern provinces, in general, had better water efficiencies and the central and western provinces needed greater improvements; and (3) the lowest water leakage loss efficiencies were in Inner Mongolia, Jiangxi, and Heilongjiang, all of which required significant improvements., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environment pollution was closely related to human health. The energy consumption is one of the important sources of environmental pollution in the development of economy. This paper used undesirable two-stage meta-frontier DDF (distance difference function) data envelopment analysis model to explore the impact of environment pollutants from energy consumption on the mortality of children and the aged, survival rate of 65 years old and health expenditure efficiency in 27 high income countries, 21 upper middle income countries, and 16 lower middle income countries from 2010 to 2014. High income countries had higher efficiency of energy and health than middle income countries in general. But whether in high income or middle income countries, the efficiency of non-renewable energy is higher than renewable energy. There was much room for both high income countries and middle income countries to improve renewable energy efficiency. Besides, middle income countries need to improve the efficiency of non-renewable energy and reduce pollutant emissions per unit of GDP. In terms of health efficiency, upper middle income countries performed worse than lower income countries. This phenomenon might indicate there was a U-shaped relationship between health efficiency and income level. Upper income countries should pay more attention to the environmental and health problems and cross the U-shaped turning point. The contribution of this article was to consider the heterogeneous performance of energy efficiency, environmental efficiency, and health efficiency under the influence of income level differences, and found that there might be a U-shaped relationship between health efficiency and income level.

China's pursuit of economic growth, rapid industrialization, and urbanization over the past few decades has resulted in high energy consumption, which in turn has caused serious environmental pollution problems, such as CO 2 and PM 2.5 emissions, the long-term exposure to which can seriously affect resident health. To resolve these air pollution problems, the Chinese government has put in place several policies to reduce air and environmental pollution. Past studies on energy and environmental efficiency have been mostly static, have ignored the dynamic changes over time and regional differences, and have rarely considered human health factors. Therefore, this study employed a modified meta 2-stage Epsilon-Based Measure (EBM) Malmquist model to explore the relationships between the economy, energy, the environment, health and media, and the regional differences in 31 Chinese cities from 2014 to 2016. It was found that (1) Haikou and Lhasa's efficiencies were 1 and were the best in all 3 years, and Shijiazhuang, Jinan and Shenyang's were the most improved; (2) there was a gap between the eastern, central and western technological frontiers, with Chengdu, Hohhot, Chongqing, and Nanchang having technological gap ratios below 0.70 in the western and central Chinese regions, and Haikou, Guangzhou, and Shanghai in eastern China having technological gap ratios above 0.90 in all 3 years; and (3) the variations in the health treatment stage were greater than in the production stage, indicating that technological changes and efficiency improvements in the health treatment stages in each city were not stable.

Improving the management efficiency of industrial accidents is significant for stabilizing social order and improving production efficiency. Although many previous studies have discussed the impact of work injury on different occupations from the work safety and health perspectives, few have jointly discussed economic, social, medical, and environmental pollution issues, and those that do mostly employ static models, failing to take into account welfare factors and environmental pollution issues that affect society. Therefore, in order to understand the dynamic evolution trend between social and economic activities and environmental issues, this study utilizes a modified undesirable two-stage dynamic exogenous data envelopment analysis (DEA) model to explore the economic, social, medical, and environmental efficiencies of 30 provinces in China to fill the gap in the literature. In terms of work injury insurance expenditure efficiency, the results show that the air quality index (AQI) impacts the ranking of China's 30 provincial regions, with Fujian, Ningxia, Qinghai, Shandong, Tianjin, and Xinjiang being greatly affected. AQI significantly influences overall factor efficiency, rescue invalid deaths, and the work-related injuries in the various regions. AQI also has a relatively small effect on the efficiency of work injury insurance benefits. Based on this, we offer suggestions for policy makers to evaluate the social benefits of environmental governance and the efficiency of human capital.