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The Beijing–Tianjin–Hebei region (BTH) is one of the crucial areas for economic development in China. However, rapid urban expansion and industrial development in this region have severely impacted the surrounding ecological environment. The air quality, water, and soil resources face significant pressure. Due to the close relationship between land utilization, population, investment, and industry, effective land use is a key factor in the coordinated development of the region. Therefore, clarifying the patterns of urban land use change and revealing its influencing factors can provide important scientific evidence for the coordinated development of the BTH region. This study aims to improve urban land use efficiency (ULUE) in the BTH region. Firstly, based on the input and output data of land elements for the 13 cities in the BTH region, the Data Envelopment Analysis (DEA) method is used to quantify the ULUE of the BTH urban agglomeration and analyze the spatiotemporal characteristics of ULUE. Input indicators includes capital, labor, and land. Output indicators includes economy, society, and environment. The results show that the overall ULUE in the BTH region has increased, albeit with notable fluctuations. Between 2000 and 2010, ULUE rose swiftly across all cities except Beijing and Tianjin, where changes were minimal. Post-2010, cities exhibited varied trends: steady growth, slow growth, sustained growth, step-wise growth, and initial growth followed by decline. Spatially, before 2010, the BTH showed a "high in the northeast and low in the southwest" pattern, transitioning post-2010 to a smoother "core-periphery" pattern. Mid-epidemic, high ULUE values reverted to the core area, shifting southward post-epidemic. Secondly, panel data analysis is conducted to explore the factors influencing ULUE. The results indicate that fiscal balance, the level of openness, the level of digitalization, industrial structure, and the level of green development are significant factors affecting ULUE. Finally, strategies are proposed to improve ULUE in the BTH region, including national spatial planning, industrial layout, existing land use, infrastructure construction, optimization of local fiscal revenue, and improvement in the business environment, aiming to enhance ULUE and promote the coordinated development of industries in the BTH region. [ABSTRACT FROM AUTHOR]

This research dynamically evaluates the innovation efficiency of China's high-tech industry and explores the efficiency differences in basic innovation, application innovation, and income innovation of this industry for different regions. Based on panel data of 30 provinces from 2015 to 2019, we construct a three-stage dynamic DDF (Directional Distance Function) model, divide the high-tech industry into three stages and measure the efficiency of the three stages. From 2015 to 2019, most of the total efficiency of China's high-tech industries showed an upward trend, with the western region having the highest total efficiency value and the central region the lowest. Most of the 30 provinces present basic innovation efficiency < applied innovation efficiency < profitable innovation efficiency. The conclusions from the article's empirical analysis can help developing countries concerned find out key links to improve the efficiency of high-tech entrepreneurship and innovation and then formulate relevant industrial policies. [ABSTRACT FROM AUTHOR]

Inland ports have become elements of the modern transport and logistics infrastructure hub and play an important role in shaping urban spatial texture. However, the spatial dimensions of their development have received little attention in the existing literature. This paper explores the spatial value concept for inland ports, i.e., the node and place values, by using a node-place model that was adopted for passenger terminals such as metro stations or train terminals. After measuring the node and place values, our research further evaluates the efficiency of node value's impact in improving place value, which indicates the effects of node value on regional development. This paper examines the impact of inland port activities on regional development, studying 12 Chinese inland ports with various models. The results show that half of the inland ports are balanced in terms of node value and place value. Only 50% of the inland ports are efficient, in terms of the contribution of node value to place value, in promoting the regional economy. Inland ports in a balanced position are usually more efficient. This study provides new evidence of inland ports promoting regional development, as well as a basis for policy-making for future inland ports. [ABSTRACT FROM AUTHOR]

China is a country highly vulnerable to natural disasters, resulting in significant losses in terms of human casualties, injuries, property damage, economic losses, infrastructure destruction, and so on each year. We propose a conceptual model based on the Data Envelopment Analysis model to evaluate regional vulnerability in mainland China using the annual data of Chinese official statistics from 2006 to 2021. The proposed model includes five input variables: regional total population, per capita GDP, population density, GDP per square kilometer, and regional total fixed investment in water conservancy, environment, and public facilities management. Additionally, it incorporates two output variables: affected people and direct economic loss. The results indicate that the vulnerability level generally decreases from West China through Central China to East China. Based on the new classification method proposed in this study, the regions are divided into five areas. These findings can serve as a reference for policymakers in enhancing disaster planning and improving the efficiency of natural disaster prevention. [ABSTRACT FROM AUTHOR]

An important research direction in the field of traffic light recognition of autonomous systems is to accurately obtain the region of interest (ROI) of the image through the multi-sensor assisted method. Dynamic evaluation of the performance of the multi-sensor (GNSS, IMU, and odometer) fusion positioning system to obtain the optimum size of the ROI is essential for further improvement of recognition accuracy. In this paper, we propose a dynamic estimation adjustment (DEA) model construction method to optimize the ROI. First, according to the residual variance of the integrated navigation system and the vehicle velocity, we divide the innovation into an approximate Gaussian fitting region (AGFR) and a Gaussian convergence region (GCR) and estimate them using variational Bayesian gated recurrent unit (VBGRU) networks and a Gaussian mixture model (GMM), respectively, to obtain the GNSS measurement uncertainty. Then, the relationship between the GNSS measurement uncertainty and the multi-sensor aided ROI acquisition error is deduced and analyzed in detail. Further, we build a dynamic estimation adjustment model to convert the innovation of the multi-sensor integrated navigation system into the optimal ROI size of the traffic lights online. Finally, we use the YOLOv4 model to detect and recognize the traffic lights in the ROI. Based on laboratory simulation and real road tests, we verify the performance of the DEA model. The experimental results show that the proposed algorithm is more suitable for the application of autonomous vehicles in complex urban road scenarios than the existing achievements. [ABSTRACT FROM AUTHOR]

Ensuring sustainable levels of rice yield has become a significant concern in recent years. To improve yields in rice production, it is essential to increase factor inputs and productivity. However, current research primarily focuses on general grain productivity, rather than rice. In this study, utilize the DEA-Malmquist index to present a comprehensive temporal and spatial analysis of rice productivity and its determinants in China. Our findings reveal that the overall efficiency of rice production in China exhibits a fluctuating upward trend, with technological progress being the primary driver of improvement in production efficiency. Moreover, rice production efficiency demonstrates a distribution pattern that decreases from east to west, with resource endowment, production conditions, socioeconomic development levels, and the political system being crucial factors influencing efficiency. This study proposes novel ideas for structural adjustments and regional divisions within China's rice industry and provides a theoretical foundation for governments to develop evidence-based policies. [ABSTRACT FROM AUTHOR]

The industrial sector, the backbone of China's economic development, is a key field that requires environmental management. The purpose of this study is to propose an improved data envelopment analysis (DEA) model to analyze the performance of provincial industrial systems (ISs) from 2011 to 2020 in China. To comprehensively characterize the operational framework of ISs, this study proposes an improved meta-frontier network DEA model. Unlike the existing models, the one proposed in this study not only considers the technical heterogeneity of ISs, but also reflects the interaction between IS subsystems. The empirical analysis yields valuable research findings. First, the overall environmental performance of Chinese ISs is generally low, with an average performance of 0.50, showing a U-shaped trend during the study period. Furthermore, significant regional differences are observed in the environmental performance of Chinese ISs. Second, the average performance of the production subsystem is 0.75, while the average performance of the pollution control subsystem (PTS) is 0.44. The low performance of the PTS pulls down the overall performance of Chinese ISs. Third, the technological level of Chinese ISs is low, with about 50% improvement potential. Finally, targeted suggestions to promote the green development of ISs are proposed on the basis of the empirical results. [ABSTRACT FROM AUTHOR]

The dual-carbon target brings severe challenges to enterprise financing. Low-carbon supply chain financing has become a key measure by which enterprises break through the financing bottleneck. How to accurately evaluate and optimize the financial efficiency of a low-carbon supply chain is of great significance. We developed a financial behavior scale of the low-carbon supply chain for enterprises and constructed the evaluation index system for financing efficiency of enterprises' low-carbon supply chain. Based on the qualitative and quantitative data of 205 listed companies, we combine the PCA model with the DEA–Malmquist model to conduct static and dynamic analysis of the financing efficiency of enterprises' low-carbon supply chain. The results show that the financing efficiency of the culture, sports, and entertainment industries needs to be improved. The pure technical efficiency of information transmission, software, and information technology services is low. The total factor productivity index of water conservancy, environment and public facilities management, and the real estate industry fluctuated significantly. In this regard, enterprises must combine the characteristics of the industry and improve the financing efficiency of the supply chain using low-carbon processes of improvement, selection of low-carbon environmental protection materials, and collaborative supply chain emission reduction to break the financing constraints of enterprises and promote the realization of the national dual-carbon target. [ABSTRACT FROM AUTHOR]

The development of rural finance has an important impact on agricultural development. This study is to quantitatively evaluate the efficiency of rural agriculture financial support in China and empirically analyze its influencing factors. Based on the panel data of 30 provinces in China from 2014 to 2018, this study uses the DEA model to quantitatively evaluate the efficiency of rural agriculture financial support and uses the panel Tobit model to form an empirical analysis of its influencing factors. The results show that: (1) The efficiency of rural agriculture financial support in the eastern region is significantly higher than that in the central and western regions; (2) The efficiency of rural agriculture financial support in Beijing, Zhejiang, and Guangdong are on the production frontier over the years, while other provinces have a large space to improve efficiency; (3) The strength of rural financial support as well as the level of regional economic development has a significant positive impact on the efficiency of rural agriculture financial support, while the intensity of rural financial services, as well as the scale of agricultural production and operation, has a significant negative impact. Finally, this study puts forward policy recommendations on rural financial support for the development of "agriculture, rural areas and farmers". [ABSTRACT FROM AUTHOR]

The "Belt and Road" initiative proposed by China has received much attention from the international community. Natural disasters along the route have posed considerable challenges to the "Belt and Road" economic construction. Southeast Asia, as the main thoroughfare of the Maritime Silk Road, always suffers from floods. It is necessary to evaluate flood risk to enhance disaster emergency management. Based on the Data Envelopment Analysis (DEA) model, inputs consist of four factors: the number of deaths, victims, frequency of occurrence, and economic losses caused by meteorological disasters. To study the vulnerability to flood disasters in Southeast Asian countries, the four factors caused by flood disasters were taken as outputs, respectively. The relative efficiency values of Laos, Malaysia and Cambodia exceed 0.8. They are most vulnerable to floods. The following four countries, Thailand, Myanmar, Indonesia, and the Philippines, are also vulnerable to flood disasters. The vulnerability of Vietnam is relatively lower than the others. In brief, the risk of flood disasters in Southeast Asia is high. Risk assessment for Southeast Asia is essential to ensure the implementation of the "Belt and Road" initiative. [ABSTRACT FROM AUTHOR]

Against the background of sustainable development, landfill covers can consist of a range of materials, from clay to geocomposite and polymer composites. Given engineering and environmental requirements, we analyzed the performance and sustainability of four sanitary landfill cover materials, namely clay, HDPE, PVC, and GCL. Within the principles of environmentally sustainable design, we constructed a material selection index based on the performance as well as the economic and environmental impacts of the materials. In addition, using a data envelopment analysis (DEA) model with an analytic hierarchical process (AHP) preference cone, we developed a C2WH model to evaluate the performance of the selected materials. Through the calculation, we found that the comprehensive indexes of the four covering materials were E1 = 0.2600, E2 = 0.5757, E3 = 0.7815, and E4 = 1.0000, respectively. Our results indicated that the investigated materials could be ranked according to performance as follows: GCL > PVC > HDPE > clay. Thus, our results showed that GCL, with the highest efficiency value, was the optimal cover of the investigated materials. The multiobjective decision model developed in our study can be used as a technical reference and offers support for the selection of eco-friendly landfill cover materials. [ABSTRACT FROM AUTHOR]

Appropriate channel strategies can help to improve the operational efficiency of retail firms and stimulate the domestic demand market. To study the sustainability of retail enterprises in the COVID-19 era, this paper uses the data of 29 Chinese listed retail enterprises from 2012 to 2021 as a sample, and uses data envelopment analysis (DEA) to evaluate and analyze the efficiency of the listed retail enterprises that implement different channel strategies. The results of the study show that: (1) The implementation of channel strategy will re-integrate the information flow, capital flow, commercial flow and logistics of enterprises, and affect the efficiency of enterprises through four paths: market demand, channel resources, channel technology and channel system. (2) The implementation of dual-channel strategy enterprises, in the short term, has greater technical efficiency than single-channel strategy enterprises. (3) The channel integration strategy of online ordering and store delivery has a significant positive impact on the overall efficiency of listed retail enterprises. (4) The inventory turnover rate has a significant positive impact on the overall efficiency of the listed retail enterprises. The level of accounts receivable, the level of retail technology, the level of investment in fixed assets and the size of enterprises have a negative impact on the overall efficiency of the listed retail enterprises. [ABSTRACT FROM AUTHOR]

As an important indicator for measuring the development level of low-carbon tourism, reducing the carbon emissions of tourism transportation has become an essential strategic goal and task for the sustainable development of tourism. Among many tourism vehicles, high-speed rails have a significant role in reducing the carbon emissions of tourism transportation. To clarify the impact of high-speed rails on the development efficiency of low-carbon tourism, using the relevant data of Zhengzhou urban agglomeration from 2010 to 2020, the DEA-BCC model and the Malmquist index method were used to measure these data. The results show the following: (1) the average comprehensive development efficiency of the Zhengzhou metropolitan high-speed rail for low-carbon tourism is low, and the comprehensive development efficiency of each city varies greatly; (2) the impact of high-speed rails on the development efficiency of low-carbon tourism in some underdeveloped areas is increasing. The impact on the development efficiency of low-carbon tourism in more developed areas is declining; (3) affected by COVID-19, tourism carbon emissions have shown a downward trend, reflecting the importance of low-carbon travel to low-carbon tourism to a certain extent. The research results not only verify the existing research conclusions but also verify the role of high-speed rails in the development of low-carbon tourism, and have practical value with respect to targeted guidance for the development of low-carbon tourism. [ABSTRACT FROM AUTHOR]

Difficulty in financing and low financing efficiency is one of the bottlenecks that restrict the high-quality development of China's energy-saving and environmental protection industry and economy. The key to improving financing efficiency is to understand its influencing factors. This paper uses data envelopment analysis (DEA) and the Malmquist index to measure the overall financing efficiency and the efficiency of different financing methods of 205 Chinese energy-saving and environmental protection industries from 2015 to 2020 from static and dynamic perspectives, respectively, as well as the Tobit model to estimate the impact of factors such as the digital transformation and green technological innovation of enterprises on financing efficiency. The study shows the following: (1) Static analysis shows that: the financing efficiency of the comprehensive technical efficiency of China's energy conservation and environmental protection industry is less than one, 5.8% to 23.41% of enterprises have very effective comprehensive technical financing efficiency, and fewer than 9% enterprises have very effective scale efficiency levels. Enterprises may have more room for improving their financing efficiency in the future. The four types of financing are, namely, internal financing, equity financing, fiscal financing, and debt financing, in descending order of efficiency. (2) Dynamic analysis shows that the financing efficiencies of debt financing and fiscal financing are both on an upward trend, while internal and equity financing efficiencies are on a downward trend. Additionally, the technological progress change index and scale efficiency are two key factors affecting the financing efficiency of different financing methods. (3) In terms of financing methods, the comprehensive technical efficiency and scale efficiency of endogenous financing and equity financing are high, while the comprehensive technical efficiency and scale efficiency of debt financing and fiscal financing are low and flat. (4) Digital transformation, green technology innovation, the asset–liability ratio, profitability, and operational capability have a significant positive impact on the financing efficiency of energy-saving and environmental protection enterprises. This paper studies the financing efficiency of China's energy conservation and environmental protection industry under different financing methods and the mechanism through which key factors affect the financing efficiency of enterprises. It aims to provide a theoretical basis for managing financing methods scientifically and rationally and improving the financing efficiency of the energy conservation and environmental protection industry, as well as to provide practical reference for the implementation of digital transformation, green technology innovation and diversified financing in China and other developing economies. [ABSTRACT FROM AUTHOR]

In the study of the water–energy–food nexus (WEF nexus), the importance of the intensity and quantity index system has been widely recognized. In order to study the impact of WEF on the economy, this paper establishes an intensity index system and a quantity index system, taking account of the impact of environmental pollution. Using a DEA model and China's provincial data from 2019, this paper calculated the efficiency of the WEF nexus with the developed intensity and quantity index systems. The results show that the efficiency is not high in areas with a high economic development level, and efficiency is not the lowest in areas with a relatively low economic development level. When considering environmental pollution, the efficiency of some provinces has increased significantly, indicating that the WEF nexus has not caused environmental damage and is conducive to sustainable economic development. In the two intensity index systems, the efficiency of the production system is significantly lower than that of the consumption system, indicating that there is a serious waste of cultivated land per capita. Compared with the intensity index system, the efficiency of the quantity index system is low, and the polarization is obvious. A high level of GDP does not mean a high level of economic development. There may be a low level of resource utilization technology or environmental pollution underlying it. It is unscientific to evaluate local economic development only by GDP. When evaluating the urban economy and national economy, we should conduct an overall study of WEF and reasonably allocate WEF resources, which will not only help to alleviate the current situation of resource shortage in various countries but also effectively promote the coordinated development of national and regional economies. At the same time, environmental protection should also be taken into account. Compared with the economic development model of developing the economy first and then solving environmental problems, developing and solving at the same time is more conducive to the sustainable development of the national economy. [ABSTRACT FROM AUTHOR]

As an important part of low-carbon ecological city construction, green building is also an objective requirement of sustainable development. Based on the green building panel data of 30 provincial administrative regions in China from 2010 to 2020, the super-efficiency SBM model combined with the three-stage DEA model was adopted to obtain the green building efficiency value that was closer to the real situation by excluding the influence of environmental factors and statistical noise. Green buildings in China have only been developing for just over ten years and are still in the initial stage of spatial aggregation in which transportation infrastructure plays an important role in scale effect. This manuscript focuses on analyzing the influence factors, intensity and direction of transportation infrastructure on green building efficiency. The results show that: (1) The agglomeration effect is obvious in the area of green buildings with high efficiency, but the radiation effect is not strong in low-efficiency area. (2) Municipal transportation infrastructure investment, road surface area, per capita number of stations and interregional traffic network density have a positive impact on green building efficiency, while freight volume has a negative impact. [ABSTRACT FROM AUTHOR]

Improving the efficiency of family farms is of great significance to rural revitalization and agricultural modernization in China. In order to find out the development status and shortcomings of family farms in China, and put forward targeted policy recommendations to improve the efficiency of various family farms, this paper applies the DEA model to measure the efficiency of family farms from a micro perspective by using the field survey data of the national family farm demonstration bases of Wuhan and Langxi, China. In addition, the Tobit model is further applied to explore the factors that affect the efficiency of full sample family farms, as well as to compare and analyze the differences in the efficiency in different regions and of different operation types. The results show that the efficiency of family farms is low, the efficiency of family farms in Wuhan is higher than that in Langxi, and the efficiency of breeding family farms is higher than that of planting family farms and mixed family farms. Capital input, farmers' education level, market channels, brand registration, fertilizer usage and financial credit have positively affected the efficiency of family farms, while government subsidies and natural disasters have had negative effects on it. Specially, the land operating area shows a U-shaped relationship with farm efficiency. The efficiency of planting family farms is positively affected by labor input, while that of breeding and mixed family farms rely more on capital input and financial credit instead. [ABSTRACT FROM AUTHOR]

Energy efficiency improvement is essential for China's sustainable development of its social economy. Based on the provincial panel data of China's three economic regions from 1990 to 2013, this research uses the data envelopment analysis (DEA) model to measure the total-factor energy efficiency, and the Tobit regression model to explore the driving factors of efficiency changes. Empirical results show: (1) Energy efficiency, energy consumption structure, and government fiscal scale are significantly positively correlated. (2) Industrial structure and per capita income level have negative correlation to energy efficiency; the impact of industrial structure on energy efficiency is relatively small. (3) The increase of carbon dioxide emissions will decrease the energy efficiency. Furthermore, with people becoming less conscious of energy conservation and emission reduction, energy efficiency will also decrease. (4) Specific energy policies will improve energy efficiency, and greater openness in coastal areas will also have the similar effect. [ABSTRACT FROM AUTHOR]

Currently, economic development has become a dominant factor in the promotion of urban regeneration in China. This means that decision makers often overlook the impacts on the natural environment when planning urban regeneration within a region. To properly face such challenges and others that may arise, a strategy relying on Nature-Based Solutions (NBS) can enhance the physical and ecological environment of a city, while ensuring greater resilience to natural disasters, and the use of fewer resources. NBS also improves the social well-being of citizens by creating more inclusive and engaged communities. This paper reviews the literature concerning urban regeneration and natural disaster vulnerability to discuss the complex mechanisms of the interactions between natural disaster and urban regeneration. Then, the evaluation model of natural disaster vulnerability in urban area is constructed, and data envelopment analysis (DEA) model is used to assess the vulnerability of natural disasters in various regions of Chongqing. Finally, under the background of NBS, this paper puts forward the way of urban regeneration, and provides an important direction for urban regeneration to realize the sustainable development of cities. [ABSTRACT FROM AUTHOR]

Because overall energy consumption intensity in China's manufacturing industry is extremely high, the study of energy efficiency in that industry, with an analysis of the policy impacts of energy intensity reduction and other key factors, will no doubt improve energy utilization in the industry and stimulate sustainable development within it. This paper uses 2004-2014 panel data of 28 manufacturing industries and a piecewise linear utility function to construct a data envelopment analysis (DEA) model of energy consumption with environmental regulations constraints. We also examine the DEA evaluation of energy efficiency in manufacturing industries. We integrate environmental regulations as qualitative variables into the energy consumption evaluation model to research the coupling effects on energy consumption intensity of energy consumption structure, opening up, environmental regulations, technological progress, and competition within industries. The research shows that energy efficiency policy intensity is not the major effect on the development of low or moderate energy-consumption industries, whereas low-energy-efficiency policy is very favorable for the development of high energy-consumption industries [ABSTRACT FROM AUTHOR]

An explanation and quantification of the water-energy-food nexus (WEF-Nexus) is important to advance our understanding of regional resource management, which is presently in its infant stage. Evaluation of the current states, interconnections, and trends of WEF-Nexus, in cities, has largely been ignored due to quantification hurdles and the lack of available data. Based on the interaction of WEF-Nexus with population system, economic system, and environmental system, this paper builds the input output index system at the city level. Using the input output index system, we evaluate the WEF-Nexus input-output efficiency with the data envelopment analysis (DEA) model. We regard the decision making unit as a “black box”, to explore the states and trends of WEF-Nexus. In the empirical study based on data from China, we compare the input-output efficiency of WEF-Nexus in 30 provinces across China, from 2005 to 2014, to better understand their statues and trends of the input-output efficiency holistically. Together with the Malmquist index, factors leading to regional differences in the fluctuation of input-output efficiency are explored. Finally, we conclude that the DEA model indicates the regional consumption of WEF resources in the horizontal dimension and the trends in vertical dimension, together with the Malmquist index, to explain the variations for proposing specific implications. [ABSTRACT FROM AUTHOR]

The differentiation rule and driving mechanisms of collapse disasters in various regions are unclear, and the results from existing methods of research are not sufficiently scientific. To reveal the nature of collapse disasters, this study utilized data from the 1:50,000 geological disaster investigation results database, 1:50,000 topographic data, and TM images. Topography, human activity intensity, rock mass structure, hydrological conditions, vegetation status, and meteorological conditions were used as indicators in the DEA model to analyze their validity and to explore the differentiation law and driving mechanisms of the highway slope along the YaLu river, a location of frequent geological disasters in Changbai County. In the analysis process, each index was quantitatively graded, i.e., the number of disaster points corresponding to each index was used as an input index, and the number of disaster points and the scale and stability of disaster points corresponding to the graded quantitative index were used as the output indexes. The results of the analysis of the study area indicate that there are significant differences in geological disasters due to different regional characteristics. We carried out three evaluations and performed spatial superposition analysis of the indicators corresponding to the effective values and the regional collapse points. The driving factors of collapse disasters can be divided into three categories, namely the impact of human activities, rainfall, and gravity stress. The GIS analysis and mapping found that the collapse points located to the south of the Grand Canyon of Changbai County were primarily affected by rainfall. Additionally, the areas affected by activity intensity are mostly concentrated in county towns with concentrated populations and road slopes. [ABSTRACT FROM AUTHOR]

As a labor-intensive industry with a strong industrial driving force and high-technology integration, green buildings offer some comparative advantages. Driven by the concept of green development, green buildings are ushering in a period of opportunity for integrated development among multiple fields. Therefore, this research will select the panel data of the financial industry and the green buildings industry in 2014 and 2018, respectively, in 31 provinces in China (excluding Hong Kong, Macao and Taiwan) and, through the method of factor analysis, will innovatively construct a financial industry development index and a green building Development Index for each province in China. Through the coupling coordination model, it studies the development level of the financial industry and green buildings in various provinces, in order to deeply explore the path and mechanism of coordinated development between the two. The results show that the financial industry and green buildings in the eastern coastal areas have a high level of coupling, and the coupling and coordinated development have a greater degree of correlation. The potential for coupling and coordination in Central China is developing for the better, while volatility in the Northeast and Northwest regions is relatively large. From the time dimension angle, the degree of coupling and coordination between green buildings and the financial industry in China is generally low, and in the transitional stage, from the brink of unbalanced development to a primary stage of coordinated development. Accordingly, this paper proposes that local government should pay attention to the coordination relationship between green buildings and financial industry development and formulate a coordination mechanism between their growth according to local conditions, so as to promote the correct interactive advancement of the two.

Existing studies of financing efficiency concentrate on capital structure and a single external environment or internal management characteristic. Few of the studies include the internal and external financing environments at the same time for hydrogen energy industry financing efficiency. This paper used the data envelopment analysis (DEA) model and the Malmquist index to measure the financing efficiency of 70 hydrogen energy listed enterprises in China from 2014 to 2020 from both static and dynamic perspectives. Then, a tobit model was constructed to explore the influence of external environment and internal factors on the financing efficiency. The contributions of this paper are studying the internal and external financing environments, and integrating financing cost efficiency and capital allocation efficiency into the financing efficiency of hydrogen energy enterprises. The results show that, firstly, the financing efficiency of China's hydrogen energy listed enterprises showed an upward trend during the years 2014–2020. Secondly, China's hydrogen energy enterprises mainly gather in the eastern coastal areas, and their financing efficiency is more than that in western areas. Thirdly, the regional economic development level, enterprise scale, financing structure, capital utilization efficiency and profitability have significant effects on the financing efficiency. These results can promote the achievement of "carbon neutrality" in China. [ABSTRACT FROM AUTHOR]

There is a close relationship between tourism efficiency and transport accessibility, but there is little research on the topic. This paper takes 17 administrative units in Hubei Province as the research object, evaluates their tourism efficiency from 2011 to 2017 and transportation accessibility in 2011 and 2017, and explores the temporal and spatial correlation between the two. The results showed that, from 2011 to 2017, tourism efficiency of Hubei province was high and steadily improving, space non-equilibrium gradually decreased, and differences shrank. In 2011 and 2017, the province had a good tourism transport accessibility, and the spatial distribution pattern was high in the east and low in the west. At the same time, tourism transport continued to improve, and spatial imbalance declined. In 2011 and 2017, the coupling and coordination of tourism efficiency and its decomposition efficiency and transport accessibility in Hubei Province were both good, indicative of the development of a tourism economy and the improvement of tourism transport facilities in all regions of the province. There is also a poor spatial matching of tourism efficiency and its decomposition efficiency with transport accessibility during the study period. This study suggested that the tourism efficiency and transport accessibility increased in Hubie province, but the coupling and spatial match remain not very good. Therefore, each region should improve the spatial match and coupling degree of tourism efficiency and transport accessibility, and enhance the sustainability of tourism development. [ABSTRACT FROM AUTHOR]

The Yangtze River Economic Belt (YREB) is a major national strategic development area in China, and the development of the YREB will greatly promote the development of the entirety China, so research on its agricultural production efficiency is also of great significance. This paper is committed to studying the agricultural production efficiency of 11 provinces in the YREB and adopts a combination of the Data Envelopment Analysis (DEA) model and the Malmquist index to make a dynamic and static analysis on the YREB's agricultural production efficiency from 2010 to 2019. Then, a three-stage DEA Malmquist model that eliminates the factors of random interference and management inefficiency is compared to a model without elimination. The results show that the adjusted technological efficiency changes, technological progress, and total factor productivity increased by -0.1%, 0.24%, and 0.22%, respectively. When comparing these values to the pre-adjustment values, the results indicate that the effect of environmental variables cannot be ignored when studying the agricultural production efficiency of the YREB. At the same time, the differences in the agricultural production efficiency in the YREB are reasonably explained, and feasible suggestions are put forward.

The new energy industry (NEI) is key to achieving a clean and low-carbon economy. Improving its technical efficiency, a factor reflecting the ability of an enterprise or industry to produce maximum economic outputs from a given set of inputs and production technologies, is vital for the healthy development of the NEI. Nevertheless, due to the fragmentation of industry data, it is still difficult to accurately measure the technical efficiency of China's NEI and understand the driving factors behind it. Based on the panel data derived from 17,457 observations on new energy enterprises in 29 Chinese provinces during 1998 and 2013 (latest data available), this paper uses data envelopment analysis (DEA) and geographically and temporally weighted regression (GTWR) for the first time to investigate the spatiotemporal characteristics and driving factors of the technical efficiency of China's NEI. The results show that the technical efficiency of China's NEI was relatively low and increased modestly from 0.44 in 1998 to 0.52 in 2013. Exploring the reasons from the perspective of spatiotemporal heterogeneity, we find that enterprise scale and technological progress are the major driving factors for increasing NEI's technical efficiency. However, the role of economic development in improving efficiency has gradually disappeared. Moreover, the negative effect of state-owned enterprises on efficiency becomes increasingly obvious. The effect of new energy resources is negligible. Our main contribution is the technical efficiency of China's NEI which is measured at the provincial level and its main driving factors are explored by considering spatiotemporal heterogeneity. Accordingly, we put forward some specific recommendations to improve the technical efficiency of China's NEI. [ABSTRACT FROM AUTHOR]

Sustainable development has become a global catchphrase in the recent development age. This leads to the growth of various methodologies in evaluating environmental efficiency, such as the Data Envelopment Analysis (DEA) method. The purpose of this study is to propose an extended DEA model, i.e., the undesirable output model, in measuring the relative eco-efficiency scores across nations. The study collected the data of inputs, namely bad outputs and good outputs of the top 20 Asian economies in the period of 2005–2019, and then estimated the environmental efficiency of each country and classified them. The results have shown that there are four nations having higher average environmental efficiency than others. Japan is a good example of sustainable development that simultaneously balances economic development and environmental protection. The study has also discussed possible solutions for improvement to the group of nations with low environmental efficiency. Contributing to applying a novelty extended DEA model, this work recommends a more precise model, taking the weight of outputs into account for further studies. [ABSTRACT FROM AUTHOR]

Trends of globalization very often cause the emergence of phenomena that asymmetrically affect the overall sustainability of the transport system. In order to predict certain situations and potentially be able to manage the transport system, it is necessary to manage risk situations and traffic safety in a timely manner. This study has conducted an investigation which implies defining the level of safety of a total of nine sections of two-lane roads. The main aim of the paper is to create a new multiphase model consisting of CRITIC (The CRiteria Importance Through Intercriteria Correlation), Fuzzy FUCOM (Full Consistency Method), DEA (Data Envelopment Analysis), and Fuzzy MARCOS (Measurement Alternatives and Ranking according to the COmpromise Solution) methods for determining the level of traffic safety on road sections under the conditions of uncertainty. In order for the created model to be adequately applied, eight parameters were created, and they were classified through four inputs and four outputs. To calculate the significance of the inputs, the CRITIC method based on the symmetric correlation matrix was used, and taking into account the nature of the outputs, the Fuzzy FUCOM method based on averaged values using the fuzzy Bonferroni Mean (BM) operator was applied to determine their weights. To determine the degree of safety, the DEA model was created. After that, the Fuzzy MARCOS method was used in order to determine the final ranking of the remaining five sections of the road network. Finally, the verification of results was performed through three phases of Sensitivity Analysis (SA). [ABSTRACT FROM AUTHOR]

The conditions of globalization often dictate the functioning of transport markets, so it is necessary to conduct frequent research in order to achieve sustainable business. This is achieved through adequate risk and safety management at all levels. The research carried out in this paper includes determining the state of railway traffic safety in a total of nine railway sections in Bosnia and Herzegovina (B&H). The aim of this paper is to develop a new integrated Entropy-Fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment)-DEA (Data Envelopment Analysis) model for determining the state of safety in B&H under particular conditions of uncertainty. Additionally, the aim is to combine the advantages of linear programming (DEA), an objective method (Entropy), and a subjective method (Fuzzy PIPRECIA). In this way, an integrated objective–subjective model is created that provides accurate and balanced decision-making through their integration. Eleven sustainable criteria were defined and divided into six inputs and five outputs. The Entropy model was used to determine the weight values of the inputs, while due to the nature of the outputs, Fuzzy PIPRECIA was used to evaluate them. After the application of the two methods, the way of averaging their values was defined. The DEA model, which implies an input- and output-oriented model, was applied to determine which railway sections have satisfactory performance in terms of safety. Two sections were eliminated from further computation due to extremely poor performance and high risk. Then, the weighted overall efficiency ranking method was applied to determine the final ranking of the railway sections. The results obtained were verified through a sensitivity analysis, which involved changing the impact of the five most significant criteria and a comparison with two Multi-Criteria Decision-Making (MCDM) methods. [ABSTRACT FROM AUTHOR]

In order to sustainably and reasonably evaluate the characteristics and efficiency of regional atmospheric environment, this paper calculated the atmospheric environmental efficiency and regional differences, which is based on the non-radial directional distance function DEA model, among 11 cities in Zhejiang Province from 2006 to 2016 in both static and dynamic dimensions. Compared with existing researches, the atmospheric environmental efficiency evaluation system constructed in this paper not only considered the development of regional economy, but also focused on the air quality output so as to constrain the emission of atmospheric pollutants. The results showed that the average value of the static efficiency of atmospheric environment in Zhejiang was 0.6824 over the past ten years, and there was still about 32 percentage difference from the production frontier. The room for improvement in pollution reduction and control was still huge. The pure technical efficiency was the main factor to impede the improvement of atmospheric environment's static efficiency in Zhejiang. Meanwhile the dynamic efficiency of atmospheric environment in Zhejiang reached an average annual rate of 7.60%, with a cumulative increase of 93.28%. As well, there were significant urban differences in the growth rate, of which Hangzhou was the fastest, followed by Ningbo and Jiaxing. The improvement of atmospheric environmental efficiency was mainly driven by technological advancement and scale efficiency expansion. The distribution of 11 cities in the four high and low environmental efficiency matrices was relatively uniform, and there was no "Matthew Effect" of H/H or L/L polarization. In the future, Zhejiang needs to formulate corresponding measures to control the atmospheric pollution by fully considering the actual conditions at different cities, and effectively strengthen the environmental management exchanges and collaboration within the province to enhance the overall atmospheric environment efficiency. [ABSTRACT FROM AUTHOR]

OECD countries are the largest energy consuming economies in the world, improving energy efficiency and reducing pollution emissions is one of the important goals of the environmental tax policies of OECD countries. Based on the total factor energy efficiency index, this paper establishes an epsilon based measure-data envelopment analysis (EBM-DEA) model to measure the energy efficiency levels of 32 OECD countries during 1995–2016 when undesired outputs are included and not included. The effect of environmental factors on energy efficiency evaluation is compared by efficiency analysis and projection value analysis. On this basis, a Panel Logit model was established to empirically examine the impact of energy taxes on energy efficiency in 32 OECD countries. This paper finds that undesired output has a large impact on the energy efficiency level of OECD countries. Measuring energy efficiency levels without considering undesired outputs tends to lead to overestimation of the energy efficiency level of environmentally friendly countries and underestimate the energy efficiency level of countries that value environmental protection. The collection of energy tax has an important impact on energy consumption efficiency. Without considering the unexpected output, the energy tax has a significant impact on improving the efficiency of coal energy consumption. When considering the unexpected output, the energy tax has a significant impact on improving the efficiency of oil energy consumption. Regardless of the expected output or not, the energy tax has a positive effect on improving the efficiency of natural gas energy consumption. The experimental results also show that the energy structure and energy price have a negative impact on energy efficiency, while the progress of environmental protection technology and industrial structure have a positive impact on energy efficiency. Energy taxes have a "double dividend". This paper argues that when evaluating a country's energy efficiency, it should consider the undesired output factors of environmental constraints; governments should pay attention to the role of energy taxes in improving energy efficiency, improve the energy tax system, optimize industrial structure upgrades, stabilize energy prices and support the development of environmental technologies and improve energy efficiency. [ABSTRACT FROM AUTHOR]

As a special financial institution, the financial company has a significant impact on the financial market and real economy. Therefore, further study of the efficiency of financial companies is of great practical significance. China's financial company is equivalent to the "internal bank" of its affiliated group. Therefore, this paper refers to the quantitative analysis and evaluation method of the banking industry, combined with the data characteristics of the financial company's industry. This paper carries out quantitative analysis and evaluation of the efficiency of 79 Chinese enterprise group finance companies from 2011 to 2016 through the DEA model and the Malmquist index model. The results are as follows: From the static point of view (based on the DEA model), the overall efficiency of Chinese financial companies is low and the efficiency is less affected by scale efficiency than that of pure technical efficiency; from the industry classification, the efficiency of oil processing, steel, and nonferrous metal financial companies is better than other industries. From the dynamic point of view (based on the Malquist index model), the overall efficiency of financial companies from 2011 to 2016 has been slightly improved and the efficiency is easily influenced by the change of scale efficiency; from the industry category, the changes of the efficiency, scale efficiency and pure technical efficiency of financial companies of military industry are fastest, and the technical progress of the auto industry financial companies is optimal. [ABSTRACT FROM AUTHOR]

With the general degradation of environmental carrying capacity in recent years, many developing countries are facing with the dual task of economic development and environmental protection. To explore the issue of urban environmental governance, in this research, we establish a Data Envelopment Analysis (DEA) model to investigate the environmental governance regarding temporal and spatial efficiency. Further, we deconstruct environmental governance efficiency into comprehensive efficiency, pure technical efficiency, and scale efficiency and develop a Tobit model to analyze the influencing factors affecting urban environmental governance efficiency. In addition, the above DEA, Tobit model, and deconstruction of efficiency have been applied to study environmental governance efficiency for the Yangtze River urban agglomeration. Findings include: (1) The gap in environmental governance efficiency between cities is highly noticeable, as the highest efficiency index is 0.934, the lowest is only 0.246, and the comprehensive efficiency index has fallen sharply from 0.708 to 0.493 in the past 10 years; (2) Environmental governance efficiency is basically driven by technological progress, while the scale efficiency change index is the main driver of the technological progress change index; (3) For environmental governance efficiency, urbanization and capital openness are irrelevant factors, economic level and urban construction are unfavorable factors, and industrial structure and population density are favorable factors. These findings will help urban agglomerations to effectively avoid the adverse effects of environmental governance efficiency in economic development, and achieve a coordinated development of urban construction and environmental governance.