Search Results (40)

Against the dual backdrop of iterative AI advancement and deepening green development imperatives, AI-driven industrial intelligence (INT) has emerged as a pivotal force in driving sustainable economic growth. While the existing literature has explored the correlation between INT and green total factor productivity (GTFP), significant gaps remain in the design of multidimensional variables, analysis of environmental regulation (ER), and capture of dynamic effects. From the perspective of ER, this study utilizes provincial panel data from China (2012–2023) to construct an 11-indicator evaluation system for INT development and employs the EBM super-efficiency model to measure GTFP. Furthermore, a two-way fixed effects model combined with a moderated mediation model is established to systematically elucidate the intrinsic linkage mechanism between INT and GTFP. The key findings are as follows: First, INT has a significant positive impact on GTFP. Second, green innovation and spatio-economic synergy are crucial pathways through which INT empowers GTFP. Third, ER exhibits a substitution effect within both the direct and indirect impacts of INT on GTFP, where intensified ER significantly attenuates INT’s positive impacts. Fourth, the enhancement effect of INT on GTFP remains statistically significant with a one-year lag, and the substitution effect of ER persists. This study provides an in-depth analysis of the mechanisms of INT-driven green economic transformation, offering valuable insights for governments to implement differentiated environmental governance strategies tailored to local conditions. Full article

Drawing on panel data for eight major citrus-producing provinces in China from 2008 to 2021, this study employs the super-efficiency EBM model—which incorporates both radial proportion and non-radial slack variables—to measure citrus green total factor productivity (GTFP). Temporal changes are investigated via the GML index, while regional disparities and convergence patterns are examined through a series of complementary techniques, thereby offering a comprehensive view of the sector’s green and coordinated development. The results reveal that, from a static perspective, the technical efficiency of most citrus-producing provinces remains below the production frontier. Dynamically, regional GTFP diverged markedly over the study period, with technical efficiency serving as the principal driver of growth. Convergence tests show no evidence of σ-convergence for the nation as a whole or for any of the three major producing regions. Absolute and conditional β-convergence coexist at the national level and in the upper–middle Yangtze region; the Zhejiang–Fujian hills exhibit no β-convergence, whereas the Guangdong–Guangxi hills display conditional β-convergence only. The findings indicate substantial room for improvement in China’s citrus GTFP. We therefore recommend that each region (1) accelerates green-technology innovation, (2) designs differentiated yet coordinated regional strategies, (3) institutionalizes long-term safeguards for green development, and (4) deepens international cooperation to enhance global competitiveness. Full article

Under the “double security” goal of achieving both food security and ecological protection, this study explores the green and low-carbon utilization efficiency of cultivated land (GLCUECL) in the Huaihe River Ecological Economic Belt (HREEB). This study identifies the spatiotemporal evolution characteristics and trends, promoting the green, low-carbon, and sustainable utilization of arable land resources in the HREEB, thus contributing to regional and national food and ecological security. Using a global super-efficiency EBM framework that accounts for undesirable outputs, as well as the GML index, the researchers measured and decomposed the GLCUECL in 25 prefecture-level cities of the HREEB from 2005 to 2021. The Theil index and kernel density estimation were applied to analyze regional disparities and changing developmental traits. Spatial convergence and divergence were assessed using the coefficient of variation and spatial convergence models. Key findings include the following: (1) Over time, the GLCUECL in the HREEB exhibited an overall upward trend and a non-equilibrium characteristic, namely the “East Sea-river-lake Linkage Area (ESLA) > Midwest Inland Rising Area (MIRA) > Huaihe River Ecological Economic Belt (HREEB) > North Huaihai Economic Zone (NHEZ)”. The increase in the GML index of the GLCUECL is mainly attributable to a technical progress change. (2) The overall difference in the GLCUECL tends to decline, which is mainly attributable to the intra-regional differences. (3) The overall kernel density curves for the HREEB and its three sub-regions exhibited a “rightward shift” trend. Except for the expansion and polarization of the absolute difference in the GLCUECL in the NHEZ, the absolute difference in GLCUECL in other regions, such as the HREEB, ESLA, and MIRA, exhibited a decreasing trend. (4) Spatial convergence analysis revealed that only the NHEZ lacks σ-convergence, whereas all regions exhibited β-convergence. Moreover, factors such as rural economic development level, cultivated land resource endowment, agricultural subsidy policy, crop planting structure, and technological input exerted a heterogeneous effect on the change in the GLCUECL. Based on these findings, this study offers recommendations for improving GLCUECL in the HREEB. Our recommendations include the implementation of the concept of green new development, optimization of the institution supply, establishing a regional cooperation mechanism for green and low-carbon utilization of cultivated land, and formulation of differentiated paths for improving the green and low-carbon utilization efficiency of cultivated land according to local conditions. Full article

In the context of global efforts to address climate change and pursue sustainable development, green finance (GF) and energy efficiency (EE) have become key issues of focus for academics and policymakers. This study explores the spatiotemporal coupling characteristics and driving factors of China’s green finance and energy efficiency from 2011 to 2022, aiming to help China achieve its dual carbon goals. This study used a three-dimensional framework to assess 30 provinces, considering factor inputs, expected outputs, and undesirable outputs. The study employed the global benchmark super-efficiency EBM model, entropy method, coupling coordination model (CCD), Dagum Gini coefficient decomposition, and spatiotemporal geographic weighted regression model (GTWR). Key findings include a “high in the east, low in the west” gradient distribution of both green finance and energy efficiency, expanding regional disparities, and a strong synergistic effect between technological innovation and energy regulation. Based on the findings, this paper proposes a three-tier governance framework: regional adaptation, digital integration, and institutional compensation. This study contributes to a deeper understanding of the coupling theory of environmental financial systems and provides empirical support for optimizing global carbon neutrality pathways. Full article

Developed countries with animal husbandry are confronted with the pressing issues of ensuring stable livestock product supplies while maintaining ecological sustainability. Additional research is required to ascertain whether environmental regulation can effectively facilitate the green transformation of animal husbandry and establish a harmonious equilibrium between environmental protection and economic growth. It is essential for the empirical development of environmental policies in animal husbandry, as it evaluates the impact of regulatory measures on this sector’s ecological efficiency and precisely investigates the underlying mechanisms of these effects. This paper evaluates the nonlinear impact of environmental regulation policies on the ecological efficiency of animal husbandry using the super-efficiency EBM model, spatial Durbin model, and panel threshold model, which are based on panel data from 31 Chinese provinces (2010–2022). The findings indicated that: (1) The ecological efficiency and environmental regulation intensity of animal husbandry in China exhibited a fluctuating upward trend. The environmental regulation is ranked from high to low in the following order: Northeast, West, Central, and Eastern regions. Conversely, the regions with high ecological efficiency are concentrated in the Northeast and Western regions. (2) The impacts of environmental regulation on the ecological efficiency of animal husbandry were N-type nonlinear, with the extreme points being 6.322 and 9.456. Environmental regulation also produced an “inverted N” type spatial spillover effect on the ecological efficiency of animal husbandry in adjacent areas, with extreme values of 5.330 and 7.670. (3) Environmental regulation considerably enhanced the ecological efficiency of animal husbandry in the Eastern and Central regions in terms of location characteristics. The influence on the Western and Northeastern regions exhibited N-type nonlinear characteristics. (4) From 2017 to 2022, ER had an N-type nonlinear effect on animal husbandry ecological efficiency in terms of temporal heterogeneity. However, the effect was not significant from 2010 to 2016. Full article

Agricultural practices significantly impact environmental sustainability, making the enhancement of Agricultural Ecological Efficiency (AEE) crucial for China’s sustainable agricultural development. However, the spatial-temporal evolution patterns and underlying driving forces of AEE remain insufficiently understood in the context of China’s rapid agricultural transformation. To address this research gap, we analyzed AEE across 30 Chinese provinces from 2000 to 2021, identifying spatial patterns and key influencing factors. Employing a Super-Efficiency EBM model with undesirable outputs, we calculated provincial AEE scores. Spatial analysis tools, including Moran’s I, Dagum Gini decomposition, and kernel density estimation, were applied to explore regional differences. We also utilized Geo-detector to quantify driving factors and their interactions. The results demonstrated a clear west-to-east and south-to-north gradient of declining AEE, with western provinces exhibiting higher efficiency levels. Despite narrowing disparities within the eastern and western regions, central regions displayed increasing intra-regional differences. Geo-detector analysis further highlighted significant interactive effects among factors such as urbanization, governmental agricultural support, education levels, and precipitation, enhancing the explanatory power of AEE spatial variations. These findings support region-specific policies for optimizing agricultural structures and resource efficiency, facilitating China’s ecological transition in agriculture. Full article

The Western Taiwan Strait (WTS) Economic Zone connects the Yangtze River Delta and the Pearl River Delta, playing a significant role in China’s coastal economy and forming part of the East Asian economic structure. This study used panel data from 20 cities in the WTS Economic Zone, spanning 2011 to 2020, to investigate urban land use efficiency and its dynamic evolution characteristics. The study used a super-efficiency EBM model, which accounts for undesirable outputs, combined with kernel density estimation and Malmquist–Luenberger (ML) index analysis, to thoroughly examine the changes in total factor productivity (TFP) of urban land use and the factors driving these changes within the WTS Economic Zone. The findings are as follows: (1) From 2011 to 2020, the overall trend of urban land use efficiency in the WTS Economic Zone was upward, with coastal areas generally exhibiting higher urban land use efficiency compared to inland areas. (2) The urban land use efficiency of cities in the WTS Economic Zone displayed four types of changes: rising, stable, “U”-shaped, and inverted “U”-shaped. (3) The TEP index of the WTS Economic Zone exhibited a right-leaning “M” trend. Technological change was the primary driver of enhanced urban land use efficiency, although there is still room for improvement in technical efficiency. Based on these findings, this study proposes policy insights to foster high-quality development of urban land use efficiency in the WTS Economic Zone. Full article

The construction industry in Saudi Arabia has been modernized through the implementation of green building technologies and intelligent building systems, which have facilitated the sustainable development of the construction industry in Saudi Arabia. However, there is a paucity of research on the current situation of the construction industry in Saudi Arabia. In this study, the super-efficient epsilon-based measurement (EBM)–Malmquist model was used to measure the static and dynamic efficiency of the construction industry in the administrative areas of the 13 provinces of Saudi Arabia from 2013 to 2022, and the Tobit model was used to empirically analyze the factors affecting the efficiency of the industry. In addition, the spatial autocorrelation of the efficiency of the industry was analyzed using Moran’s Index (MI) to study the characteristics of the spatial distribution of industrial efficiency as well as the effectiveness of resource allocation. The study shows that Saudi Arabia’s construction industry is at a low level of development; the population, GDP, and carbon dioxide emissions have a significant impact on the efficiency of the industry; and the development of the industry can help to reduce carbon dioxide emissions, thus promoting environmental sustainability; Saudi Arabia’s construction industry has a spatial spillover effect but does not have a significant agglomeration effect. This study accurately identifies the current situation of the development of the construction industry in Saudi Arabia and proposes several countermeasures and opinions, which are expected to provide a theoretical basis for realizing its sustainable development. Full article

Accelerating the green development of the dairy industry is an important work to promote the construction of ecological civilization and ensure the safe supply of dairy products. Existing studies lack a comprehensive analysis of the green development characteristics of China’s dairy industry. Based on the input–output system, the study measured and analyzed the green total factor productivity of China’s dairy industry in 29 provinces (cities, autonomous regions, and municipalities) since the 10th Five-Year Plan period, using the super-efficiency EBM model and the GML index based on non-directional and variable scale returns. Accelerating the green development of the dairy industry is an important work to promote the construction of ecological civilization and ensure the national nutrition intake. The existing studies lack a comprehensive understanding of the green development characteristics of China’s dairy industry. Therefore, this paper constructs an input–output system, measures and analyzes the green total factor productivity of the dairy industry in 29 provinces (cities, autonomous regions and municipalities directly under the Central Government), since the “15th Five-Year Plan” period based on the non-oriented super-efficiency EBM model and GML index with variable returns to scale. On this basis, the dynamic evolution of regional differences was explored using Kernel density estimation and the Dagum Gini coefficient, and the influencing factors of green total factor productivity in China’s dairy industry were analyzed using a two-way fixed effects model. The results show that from 2001 to 2020, the green total factor productivity of China’s dairy industry showed an overall upward trend, and presented a gradient pattern of “Northeast–East–Central–West” in turn, with green technical efficiency being the main driving force for promoting green total factor productivity in China and various regions. The gap in green total factor productivity between provinces and cities is gradually narrowing, and the polarization phenomenon is weakening. Super variation density is the main source of regional differences, and the difference between the West and the East is the largest, while the difference between the Central and the Northeast is the smallest. As for the influencing factors, industry agglomeration, economic development level, and environmental planning level have a significant positive promoting effect on the green total factor productivity of China’s dairy industry, while the level of population urbanization has a significant inhibitory effect on it. In order to promote the green and sustainable development of China’s dairy industry and promote the coordinated development of regional green, it is necessary to accelerate the efficiency of green technology while promoting the innovation of green technology, accelerate the integrated development of industry and formulate relevant policies according to local conditions to promote the coordinated development of green technology between regions. Full article

Due to the basic carrier function of land, the economic and ecological effects of Environmental Protection Tax Law (EPTL) will be reflected in the land use. Therefore, this article investigates the effect of EPTL on land green use efficiency (LGUE). To be specific, based on the panel data of 278 prefecture-level cities in China from 2012 to 2020, LGUE is evaluated through a global super efficiency epsilon-based measure (EBM) with unexpected output. Then, the reform of “sewage fee-to-tax” is regarded as a natural experiment to accurately evaluate the effect of EPTL on LGUE. The result that the implementation of EPTL significantly drives LGUE is confirmed. The mechanism tests show that the implementation of EPTL enhances the intensity of green innovation, promotes the optimization of industrial structure, and thereby improves LGUE. Moreover, we find that the moderating effect of tax rate increase is nonlinear and exhibits an inverted U-shape. That is, below a certain value, the tax rate increase will strengthen the EPTL’s ability to improve LGUE. However, after exceeding the value, the tax rate increase will weaken the EPTL’s ability to improve LGUE. Targeted suggestions are proposed for improving the environmental protection tax system and LGUE. Full article

Understanding how industrial agglomeration affects agricultural green production efficiency is essential for green agricultural development. This study uses the super-efficient Epsilon-Based Measure (EBM) model and Global Malmquist–Luenberger (GML) index to measure and analyze the spatial and temporal evolution characteristics and core sources of dynamics of agricultural green production efficiency in China by using panel data from 30 Chinese provinces from 2006 to 2020. It also empirically investigates the relationships between industrial agglomeration, land transfer, and agricultural production efficiency. By using fixed, intermediary, and threshold effect models, the internal links between industrial agglomeration, land transfer, and agricultural green production efficiency are examined. The findings indicate the following. (1) The green production efficiency of Chinese agriculture exhibits the regional characteristics of being “high in the west and low in the east, high in the south and low in the north” in terms of space; in terms of time, the overall trend is that green production technology efficiency is growing, with an average annual growth rate of 11.45%, and the growth primarily depends on the “single-track drive” of green technological progress. (2) Industrial agglomeration significantly affects agricultural green production efficiency, green technology efficiency, and green technology change; the corresponding coefficient values are 0.115, 0.093, and 0.022. (3) According to the mechanism-of-action results, land transfer mediates the effects of industrial agglomeration on agricultural green production efficiency, green technology efficiency, and green technology change. These effects have effect values of 28.48%, 27.91%, and 47.75%, respectively. (4) The threshold effect’s findings demonstrate a double threshold effect of industrial agglomeration on the green production efficiency of agriculture in terms of land transfer, with threshold values of 1.468 and 3.891, respectively. As a result, this study suggests adhering to the idea of synergistic development, promoting agricultural green development, strengthening the development of industrial agglomerations, promoting the quality and efficiency of industry, improving land-transfer mechanisms, and placing a focus on resource efficiency improvements, as well as other policy recommendations. Full article

Achieving synergistic development of efficient urban land use and the natural environment is crucial in promoting green urbanization. The assessment of land use eco-efficiency (LUEE) and its temporal–spatial changes provides an effective means of quantifying the relationship between the urban ecological environment and land use. Targeting 55 selected cities in the Yellow River Basin (YRB), in this study, we utilize the Super-EBM method to gauge the LUEE. We explore the temporal patterns and the spatial convergence of LUEE utilizing kernel density estimation and spatial econometric methods. Considering the resource and environmental costs of land use, we assumed the industrial pollutant emissions generated during urban land use as the undesired outputs and designed a framework for measuring the level of LUEE under double constraints, which theoretically revealed the formation process and spatial convergence mechanism of LUEE. The results show the following: (1) Throughout the sample period, the LUEE of the YRB urban agglomeration decreased from 0.158 in 2009 to 0.094 in 2020, indicating a decreasing spatial disparity in LUEE over time. Notably, the Lanxi urban cluster exhibited the largest gap in LUEE, whereas the Guanzhong Plain urban agglomeration displayed the smallest gap. The hyper-variable density exceeded the inter-group gap as the main factor leading to the difference in LUEE. (2) Although the LUEE of urban agglomerations has increased, there still exists a noticeable polarization phenomenon. (3) The LUEE of YRB demonstrates a pattern of conditional convergence and exerts a significant spatial spillover effect. Over time, the LUEE of YRB will tend towards an individual steady state. The findings have implications for strengthening linkage and synergy among cities in YRB, promoting factor integration across administrative regions, and formulating heterogeneous policies. Full article

Utilizing Chinese provincial panel data from 2006–2019, this paper applies the super-efficient epsilon-based measure (EBM) model including non-desired output to measure carbon emission efficiency (CE) and analyze spatio-temporal characteristics of CE, in which social fixed asset investment, energy consumption and urban employment per unit are used as input indicators and regional GDP and CO2 emissions are used as output indicators. Additionally, we use the spatial Durbin model to explore the impact of urban-rural income disparity (URID) on carbon emission efficiency and its spatial spillover effect and explore indirect mechanisms of consumption level and consumption structure on CE using mediating effect test. The results showed that: (1) The national CE level generally declined between 2006–2012 and fluctuated upward from 2013–2019. The trend of regional CE showed “high in the east and low in the west”. (2) The “inverted U” model accurately reflects the relationship between national CE and URID, with a “U” shaped association in the central, western, and northeastern regions, and a positive correlation with consumption level and consumption structure. (3) There is a significant mediating effect of consumption level and structure in the mechanism of URID in regulating CE. Local governments should adopt local policies, take measures to narrow URID and CLD, advocate low-carbon and environmentally friendly living for residents, and promote the upgrading of consumption structure to boost carbon emission efficiency. Full article

The sustainability of mariculture depends on adopting green technologies, which can mitigate the negative impacts on the environment and ensure long-term viability. However, existing studies do not comprehensively understand the characteristics and regional differences of green technology progress (GTP) in mariculture. According to data from ten coastal regions from 2008 to 2020, this study adopts the Epsilon-Based Measure (EBM)-Malmquist model to measure the GTP of mariculture, uses the Dagum Gini coefficient to analyze the spatial differences of GTP, and uses convergence models to explore the convergence of GTP. The results showed that: (1) the GTP of China’s mariculture showed a fluctuating upward trend temporally and significant spatial differences. The overall differences showed a dispersion trend over time. The contributions of inter-regional super variable net value difference (Gnb), inter-regional transvariation intensity (Gt), and intra-regional difference (Gw) were 38.813%, 31.256%, and 29.931%, respectively. (2) The degree of dispersion of GTP among different regions has not decreased with time, which means there is no apparent σ convergence. Absolute β convergence and conditional β convergence existed in GTP, and the absolute value of the latter was greater than that of the former. That is, the growth rate of GTP will first reach their respective steady-state levels and then approach a unified steady-state equilibrium level. Full article

The improvement of port cluster eco-efficiency is of great significance to constructing a world-class shipping hub and the high-quality development of regional economy. This study adopts the Super-EBM (Super-efficiency Epsilon-Based Measure) model to evaluate the eco-efficiency of the Yangtze River Delta port cluster in China, and the GML (Global Malmquist-Luenberger) index, spatial hot spot analysis, gravity center migration model, and the Theil index are combined to reveal the spatial-temporal evolution. The results show that the average eco-efficiency of the Yangtze River Delta port cluster is 0.686, with 55.6% of the ports being below the average, which is directly related to the low scale efficiency. Mainly driven by technical efficiency improvement, the overall eco-efficiency has a growth rate of 8.7% from 2010 to 2019. Moreover, considerable spatial divergence has formed in the port cluster, and the eco-efficiency gravity center has always been in the south of Jiangsu. The overall eco-efficiency gap has widened by 19.92%, and the gap within the region, particularly within Zhejiang, is the major source. To improve the overall eco-efficiency of the port cluster, policymakers should strengthen the technological spillover of ecologically efficient ports in clean production and mechanism reform, while optimizing the resource consolidation system of ports with relatively low eco-efficiency. Full article