Search Results (127)

This study employs a Super-SBM model to construct a comprehensive evaluation framework—encompassing input factors, desirable outputs, and undesirable outputs—to measure agricultural green total factor productivity (AGTFP) in the Tibet Autonomous Region in the period 2002–2021. We then apply kernel density estimation and Dagum Gini coefficient decomposition to examine its spatiotemporal evolution. The main findings are as follows: (1) AGTFP in Tibet rose overall from 0.949 in 2002 to 1.068 in 2021, with a compound annual growth rate of 0.78%, yet remained below the national average; (2) significant regional heterogeneity emerged, with three typical evolution patterns identified: continual improvement (Nagqu, Qamdo), stable fluctuation (Lhasa, Xigazê), and risk of decline (Lhoka, Nyingchi, Ngari); (3) gains in pure technical efficiency were the primary driver of AGTFP growth, while insufficient scale efficiency was a key constraint; (4) AGTFP exhibited a “convergence–divergence–reconvergence” dynamic, with interregional disparities widening but structural patterns stabilizing; and (5) interregional inequality was the main source of overall disparity—its importance grew over the study period, with the largest gap observed between agrarian and pastoral zones. On this basis, we recommend a “gradient advancement” strategy that prioritizes pure technical efficiency and regional coordination, while promoting zone-specific support tools tailored to local ecological conditions and institutional capacities to ensure inclusive green productivity growth. Full article

As pivotal nodes in maritime logistics networks, ports face mounting pressure to reconcile economic growth with environmental sustainability. Although the SBM-Undesirable model has been extensively applied to assess port environmental efficiency (PEE), most applications assume strong disposability and disregard heterogeneity in technological capacities across different port scales, potentially biasing the assessments. To overcome these limitations, coastal ports are initially categorized into three subgroups based on operational scale criteria. A meta-frontier SBM-Undesirable model incorporating weak disposability is then developed to evaluate PEE. Dynamic characteristics are further explored via the Global Malmquist Index. Results indicate substantial disparities between subgroup frontiers and the meta-frontier. The average group PEE (0.732) exceeded the meta PEE (0.570), implying potential overestimation under homogeneity assumptions. Large-sized ports, with a mean technology gap ratio (TGR) of 0.956, operated near the meta-frontier, whereas medium-sized and small-sized ports, with TGRs of 0.770 and 0.600 respectively, exhibited substantial technological gaps. Total factor productivity (TFP) demonstrated a volatile upward trend, averaging 6.8% annual growth. In large-sized and medium-sized ports, TFP growth was primarily driven by technological innovation, whereas in small-sized ports, it stemmed from combined improvements in technical efficiency and technological level. These insights underscore the necessity of differentiated decarbonization strategies for port management. Full article

Improving forest carbon sink efficiency (FCSE) is the key to mitigating climate change and achieving sustainable forest resource management in China. However, current research on FCSE remains predominantly focused on static perspectives and singular linear effects. Based on panel data from 30 provinces (autonomous regions and municipalities) in China from 2008 to 2022, this study integrated the super-efficiency Slack-Based Measure (SBM)-Malmquist–Luenberger (ML) model, spatial autocorrelation analysis, and dynamic fuzzy set qualitative comparative analysis (fsQCA) to reveal the spatiotemporal differentiation characteristics of FCSE and the multi-factor synergistic driving mechanism. The results showed that (1) the average value of the FCSE in China was 1.1. Technological progress (with an average technological change of 1.21) is the core growth driver, but the imbalance of technological efficiency change (EC) among regions restricts long-term sustainability. (2) The spatial distribution exhibited a U-shaped gradient pattern of “eastern—southwestern”, and the synergy effect between nature and economy is significant. (3) The dynamic fsQCA identified three sustainable improvement paths: the “precipitation–economy” collaborative type, the multi-factor co-creation type, and “precipitation–industry-driven” type; precipitation was the universal core condition. (4) Regional differences exist in path application; the eastern part depends on economic coordination, the central part is suitable for industry driving, and the western part requires multi-factor linkage. By introducing a dynamic configuration perspective, analyzing FCSE’s spatiotemporal drivers. We propose a sustainable ‘Nature–Society–Management’ interaction framework and region-specific policy strategies, offering both theoretical and practical tools for sustainable forestry policy design. Full article

The impact of urbanization on the agricultural economy has long attracted scholarly attention. Taking China as a case, this study investigates the relationship between urbanization and agricultural development under the dual progress of urbanization and the rural revitalization strategy. Based on panel data from 31 mainland provinces, this paper measures agricultural economic efficiency using the global slack-based measure (SBM) model and employs quantile regression to systematically analyze the influence of various urbanization factors across different levels of agricultural efficiency. A Tobit regression model is further adopted for robustness checks. The results show that representative urbanization factors, such as the proportion of urban population and the prevalence of higher education, exert significant negative impacts on agricultural efficiency, particularly in regions with higher efficiency levels. Freight volume has a significantly negative effect in regions with medium and low efficiency, while freight turnover negatively impacts medium- to high-efficiency areas. In contrast, improvements in healthcare services and digital infrastructure are found to consistently enhance agricultural efficiency. Although the corporatization of agriculture is often regarded as a key outcome of urbanization, its efficiency-improving effect is not statistically significant in most models and is mainly concentrated in high-efficiency regions. Overall, the improvement in China’s agricultural economic efficiency relies more on direct support from the rural revitalization strategy, while rapid urbanization has failed to bring substantial benefits and has even led to structural negative effects. These adverse outcomes may stem from the rapid occupation of suburban farmland, increased logistics costs due to the relocation of agricultural activities, and the ineffective absorption of surplus rural labor. This study highlights the need for future urbanization policies in China to pay greater attention to the coordinated development of the agricultural economy. The methods and findings of this research also provide reference value for other developing regions facing similar urbanization-agriculture dynamics. Full article

In the context of global climate change and the escalating energy crisis, the development of new energy vehicles (NEVs) has become a critical strategy for China to foster green transformation and achieve its carbon neutrality goals. This study focuses on A-share-listed NEV companies in China from 2015 to 2023, specifically those listed on the Shanghai or Shenzhen Stock Exchange and subject to domestic regulatory standards and disclosure requirements. These firms were selected due to the representativeness, availability, and quantifiability of their data. A super-efficient-network SBM model based on undesirable outputs and the Malmquist index were employed to assess the static and dynamic green technology innovation efficiency of 260 NEV enterprises. Additionally, the Tobit regression model was applied to analyze the influencing factors. The findings reveal that the overall green technology innovation efficiency of Chinese NEV enterprises is relatively low and has exhibited a declining trend over the years. Furthermore, the efficiency of enterprises in the western regions surpasses that of those in the eastern and central regions. Key factors, including government support, enterprise scale, and R&D investment, significantly inhibit the green technology innovation efficiency of firms. Based on these findings, this paper recommends prioritizing the innovation of core technologies, addressing regional disparities in development, and implementing tailored policies to enhance the green technology innovation efficiency and economic performance of NEV enterprises. Full article

The core hallmark of new quality productive forces (NQPFs) is a substantial increase in total factor productivity. Developing NQPFs tailored to local conditions significantly promote green, low-carbon, and environmentally sustainable development. This paper selects 30 provinces and municipalities in China (excluding Hong Kong, Macao, Taiwan, and Tibet) as research samples. It employs the super-efficiency Slacks-Based Measure (SBM) model, coupling coordination degree analysis, kernel density estimation, Dagum Gini coefficient, and β-convergence analysis to measure and analyze the coupling coordination degree between NQPFs and carbon total factor productivity (CTFP). The results indicate that CTFP exhibits an upward trend overall. At the same time, the NQPFs show an initial increase, followed by a decline, with significant regional variations observed in both. There is notable regional heterogeneity in the coupling coordination degree between NQPFs and CTFP. The eastern region demonstrates the highest coupling coordination degree, followed by the central, western, and northeastern regions. The primary cause of this differential distribution is inter-regional disparities, particularly widening the gap between the eastern region and others. Further analysis reveals that, except for the eastern region, the dynamic evolution trend of coupling coordination nationwide and in other regions tends to converge. Regarding absolute β-convergence, the northeastern region converges the fastest, while the western region converges the slowest. Regarding conditional β-convergence, the convergence speeds in the central, western, and northeastern regions are consistent, but the convergence results remain unchanged. This study provides important theoretical support for achieving a balanced development of NQPFs and comprehensively enhancing CTFP, ensuring significant contributions to the sustainable development of a low-carbon economy. Full article

This study investigates the coupling and coordination between resilience and efficiency in promoting the sustainable development of tourism economies, using the Beijing–Tianjin–Hebei urban agglomeration as a case study. The study employs an integrated approach combining the improved CRITIC-Entropy method, super-efficiency SBM model, and coupling coordination degree model to measure the coupling coordination degree between tourism economic resilience and efficiency, examining their spatiotemporal evolution. Further, a PVAR model is used to explore the bidirectional dynamic relationship between resilience and efficiency. The findings indicate that the coupling coordination between tourism economic resilience and efficiency in the Beijing–Tianjin–Hebei urban agglomeration has evolved from a “coordination transition stage (2011–2012)” to a “coordination development stage (2013–2020)”, showing a trend towards positive coordination. Spatial analysis reveals significant regional differences, with Beijing and Tianjin having higher coupling coordination levels than Hebei Province, demonstrating the radiating effect of core cities, while the overall level within Hebei’s cities still needs improvement. The study confirms a positive interaction between tourism economic resilience and efficiency, with both exhibiting self-enhancing mechanisms. This research highlights the importance of balancing resilience and efficiency for sustainable tourism economic development. It offers valuable insights for policymakers and regional planners to enhance the adaptability and competitiveness of tourism economies in response to external shocks, contributing to the long-term sustainability of the industry. Full article

This study focuses on the coupling and coordination between China’s new-type urbanization (NU) and transportation carbon emission efficiency (CET), revealing its spatial and temporal evolution patterns and driving factors. In recent years, the rapid rise of the digital economy has profoundly reshaped traditional industrial structures. It has catalyzed new forms of production and consumption and opened up new pathways for carbon reduction. This makes synergies between NU and CET increasingly important for realizing a low-carbon transition. In addition, digital infrastructures such as 5G networks and big data platforms promote energy efficiency and facilitate industrial upgrading. It also promotes the integration of low-carbon goals into urban governance, thus strengthening the linkages between NU and CET. The study aims to provide a scientific basis for regional synergistic development and green transformation for the goal of “dual carbon”. Based on the panel data of 30 provinces in China from 2004 to 2021, the study adopts the entropy weight method and the super-efficiency SBM model to quantify NU and CET, and then analyzes their spatial and temporal interactions and spatial spillovers by combining the coupled coordination degree model and the spatial Durbin model. The following is found: (1) NU and CET show a spatial pattern of “leading in the east and lagging in the west”, and are optimized over time, but with significant regional differences; (2) the degree of coupling coordination jumps from “basic disorder” to “basic coordination”, but has not yet reached the level of advanced coordination, with significant spatial clustering characteristics (Moran’s I index between 0.244 and 0.461); (3) labor force structure, transportation and energy intensity, industrial structure and scientific and technological innovation are the core factors driving the coupled coordination, and have significant spatial spillover effects, while government intervention and per capita income have limited roles. This paper innovatively reveals the two-way synergistic mechanism of NU and CET, breaks through the traditional unidirectional research framework, and systematically analyzes the two-way feedback effect of the two. A multidimensional NU evaluation system is constructed to overcome the limitations of the previous single economic or demographic dimension, and comprehensively portray the comprehensive effect of new urbanization. A multi-dimensional coupled coordination measurement framework is proposed to quantify the synergistic evolution law of NU and CET from the perspective of spatio-temporal dynamics and spatial correlation. The spatial spillover paths of key factors are finally quantified. The findings provide decision-making references for optimizing low-carbon policies, promoting green transformation of transportation, and taking advantage of the digital economy. Full article

Resource-based regions face particular challenges in achieving sustainable land-use transformation due to their entrenched development patterns. Through an integrated approach (super-efficiency SBM, Global Moran’s I, synergistic modeling, and SNA), this study analyzes Shanxi Province’s land-use efficiency dynamics (2015–2021), revealing (1) an N-shaped efficiency trajectory with core-periphery polarization stable high-efficiency clusters (Taiyuan/Yangquan/Luliang, mean > 1.1) versus fragmented northern mining zones and stagnant southern regions; (2) deficient spatial coordination (Moran’s I < 0) and failed capital-city spillovers, with only 2/10 cities achieving positive synergy; and (3) network instability (density = 0.14–0.29) featuring paradoxical power shifts in the emerging mining hub Shuozhou (degree = 100) outperforming traditional cores. Based on these findings, this study proposes policy recommendations from the perspective of regional policymakers, focusing on establishing provincial-level land resource utilization planning, promoting coordination among cities in terms of land resource utilization at the municipal level, and improving land resource utilization efficiency through environmental regulations. This study offers a new perspective on regional coordination for sustainable development in resource-based regions by conducting research at the provincial level, advancing policy suggestions at the meso-policy level for the green transformation of resource-based cities, and providing theoretical support for promoting the intensive and efficient utilization of land across cities in specific regions. Full article

Current evaluations of carbon emission efficiency in China’s provincial power industry often neglect the impact of carbon transfers from inter-regional power transmission, leading to biased assessments that hinder the sustainable development of the energy transition. To address this, we propose an advanced efficiency evaluation model that incorporates a multi-regional input–output (MRIO) framework, refining CO₂ emission calculations and correcting parameter deviations in the slack-based measure (SBM) model. This model improves both the precision and fairness of carbon emission efficiency assessments. We apply the MRIO-SBM model to evaluate carbon emission efficiency in the power industry across 30 provinces in China for 2012, 2015, and 2017, revealing the impact of carbon transfers on efficiency. The results indicate that incorporating MRIO improves the precision of SBM evaluations. Significant regional disparities are observed: eastern coastal regions achieve higher efficiencies, while northeastern and western regions typically exhibit lower values, ranging from 0.5 to 0.7. Efficiency evaluations must account for carbon transfer dynamics, as these transfers can lead to overestimations of efficiency by up to 19% in electricity-importing regions and underestimations of approximately 10% in electricity-exporting regions. Furthermore, the findings emphasize the need to foster low-carbon cross-regional collaboration to promote sustainable development in the power industry. Full article

Improving the green efficiency of urban land use (GEULU) is essential for optimizing resource utilization while minimizing waste and pollution, making it a critical factor influencing the sustainability of urban development. However, the spatiotemporal heterogeneity of the impact of China’s New-Style Urbanization (NU) policy on the GEULU, particularly at the urban agglomeration scale, remains understudied. This study employed a super SBM-DDF-GML model and spatial data analysis to examine the characteristics and spatiotemporal dynamics of the GEULU and its interactions with varying implementations of NU at the regional, urban agglomeration, and city levels. The results show that China’s GEULU followed a “U-shaped” tendency from 2006 to 2020. Cities in western China exhibit higher levels of green efficiency but slower growth, compared with lower absolute levels and faster development rates amongst the eastern cities. The GEULU displays a significant positive spatial autocorrelation, with “high-high clusters” shifting from west to east and “low-low clusters” moving in the opposite direction. The impact of NU on the GEULU is divergent: positive in eastern and central regions but negative in the western areas. Economic urbanization, urban population growth, and the clustering of research and education facilitate green efficiency, while urban sprawl significantly hinders its improvement. Social urbanization and digitalization exert adverse effects on green efficiency across many cities. Ecological and environmental protections promote the GEULU in southwestern cities but obstruct it in northeastern cities. The negative effect of NU on the green efficiency has diminished over time, while its positive effects have grown stronger. These findings provide insightful information for urban planners and politicians in crafting region-contextualized adaptive strategies to enhance sustainable urbanization and efficient land use in China. Full article

The carbon emission trading system (ETS), as a market-based environmental regulation tool, remains the subject of ongoing theoretical debates and empirical gaps regarding its impact on energy efficiency and the underlying mechanisms. This study focuses on China’s carbon emission trading pilot policies, utilizing panel data from 30 Chinese provinces between 2003 and 2023. The SBM-undesirable model is employed to assess energy efficiency, and the difference-in-differences (DID) model is applied to identify the causal effects of the policy. Additionally, a mechanism-testing model is utilized to explore how the carbon emission trading policy enhances energy efficiency. The findings indicate the following: (1) overall energy efficiency in China has remained relatively stable over the past two decades, but high-efficiency regions exhibit significant regional clustering effects; (2) the carbon emission trading pilot policy has significantly improved energy efficiency in the pilot regions, with a dynamic trend of “shock–enhancement–stability”, reaching its peak effect in the third year post-implementation; (3) the mechanism analysis reveals that the policy primarily enhances energy efficiency through three channels: promoting green technology innovation, advancing the use of clean energy, and strengthening government environmental regulation. This study not only provides empirical evidence to support the optimization of carbon market policies but also offers a practical framework for developing countries to design emission reduction mechanisms that align with their economic structures and policy environments. Full article

To achieve the green and efficient utilization of land in China’s three northeastern provinces and to harmonize the human–land relationship, this paper examines the spatiotemporal evolution and convergence of land green utilization efficiency (LGUE) in these provinces against the backdrop of population contraction. Utilizing data from 2000 to 2020, we employ the geometric mean method to characterize the features of population contraction and construct a global reference non-desired super-efficiency SBM-DEA model to measure LGUE. The dynamic evolution of LGUE is analyzed using kernel density estimation and spatial visualization techniques, and its convergence is tested through σ-convergence and absolute β-convergence methods. The results indicate that during the study period, the population in the three northeastern provinces has experienced overall contraction, predominantly characterized by a “growth-to-contraction” pattern, which is more pronounced in resource-based cities. Land green utilization efficiency exhibits a fluctuating upward trend, evolving spatially into a distribution pattern of “high in the middle and low on both sides along the northeast–southwest axis”. The degree of dispersion among cities also shows an upward fluctuation, with evidence of σ-convergence and absolute β-convergence. Regional balance has improved. This study concludes that there is significant potential for enhancing land green utilization efficiency in the three northeastern provinces. We recommend adopting the “smart contraction” model to promote coordinated development between population and land, capital and land, as well as ecology and land, thereby fostering sustainable development in these regions. Full article

The urban built-up land green use efficiency (UBLGUE) of the Central Plains Urban Agglomeration (CPUA) is greatly affected by the Central China Rise policy. However, studies on how socioeconomic factors affect UBLGUE in underdeveloped urban agglomerations are lacking, and little empirical research has placed particular emphasis on the Central China Rise policy. Based on the statistical data of 2003–2020, this study explores the dynamic spatial–temporal characteristics and determines the influencing mechanism of UBLGUE in the CPUA via the super-SBM–DEA method and panel regression model. The empirical results indicate the following: The average UBLGUE in the prefecture cities of the CPUA presents a significant fluctuating trend from 2003 to 2020. The UBLGUE of the CPUA is characterized by spatial imbalance. Over the period of Central China Rise, the main factors influencing the spatial–temporal differentiation of the UBLGUE in the CPUA are the economic development, industrial structure, environmental regulation intensity, and energy consumption intensity. UBLGUE has strong economic attributes and is positively promoted by economic development. In contrast, the industrial structure, environmental regulation intensity, and energy consumption intensity significantly hinder the UBLGUE. Energy consumption intensity has the strongest negative effect on UBLGUE. Finally, corresponding policy recommendations are proposed to promote UBLGUE based on the conclusions obtained. Full article

To investigate the effectiveness of water environment governance in China, this study employs the Super-SBM model to measure the WEGE (water environment governance efficiency) of 283 prefecture-level cities in China from 2013 to 2022. Multidimensional decomposition is conducted using the Dagum Gini coefficient, kernel density estimation, convergence models, and the Tobit model. The findings reveal the following: (1) China’s WEGE is generally at a low-efficiency development stage, exhibiting a pattern of “western regions > central regions > eastern regions”. WEGE evolves from “scattered distribution” to “multi-center aggregation”. (2) The overall Gini coefficient for WEGE in China is relatively low, with an average of 0.120. Intra-group differences and transvariation intensity are the primary sources of regional disparities. (3) The country and the three major regions exhibit right-tailed and multi-polar phenomena. (4) σ-convergence is observed exclusively in the eastern area, whereas both absolute and conditional β-convergence are evident throughout the country as well as within the three major regional divisions. (5) Government intervention has a significant positive impact on WEGE, while artificial intelligence, spatial agglomeration, and industrial structure upgrading exert negative effects on WEGE. Therefore, it is urgent to pay attention to the regional differences in WEGE and implement practical measures for collaborative water environment governance. Full article