Search Results (70)

Exploring the regional disparities in and spatiotemporal evolution of the new energy vehicle promotion level (NEVPL) is essential for facilitating low-carbon and environmentally sustainable development. This study employs a multidimensional index system to assess the NEVPL across 31 Chinese provinces from 2017 to 2023, utilizing data on NEV ownership, annual NEV sales, the number of public charging piles, and the vehicle-to-pile ratio. The NEVPL scores were estimated using the Entropy-TOPSIS method. Spatial patterns and the mechanisms of regional disparities were examined using a suite of spatial analytical techniques, including the standard deviation ellipse (SDE), gravity center analysis, Dagum Gini coefficient decomposition, and kernel density estimation. The results reveal three principal findings. First, NEVPL exhibited a sustained upward trend nationwide. The eastern region consistently maintained a leading position, the central and western regions demonstrated steady growth, and the northeastern region remained underdeveloped, leading to an expanding regional gap. Second, spatial distribution transitioned from an early dispersed pattern to a structure characterized by both agglomeration and differentiation. The promotional center gradually shifted toward the southeast, and high-value regions became increasingly isolated, forming island-like clusters. Third, spatial inequality was mainly driven by inter-regional differences, which contributed to over 70 percent of the total variance. The rising intra-regional disparity within the eastern region emerged as the predominant factor widening the national gap. These findings offer empirical evidence to support the refinement of new energy vehicle (NEV) policy frameworks and the promotion of balanced regional development. Full article

The sustainable development of higher education exhibits a strong and measurable association with the level of regional innovation capacity. Drawing on panel data covering 31 provincial-level administrative regions in China from 2010 to 2022, we construct evaluation frameworks for both higher education and regional innovation capacity using the entropy weight method. These are complemented by kernel density estimation, spatial autocorrelation analysis, Dagum Gini coefficient decomposition, and the Obstacle Degree Model. Together, these tools enable a comprehensive investigation into the spatiotemporal evolution and driving mechanisms of coupling coordination dynamics between the two systems. The results indicate the following: (1) Both higher education and regional innovation capacity indices exhibit steady growth, accompanied by a clear temporal gradient differentiation. (2) The coupling coordination degree shows an overall upward trend, with significant inter-regional disparities, notably “higher in the east and low in the west”. (3) The spatial distribution of the coupling coordination degree reveals positive spatial autocorrelation, with provinces exhibiting similar levels tending to form spatial clusters, most commonly of the low–low or high–high type. (4) The spatial heterogeneity is pronounced, with inter-regional differences driving overall imbalance. (5) Key obstacles hindering regional innovation include inadequate R&D investment, limited trade openness, and weak technological development. In higher education sectors, limitations stem from insufficient social service benefits and efficiency of flow. This study recommends promoting the synchronized advancement of higher education and regional innovation through region-specific development strategies, strengthening institutional infrastructure, and accurately identifying and addressing key barriers. These efforts are essential to fostering high-quality, coordinated regional development. Full article

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

By constructing a comprehensive evaluation index system for the development level of Agricultural Machinery Socialization Services (AMSS) in China’s hilly and mountainous areas, the article adopts the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) entropy weight method to carry out a comprehensive evaluation of the development level of AMSS in China’s 17 major hilly mountainous provinces, and utilizes the obstacle degree model and the Dagum Gini coefficient decomposition method to deeply explore the developmental constraints and regional differences in characteristics. The results of the study show that the development level of AMSS in all provinces is generally on the rise, and the overall development level of the Southwest region is relatively lagging behind, with significant differences from other regions. The obstacle degree model shows that industrial development, Government funding, and farmland construction are the main factors constraining AMSS in hilly and mountainous areas, specifically, the degree of coverage of AMSS, the percentage of agricultural machinery professional cooperatives, the degree of land fragmentation, and the level of agricultural machinery extension inputs have a greater impact on the level of development of AMSS. Dagum Gini coefficient calculations show that the overall relative differences in development levels have a tendency to decrease, but the level of development of agricultural machinery socialization in the southwestern hilly and mountainous second-maturity areas is still low, with an imbalance in development within the region and a more significant gap with the development levels of other hilly and mountainous regions. Full article

The scientific evaluation of ecological total factor productivity of cultivated land use (ETFPCLU) is fundamental for advancing sustainable utilization of cultivated land resources and safeguarding national food security and ecological stability. Using the epsilon-based measure and the global Malmquist–Luenberger (EBM–GML) index, this study quantifies and decomposes ETFPCLU across China. Spatial–temporal variations and convergence patterns are systematically investigated via an analytical toolkit comprising the spatial mismatch index, Dagum’s Gini coefficient decomposition, and convergence models. The results indicate that Chinese ETFPCLU increased by an average of 2.1% per year from 2001 to 2022, primarily attributed to technical change (TC), with limited contributions from efficiency change (EC). The spatial mismatch between ETFPCLU and TC, as well as EC, is predominantly characterized by low to medium mismatch types, exhibiting a high degree of spatial distribution similarity; inter-regional differences are the main contributors to regional disparities. Furthermore, except for the central region, significant σ-convergence exists in ETFPCLU across the country and in other regions, alongside absolute β-convergence and conditional β-convergence in the four major regions. The analysis concludes that to enhance ETFPCLU, it is essential to strengthen technological innovation, synergistically improve technological efficiency, formulate ecological protection policies tailored to local conditions, and foster collaboration among regions for cultivated land protection. Full article

The digital economy, as an emerging productive force, has become a critical catalyst for economic sustainable progress. This study examines the regional disparities and origins of the digital economy, as well as its spatial and temporal growth patterns, which are essential for bridging the financial gap among regions and promoting synchronized economic progress. We developed a multidimensional index system to evaluate the level of digital economic development across 30 Chinese provinces, encompassing aspects such as the Internet’s evolution, digital infrastructure, capacity for digital innovation, and the application of digital technologies. The regional imbalances and origins of the digital economy were scrutinized using Dagum Gini coefficient decomposition. Furthermore, the study investigated the spatiotemporal dynamics of digital economy progression in China, employing methods like kernel density estimation, migration models of the gravity center, and an analysis via the standard deviation ellipse. The results reveal the following: (1) Digital economic development is more advanced in Eastern China compared to the western regions, with variations primarily driven by inter-regional differences. (2) The absolute gap in national digital economic development levels is widening, and relative disparities within the eastern region are increasing. Significant polarization is observed in the development of the digital economy across the central and western regions, while disparities in the northeastern region are comparatively minimal. (3) The center of gravity for China’s digital economy has overall shifted southward; the standard deviation ellipse has extended both northward and southward and become more oblate; and the dispersion within China’s digital economy has intensified. 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

Exploring the law and evolution mechanism of coupling and coordination between agricultural carbon emission efficiency (ACE) and agricultural economic growth (AEG) can provide a reference basis for agricultural low-carbon transformation. This study takes 11 cities in Jiangxi Province as the research object; measures the level of ACE based on the panel data from 2008 to 2022; and analyzes the development and influencing factors of the coupling and coordination between ACE and AEG by using the coupling coordination degree model, the Dagum Gini coefficient decomposition method, and the Tobit regression model. The results reveal the following: (1) The overall ACE in Jiangxi Province displays a significant upward trend, with the average efficiency value increasing from 0.172 to 0.624, reflecting an average annual growth rate of 72.43%. Nonetheless, there remains clear regional heterogeneity, characterized by lower efficiencies in Central and Southern Jiangxi compared to the higher efficiencies found in Northern and Western Jiangxi. (2) Despite gradual improvements in regional coordination, the Central and Southern Jiangxi regions still lag Northern and Western Jiangxi in terms of the linked coordination between ACE and AEG, symptoms of which had been previously misaligned. (3) The results of Dagum’s Gini coefficient decomposition show that inter-regional disparities are the main source of overall disparities, with a contribution of 37.43%, which is higher than the synergistic effect of intra-regional disparities and hyper-variable densities, corroborating the core contradiction of uneven development across regions. (4) The Tobit model reveals that government investment, industrial structure optimization, urbanization, and educational attainment exert a significant positive influence on promoting coupling coordination. To establish a scientific basis for achieving a low-carbon agricultural transformation and equitable AEG in Jiangxi Province, this research recommends bolstering regional cooperation, fostering innovations in agricultural science and technology, optimizing the industrial structure, and enhancing farmers’ awareness of low-carbon practices. This study expands the theoretical system of agricultural low-carbon transition in terms of research methods and scales to provide a scientific basis for agricultural provinces to realize agricultural low-carbon transition and balanced economic development. Full article

Green technological innovation, as a critical emerging resource element, is instrumental in advancing sustainable and high-quality development of the construction sector. However, despite extensive research, the synergistic mechanism linking regional green technology innovation (RGTI) and carbon reduction in the construction industry (CRCI) remains theoretically underexplored, especially through the lens of new quality productivity (NQP). Based on dynamic panel data from 30 Chinese provinces spanning 2013–2021, this study employed multiple analytical approaches, including econometric models, coupling coordination models, kernel density estimation, and Dagum Gini coefficient decomposition, to systematically examine their interactive relationships and spatiotemporal evolution characteristics. The findings reveal that RGTI directly reduces the carbon emissions intensity of the construction industry and yields a “dual-driving effect” through the mediating role of NQP. Significant coupling coordination effects were identified among RGTI, NQP, and CRCI. Further investigation showed that their synergistic evolution manifests distinct “regional lock-in effects” and “polarization effects”, with eastern regions achieving positive interactions, while central and western regions remain constrained by developmental limitations. Although overall disparities narrowed during the study period, inter-regional differences persisted as the dominant factor. This study extends the research perspective on construction industry carbon reduction, contributing to new quality productivity formation and inter-regional emission reduction coordination. Full article

Against the backdrop of the global digital wave and the “dual carbon” goals, the coordinated development of new-quality productivity and digital transformation has emerged as a critical engine for high-quality economic growth. This study constructs an evaluation system for new-quality productivity incorporating 20 indicators, including green innovation and digital infrastructure, and a 17-indicator system for digital transformation. Using the entropy method, modified coupling coordination model, and Dagum Gini coefficient, the spatiotemporal coupling characteristics of 31 provinces in China from 2011 to 2023 are systematically analyzed. The findings reveal a gradient distribution of coupling coordination degree, with higher levels in the East and lower in the West. The Eastern region forms a “technology-ecology” dual-driven model through digital innovation and environmental protection investment, while Central and Western regions face dual constraints of lagging digital infrastructure and insufficient pollution control capacity. Difference decomposition shows that inter-regional disparities contribute 64–70% to overall differences, with green technology innovation and digital infrastructure efficiency identified as core influencing factors. This study proposes a differentiated coordination mechanism of “eastern leadership-central rise-western revitalization”, aiming to promote a sustainable development pattern integrating digital empowerment and ecological protection through improving cross-regional digital infrastructure networks, innovating market-based factor allocation, and establishing green technology sharing platforms. Full article

The integration of the agricultural product market is of great significance to reducing price fluctuations and improving social welfare. In this study, we employ the relative price method to measure the integration of the agricultural product market in 31 Chinese provinces from 2003 to 2022. We use the Dagum–Gini coefficient and its decomposition and the σ convergence and β convergence models to analyze regional variations, time trends, and convergence. It is found that the degree of integration of the Chinese agricultural product market did not increase continuously but fluctuated with increasing intensity. The spatial differentiation degree of agricultural market integration fluctuated. The integration degree of the agricultural product market has σ convergence, absolute β convergence, and conditional β convergence. The marginal contribution of this study is the systematic analysis of the dynamic evolution and convergence of the integration of the Chinese agricultural product market. In order to improve the integration degree of the agricultural product market, in this paper, we put forward policy suggestions from three aspects: strengthening policy support, optimizing resource allocation, and building agricultural product market information centers. Full article

Based on the panel data of 30 provinces in China from 2013 to 2022, this paper constructs a measurement index system for the symbiotic level of digital innovation ecosystems from three dimensions: the symbiosis of digital innovation subjects, the digital innovation environment, and digital innovation interaction. This paper applies the entropy weight TOPSIS method, Dagum Gini coefficient decomposition, and spatial convergence analysis to empirically examine the symbiotic levels, regional disparities, and spatial convergence of China’s digital innovation ecosystem. The results are as follows: (i) At the national level, the symbiotic level of China’s digital innovation ecosystem has generally increased, creating a spatial distribution pattern that is “high in the east, flat in the middle, and low in the west”. (ii) From a regional perspective, the major disparities between regions are the primary factors contributing to the overall difference in the symbiotic level of China’s digital innovation ecosystem. (iii) From the perspective of σ convergence, regional disparities in the symbiotic level of the digital innovation ecosystem are constantly expanding, and uneven regional development is intensifying. (iv) From the perspective of absolute β convergence, regions with lower levels of symbiosis in the digital innovation ecosystem have a faster growth rate of symbiosis than regions with higher levels of symbiosis, and there is a certain spatial spillover effect. (v) From the perspective of conditional β convergence, economic structure and innovation application can accelerate the spatial convergence of China’s digital innovation ecosystem symbiosis to a certain extent. Full article

In the dual-carbon context, forestry green total factor productivity (FGTFP) serves as a key indicator of the quality and efficiency of forestry development. Based on New Economic Geography Theory, this study explores FGTFP and its spatial divergence under the constraint of carbon emissions. We analyzed panel data from 30 Chinese provinces between 2004 and 2022. The Directional Distance Function (DDF) model was applied to measure FGTFP, and the Global Malmquist–Luenberger (GML) model was applied to measure FGTFP’s decomposition index. The Dagum Gini coefficient was employed to analyze the degree of spatial divergence of FGTFP and identify its sources. Using Porter’s model and Sustainable Development Theory, the geo-detector was applied to examine the driving factors of FGTFP and its decomposition index. The study’s findings indicate that (1) FGTFP in China generally trended upward from 2004 to 2022, with significant heterogeneity observed at both interprovincial and regional levels; (2) Technological Improvement (TI) was the primary driver of FGTFP growth in the eastern, northeastern and central regions, while Efficiency Change (EC) was the key driver in the western region; (3) FGTFP exhibited distinct spatial divergence patterns in China, with hypervariable density as the primary source, followed by interregional differentiation, and regional differentiation contributing the least; and (4) green energy transition factors consistently showed a significant “two-factor enhancement effect” and a “non-linear enhancement trend”, while external environmental factors exhibited strong interaction effects but demonstrated a “non-linear weakening trend”. Therefore, it is essential to promote the green transformation of production modes, facilitate structural adjustments and upgrades in the forestry industry, enhance regional collaboration, and advance the “dual enhancement” of technological progress and efficiency. Additionally, leveraging regional comparative advantages will promote coordinated development. Full article

As one of the major sources of carbon emissions, the significant spatial disparities in agricultural carbon emissions (ACE) pose a serious challenge to coordinated regional carbon reduction efforts. In order to precisely identify the sources of these ACE differences, this study estimates the ACE of China from 2005 to 2020 across four main emission sources and applies the bidimensional decomposition method of the Gini coefficient to measure and decompose their spatial disparities. Finally, the key factors driving ACE disparities are analyzed using the Quadratic Assignment Procedure (QAP). The results show that China’s total ACE initially declined, followed by an upward trend over the study period. Spatially, emissions were higher in eastern regions compared to western regions, and higher in southern regions compared to northern regions. The differences in paddy field emissions between the central and western regions were identified as the primary contributor to east–west disparities, while differences in agricultural materials emissions between northern and southern regions were the dominant source of north–south disparities. Furthermore, regional differences in agricultural development levels and mechanization capacity were found to be the strongest drivers of spatial ACE disparities. This study provides empirical evidence for formulating region-specific and source-targeted carbon reduction policies. Our findings highlight the importance of addressing regional imbalances, particularly in paddy field management and agricultural material usage, to promote more coordinated and sustainable agricultural carbon reduction across China. Full article

Understanding the efficiency of agricultural eco-product value realization is critical for sustainable development and regional equity. Here, we present a comprehensive analysis of the spatiotemporal patterns and regional disparities in the value realization efficiency of agricultural ecological products across China’s 31 provinces from 2010 to 2022. Utilizing an advanced Super-NSBM model, we quantify three dimensions of efficiency: overall value realization, economic value conversion, and social welfare value realization. Spatial mapping and dynamic evolution analysis are conducted through Dagum Gini coefficient decomposition and conditional kernel density estimation. Our results reveal three key insights: (1) China’s agricultural eco-product value realization efficiency remains suboptimal, with a gradual upward trend. Economic value conversion outperforms social welfare value realization, which exhibits significant regional heterogeneity. A distinct east–west gradient is observed, with Western regions demonstrating notable progress despite initial inefficiencies. (2) Inter-regional disparities are narrowing, particularly between Eastern and Central regions. While polarization in Northeast China has diminished, Western regions show widening efficiency gaps and emerging polarization trends. (3) Regional differences are predominantly driven by inter-group disparities, with Eastern China exhibiting the lowest intra-regional variability. Cross-regional differences follow a U-shaped trajectory, decreasing initially before rebounding in recent years. These findings provide a robust empirical foundation for optimizing regional strategies in ecological product value conversion and offer critical insights for addressing spatial inequities in sustainable agricultural development. Full article