Search Results (99)

Promoting green utilization of cultivated land is the key to balancing resource use and ecological capacity. However, its working mechanisms are still unclear. This study attempts to address this empirical research gap through a three-stage cyclic system (Input-State-Output). It employed the PEST framework (Politics, Economy, Society, Technology) to identify external drivers. Using advanced methods, including the Super-SBM model, Dagum Gini coefficient, and Kernel density estimation, this paper mapped the spatiotemporal drivers of China’s green utilization efficiency of cultivated land (GUECL) between 2000 and 2020. The results indicate that despite some variation, the GUECL exhibited a distinct upward tendency over the study period. Spatially, efficiency was highest in northeastern China, while eastern and western China indicated moderate efficiency, and it was the lowest in central China. Regional differences generally narrowed, with trans-variation remaining the primary source of differences. External drivers varied across regions. At the national level, fiscal support and the R&D staff reduced GUECL, while economic growth increased it. In contrast, at the regional level, environmental regulation helped in western China, while income disparity boosted it in central China. Moreover, farm size and machinery use promoted GUECL in the eastern, central, and northeastern China, while cropping intensity and farmer education had positive effects in the central and eastern regions. This study provides a scientific foundation for developing region-specific strategies to promote the green utilization of cultivated land. It provides a valuable Chinese case for global research on sustainable land use. Full article

Against the backdrop of China’s “carbon peaking” and “carbon neutrality” goals, as well as the advancement of new industrialization, the oil and gas industry is undergoing a critical transformation from resource-dependent growth toward innovation-driven, low-carbon, and high-quality development. The integrated advancement of high-end, intelligent, and green transformation—collectively referred to as the “Three Modernizations”—has become a vital pathway for promoting industrial upgrading and sustainable growth. Based on panel data from 30 Chinese provinces from 2009 to 2023, this study constructs a comprehensive evaluation index system covering 19 secondary indicators across three dimensions: high-end, intelligent, and green development. Using the entropy-weighted TOPSIS method, kernel density estimation, Dagum Gini coefficient decomposition, and σ–β convergence models, the study examines the spatiotemporal evolution, regional disparities, and convergence characteristics of HIG integration, and further explores its driving mechanisms through a two-way fixed effects model and mediation effect analysis. The results show that (1) the overall HIG integration index rose from 0.34 in 2009 to 0.46 in 2023, forming a spatial pattern of “high in the east, low in the west, stable in the center, and fluctuating in the northeast”; (2) regional disparities narrowed significantly, with the Gini coefficient declining from 0.093 to 0.058 and σ decreasing from 7.114 to 6.350; and (3) oil and gas resource endowment, policy support, technological innovation, and carbon emission constraints all positively promote integration, with regression coefficients of 0.152, 0.349, 0.263, and 0.118, respectively. Heterogeneity analysis reveals an increasing integration level from upstream to downstream, with eastern regions leading in innovation-driven development. Based on these findings, the study recommends strengthening policy and institutional support, accelerating technological innovation, improving intelligent infrastructure, deepening green and low-carbon transformation, promoting regional coordination, and establishing a long-term monitoring mechanism to advance the integrated high-quality development of China’s oil and gas industry. Overall, this study deepens the understanding of the internal logic and spatial dynamics of the “Three Modernizations” integration in China’s oil and gas industry, providing empirical evidence and policy insights for accelerating the construction of a low-carbon, secure, and efficient modern energy system. Full article

Rural revitalization relies on both industrial upgrading and cultural reinvigoration. Tea-culture–tourism integration has been regarded as a potentially effective route for advancing rural revitalization, yet its interactive relationship and dynamic evolution remain insufficiently understood. Based on provincial-level panel data from 18 major tea-producing provinces in China between 2013 and 2022, this study constructs two comprehensive evaluation index systems for tea–culture–tourism integration and rural revitalization. It employs the entropy weight method, the coupling coordination degree model, the Dagum Gini coefficient decomposition, and spatial econometric models to measure their coupling coordination degree and analyze its spatiotemporal pattern, regional disparities, and driving factors. The main findings are as follows: (1) Both tea–culture–tourism integration and rural revitalization exhibited upward trends, with the latter being consistently higher. (2) The coupling coordination degree transitioned from dissonance to coordination, spatially forming a gradient progression pattern of “coastal-river-inland”. (3) Regional disparities were primarily dominated by transvariation density and inter-regional differences. (4) Results of spatial econometric models indicated that fiscal conditions exerted a significant positive direct effect, while urban–rural social development, employment structure, and human capital generated significant positive direct and indirect effects. Full article

A precise understanding of the carbon dynamics of agricultural land use is essential for advancing China’s “dual carbon” goals and promoting sustainable rural development. Drawing on panel datasets for 31 Chinese provinces over the period 1997–2022, this study comprehensively analyzes the spatiotemporal evolution, regional disparities, and transition dynamics of agricultural carbon capture and emissions. Using a combination of the emission factor method, the Dagum Gini coefficient, kernel density estimation, and Markov chain models, the study finds that China’s total agricultural carbon capture has continued to increase, yet regional disparities are widening, with the central region leading and the northeastern region lagging. Meanwhile, agricultural carbon emissions exhibit a “strong west, weak east” spatial pattern and demonstrate a high degree of club convergence. Club convergence refers to the phenomenon where regions with similar initial levels converge to the same steady-state over the long run, while remaining persistently different from other regions. The net carbon effect exhibits a dual structure of carbon surplus zones and carbon deficit zones: 23 provinces act as carbon surplus zones, while 8 provinces are carbon deficit zones, primarily located in ecologically fragile or special-function regions. These findings highlight the spatial heterogeneity, path dependence, and policy sensitivity of carbon effects from agricultural land use. Accordingly, the study proposes differentiated policy recommendations, including region-specific carbon management strategies, the establishment of a unified agricultural carbon trading system, and the integration of technological and institutional innovations to achieve a balanced and low-carbon agricultural transformation. Full article

Understanding the multidimensional sources and key drivers of differences in green transition performance (GTP) among resource-based cities is vital for accomplishing national sustainable development objectives and facilitating regional coordination. This study proposes a “Carbon Reduction–Pollution Control–Greening–Growth” evaluation framework and utilizes the entropy method to assess the GTP of China’s resource-based cities from 2013 to 2022. The Dagum Gini coefficient and variance decomposition methods are employed to investigate the GTP differences, and the Optimal Parameters-Based Geographical Detector and the Geographically and Temporally Weighted Regression model are applied to identify the driving factors. The results indicate the following trends: (1) GTP exhibits a fluctuating upward trend, accompanied by pronounced regional imbalances. A pattern of “club convergence” is observed, with cities showing a tendency to shift positively toward adjacent types. (2) Spatial differences in GTP have widened over time, with transvariation density emerging as the dominant contributor. (3) Greening differences represent the primary structural source, with an average annual contribution exceeding 60%. (4) The impact of digital economy, the level of financial development, the degree of openness, industrial structure, and urbanization level on GTP differences declines sequentially. These factors exhibit notable spatiotemporal heterogeneity, and their interactions display nonlinear enhancement effects. Full article

Understanding the coupled and coordinated development of China’s urban and rural basic education systems is crucial for fostering their interaction and synergistic growth. Using China’s provincial panel data from 2011 to 2023, this study measures the coupled and coordinated development level of urban–rural basic education (CCD-URBE) via the entropy weight method, G1-method and coupling coordination degree model. On this basis, the Dagum Gini coefficient decomposition method, traditional and spatial Markov chain models, as well as convergence test models are employed for empirical research. The results show that: (1) During the study period, the CCD-URBE across the nation and the four major regions improves significantly. Both intra-regional and inter-regional disparities show a consistent downward trend. Inter-regional disparities are the main source of the overall disparities, and the contribution rate of transvariation density to the overall disparities exhibits the most significant increase. (2) The CCD-URBE demonstrates strong stability, as most regions tend to maintain their original CCD-URBE grades. Meanwhile, neighborhood grades moderate the local transition probability significantly. Neighborhoods with high CCD-URBE promote the upward improvement of the local CCD-URBE, while those with low CCD-URBE inhibit it. (3) The CCD-URBE across the nation and the four major regions shows obvious trends of σ-convergence, absolute β-convergence, and conditional β-convergence. The central region, which has lower CCD-URBE, exhibits higher convergence speed. Based on these findings, targeted policy implications are derived. Full article

Based on provincial panel data from 2014 to 2023, this study employs the entropy weight method to construct an indicator system for measuring the logistical resilience of regions along China’s Belt and Road Initiative (BRI). The Dagum Gini coefficient is used to analyze regional disparities in resilience levels. Furthermore, when geographical factors are integrated, spatial autocorrelation analysis via Moran’s I index is conducted on the measurement results to explain the spatial heterogeneity among variables. The results reveal several key findings: (1) During the implementation of the BRI, the logistical resilience of regions along the route has improved to varying degrees, indicating enhanced ability of the logistics industry to withstand external risks and recover from disruptions. (2) The level of regional logistical resilience exhibits a spatial pattern similar to that of logistics industry development, characterized by a gradual decline from the southeastern coastal areas toward the northwestern inland regions. (3) Logistical resilience within the study areas has increasingly significant spatial spillover effects; that is, regions with developed logistics industries positively impact surrounding areas, driving improvements in their resilience levels. The results of this study suggest a growing trend of spatial convergence in logistical resilience across these regions. Based on these results, corresponding policy recommendations are proposed to provide insights for enhancing regional logistical resilience. Full article

According to the “Five Development Concepts” of the new national development plan, the study of inclusive green development in the petroleum and gas sector (IGDPG) is crucial for enhancing production efficiency and safeguarding the environment and resources. This study constructs the IGDPG indicator system from industrial development, social opportunity equity, poverty and income inequality reduction, and green ecology dimensions, and the CRITIC Portfolio empowerment-TOPSIS method was used to measure the level of IGDPG in the eastern, central, and western regions using panel data. The Dagum Gini coefficient method was applied to analyze regional disparities and their causes, while the obstacle degree model and the Tobit model were used to identify internal and external factors of IGDPG. We found that IGDPG levels in the three regions showed fluctuating growth, and the eastern region (0.394) had much higher IGDPG levels than the central (0.337) and western (0.355) regions. The overall Gini coefficient for IGDPG is small, while inter-regional disparities are the primary source of overall disparities, and the intra-regional disparities of the three main areas exhibit a declining tendency. In terms of internal factors, social opportunity equity has been identified as the primary obstacle constraining IGDPG. Externally, factors such as industrial cluster, industrial upgrading, urbanization rate, and digital economy exhibit a facilitative effect on IGDPG, whereas environmental burdens exert an inhibitory influence. Moreover, all of these internal and external drivers demonstrate significant regional variations. Therefore, breaking regional restrictions and promoting the coordinated development of IGDPG so as to improve China’s IGDPG level as a whole is the forecasted trend. Full article

Agriculture is fundamental to food security and environmental sustainability. Advancing its holistic ecological transformation can stimulate socioeconomic progress while fostering human–nature harmony. Utilizing provincial data from mainland China (2013–2022), this research establishes a multidimensional evaluation framework across four pillars: agricultural ecology, low-carbon practices, modernization, and productivity enhancement. Through comprehensive assessment, we quantify China’s low-carbon green agriculture (LGA) development trajectory and conduct comparative regional analysis across eastern, central, and western zones. As for methods, this study employs multiple econometric approaches: LGA was quantified using the TOPSIS entropy weight method at the first step. Moreover, multidimensional spatial–temporal patterns were characterized through ArcGIS spatial analysis, Dagum Gini coefficient decomposition, Kernel density estimation, and Markov chain techniques, revealing regional disparities, evolutionary trajectories, and state transition dynamics. Last but not least, Tobit regression modeling identified driving mechanisms, informing improvement strategies derived from empirical evidence. The key findings reveal the following: 1. From 2013 to 2022, LGA in China fluctuated significantly. However, the current growth rate is basically maintained between 0% and 10%. Meanwhile, LGA in the vast majority of provinces exceeds 0.3705, indicating that LGA in China is currently in a stable growth period. 2. After 2016, the growth momentum in the central and western regions continued. The growth rate peaked in 2020, with some provinces having a growth rate exceeding 20%. Then the growth rate slowed down, and the intra-regional differences in all regions remained stable at around 0.11. 3. Inter-regional differences are the main factor causing the differences in national LGA, with contribution rates ranging from 67.14% to 74.86%. 4. LGA has the characteristic of polarization. Some regions have developed rapidly, while others have lagged behind. At the end of our ten-year study period, LGA in Yunnan, Guizhou and Shanxi was still below 0.2430, remaining in the low-level range. 5. In the long term, the possibility of improvement in LGA in various regions of China is relatively high, but there is a possibility of maintaining the status quo or “deteriorating”. Even provinces with a high level of LGA may be downgraded, with possibilities ranging from 1.69% to 4.55%. 6. The analysis of driving factors indicates that the level of economic development has a significant positive impact on the level of urban development, while the influences of urbanization, agricultural scale operation, technological input, and industrialization level on the level of urban development show significant regional heterogeneity. In summary, during the period from 2013 to 2022, although China’s LGA showed polarization and experienced ups and downs, it generally entered a period of stable growth. Among them, the inter-regional differences were the main cause of the unbalanced development across the country, but there was also a risk of stagnation and decline. Economic development was the general driving force, while other driving factors showed significant regional heterogeneity. Finally, suggestions such as differentiated development strategies, regional cooperation and resource sharing, and coordinated policy allocation were put forward for the development of LGA. This research is conducive to providing references for future LGA, offering policy inspirations for LGA in other countries and regions, and also providing new empirical results for the academic community. Full article

This study develops a four-dimensional value-assessment framework encompassing economic, innovation, social, and cultural dimensions to evaluate the multidimensional performance of family firms in China. Drawing on the entropy weighting method, we construct a composite value index for 251 A-share listed family firms from 2014 to 2023 and apply spatial statistical techniques—including Dagum Gini coefficients, Theil indices, and coefficients of variation—to examine temporal evolution and regional disparities. We further estimate explanatory panel models with firm and year fixed effects (Hausman test favoring FE) to identify the firm-level determinants of composite value. Leverage exhibits a significantly negative association with value, while firm size and innovation capacity are positively related; no significant moderating effect of technology-intensive industry is found. A robustness check using equal weights (0.25 for each dimension) yields an almost perfect correlation (0.9999) with the entropy-weighted index, confirming that the dominance of the innovation dimension in the weighting scheme does not materially affect the overall conclusions. The results highlight the importance of integrating multidimensional value perspectives into both academic research and policy design to promote balanced, inclusive, and sustainable development trajectories for family enterprises. Full article

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

Enhancing market integration levels is crucial for advancing sustainable regional collaborative development and achieving ecological protection and high-quality development goals within the Yellow River Basin, fostering a balance between economic efficiency, social equity, and environmental resilience. This study analyzed the retail price data of goods from prefecture-level cities in the Yellow River Basin from 2010 to 2022, employing the relative price method to measure the market integration index. Additionally, it examined the temporal and spatial evolution patterns and driving factors using the Dagum Gini coefficient and panel regression models. The results indicate the following. (1) The market integration index of the Yellow River Basin shows a fluctuating upward trend, with an average annual growth rate of 9.8%. The spatial pattern generally reflects a situation where the east is relatively high and the west is relatively low, as well as the south being higher than the north. (2) Regional disparities are gradually diminishing, with the overall Gini coefficient decreasing from 0.153 to 0.104. However, internal differences within the downstream and midstream areas have become prominent, and contribution rate analysis reveals that super-variable density has replaced between-group disparities as the primary source. (3) Upgrading the industrial structure and enhancing the level of economic development are the core driving forces, while financial support and digital infrastructure significantly accelerate the integration process. Conversely, the level of openness exhibits a phase-specific negative impact. We propose policy emphasizing the need to strengthen development in the upper reach of the Yellow River Basin, further improve interregional collaborative innovation mechanisms, and enhance cross-regional coordination among multicenter network nodes. 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

High-quality growth of the construction industry and an improved human settlements environment are essential to sustainable urbanization. Existing studies have paid limited systematic attention to the spatial and temporal dynamics of the coordinated development between the construction industry and human settlements, as well as the underlying factors driving regional disparities. This gap restricts the formulation of precise, differentiated sustainable policies tailored to regions at different development stages and with varying resource endowments. Southern China, characterized by pronounced spatial heterogeneity and unique development trends, offers a natural laboratory for examining the spatio-temporal interaction between these two dimensions. Using panel data for 15 southern provinces (2013–2022), we applied the entropy method, coupling coordination model, Dagum Gini coefficient, spatial trend surface analysis, gravity model, and grey forecasting to evaluate current conditions and predict future trends. The main findings are as follows. (1) The coupling coordination degree rose steadily, forming a stepped spatial pattern from the southwest through the center to the southeast. (2) The coupling coordination degree appears obvious polarization effect, presenting a spatial linkage pattern with Jiangsu-Shanghai-Zhejiang, Hubei-Hunan-Jiangxi, and Sichuan-Chongqing as the core of the three major clusters. (3) The overall Dagum Gini coefficient declined, but intra-regional disparities persisted: values were highest in the southeast, moderate in the center, and lowest in the southwest; inter-regional differences dominated the total inequality. (4) Forecasts for 2023–2027 suggest further improvement in the coupling coordination degree, yet spatial divergence will widen, creating a configuration of “eastern leadership, central catch-up acceleration, and differentiated southwestern development.” This study provides an evidence base for policies that foster high-quality construction sector growth and enhance the living environment. The findings of this study indicate that policymaking should prioritize promoting synergistic regional development, enhancing the radiating and driving role of core regions, and establishing a multi-level coordinated governance mechanism to bridge regional disparities and foster more balanced and sustainable development. Full article

The Yangtze River Economic Belt (YEB), serving as a pivotal transportation corridor connecting eastern and western China and a national strategic development hub, plays a central role in driving high-quality economic development (HQAED) across the country. Based on the new development paradigm with emphasis on green transformation and transportation integration, this study proposes a comprehensive evaluation framework for an HQAED index (HQAED) across five core dimensions. Employing the entropy-weighted CRITIC method to quantify provincial HQAED values, combined with Dagum–Gini coefficient analysis to examine regional inequality patterns and determinants, and complemented by kernel density estimation (KDE) for temporal dynamics analysis, this research reveals four key findings: (1) There are significant disparities in HQEDI levels across the YEB, with a clear east–west gradient: the lower reaches > middle reaches > upper reaches. (2) While the dimensions of green development and shared development have shown steady growth despite initial disadvantages, the openness dimension faces structural challenges that require particular attention. (3) The overall Gini coefficient fluctuates between 0.068 and 0.094, indicating moderate regional disparities with relatively limited inequality. (4) The rightward shift in the HQEDI kernel density curves confirms overall progress, but also highlights widening disparities in the upstream regions and growth stagnation in the midstream areas. Practically, the entropy–CRITIC fusion methodology offers a transferable framework for emerging economies measuring sustainability-transition progress, while the quantified “green transportation empowerment” effects provide actionable levers for policymakers to optimize ecological compensation mechanisms and cross-regional infrastructure investments. Full article