Search Results (687)

The pharmaceutical manufacturing industry in China is undergoing a critical transition toward high-quality development, making a systematic assessment of its Development Quality of the Pharmaceutical manufacturing industry (DQPI) essential for evidence-based policy formulation. However, a comprehensive evaluation system incorporating the dimensions of open and green development, as well as a spatiotemporal evolution analysis, remains underdeveloped. To address these gaps, this study develops a five-dimensional evaluation system for DQPI comprising industrial scale, economic benefits, innovation, open development, and green development. Using data from 2011 to 2023 at three spatial scales (national, regional, and provincial), this study applies entropy weight method, coupling coordination degree model, regional differences analysis, and spatial autocorrelation analysis to conduct a multidimensional evaluation and spatiotemporal evolution analysis. The results indicate a significant upward trend in China’s DQPI at the national level, with innovation being the primary driver. However, economic benefits act as a key constraint, and green development has recently declined. Spatially, inter-regional differences emerge as the primary source of overall differences, manifesting as a distinct east–west gradient pattern and a core-periphery structure characterized by high-high and low-low clusters. This study uncovers the key structural challenges: an efficiency-profitability paradox within the innovation-to-benefit transformation, and intensifying regional divergence. To address these, it proposes a synergistic ‘Core Leadership–Periphery Breakthrough’ governance framework, informing the transition of the pharmaceutical manufacturing industry toward high-quality and sustainable development. Full article

Understanding the spatiotemporal evolution of forest biomass energy potential is essential for supporting low-carbon land-use planning and regional energy transitions. China, characterized by pronounced spatial heterogeneity in forest resources and ecological conditions, provides an ideal case for examining how biophysical endowments and management factors shape biomass energy potential. This study constructs a province-level panel dataset for China covering the period from 1998 to 2018 and investigates long-term spatial patterns, regional disparities, and driving mechanisms using spatial visualization, Dagum Gini decomposition, and fixed-effects estimation. The results reveal a gradual spatial reorganization of forest biomass energy potential, with the national center of gravity shifting westward and northwestward, alongside a moderate dispersion of high-potential clusters from coastal areas toward the interior. Interregional transvariation is identified as the dominant source of regional inequality, indicating persistent structural differences among major regions. To explore future dynamics, a random forest model is employed to project provincial forest biomass energy potential from 2018 to 2028. The projections suggest moderate overall growth, smoother distributional structures, and a partial reduction in extreme provincial disparities. Central, southwestern, and northwestern provinces are expected to emerge as important contributors to future growth, reflecting ecological restoration efforts, expanding plantation forests, and improved forest management. The findings highlight a continued upward trend in national forest biomass energy potential, accompanied by a spatial shift toward inland regions and evolving regional disparities. This study provides empirical evidence to support region-specific development strategies, optimized spatial allocation of forest biomass resources, and integrated policies linking ecological sustainability with renewable energy development. Full article

Miniature commercial trucks constitute a critical component of urban freight systems but face elevated crash risk due to distinctive driving patterns, frequent operation, and variable loads. This study quantifies how long-term and short-term driving behaviors jointly shape crash economic loss levels and identifies factors most strongly associated with severe claims. A driver-level dataset linking multi-source running behavior indicators, vehicle attributes, and insurance claims is constructed, and an enhanced Wasserstein generative adversarial network with Euclidean distance is employed to synthesize minority crash samples and alleviate class imbalance. Crash economic loss levels are modeled using a random-effects generalized ordinal logit specification, and model performance is compared with a generalized ordered logit benchmark. Marginal effects analysis is used to evaluate the influence of pre-collision driving states (straight, turning, reversing, rolling, following closely) and key behavioral indicators. Results indicate significant effects of inter-provincial duration and count ratios, morning and empty-trip frequencies, no-claim discount coefficients, and vehicle age on crash economic loss, with prolonged speeding duration and fatigued mileage associated with major losses, whereas frequent speeding and fatigue episodes are primarily linked to minor claims. These findings clarify causal patterns for miniature commercial truck crashes with different economic losses and provide an empirical basis for targeted safety interventions and refined insurance pricing. Full article

Emergency supplies policies are a key component of regional risk governance, yet their design coherence has received limited systematic examination. Focusing on the Yangtze River Delta (YRD), this study conducts a design-oriented evaluation of emergency supplies policy design by integrating policy text mining with the Policy Modeling Consistency (PMC) index model. Based on a corpus of 212 emergency supplies–related policy documents, the study first examines the structural features and thematic emphases of the regional policy system and constructs a PMC-based evaluation framework within a mission–structure–mechanism perspective. On this basis, 16 provincial- and municipal-level policies issued between 2019 and 2023 are identified as core, system-defining policy texts and subjected to in-depth PMC evaluation. The results indicate that the evaluated core emergency supplies policies exhibit an overall “good” level of design coherence. Mission-oriented dimensions, including normative orientation and policy objectives, are generally well articulated, whereas mechanism-oriented dimensions—particularly linkage response and allocation arrangements—are specified less consistently. Observed interjurisdictional differences reflect institutional roles and governance traditions rather than variations in administrative capacity. By shifting analytical attention from implementation outcomes to design-stage coherence in core policy texts, this study provides a structured diagnostic approach for assessing emergency supplies policy design and offers insights for strengthening regional coordination and institutional resilience. Full article

Historical cropland reconstruction is crucial for modeling long-term agricultural dynamics and assessing their climatic and ecosystem impacts, while also providing critical regional benchmarks for improving global land-use datasets. This study presents a millennium-long reconstruction of cropland area at the provincial level for the Korean Peninsula by integrating multi-source historical cropland records, land surveys, and modern statistical and remote-sensing-based data. Then, a land suitability model for cultivation and a spatial allocation model were developed by incorporating topographic, climatic, and soil variables to generate 10 km resolution gridded cropland data over the past millennium. Our analysis revealed a long-term increasing trend in cropland area at the provincial level over the past millennium, with significant spatial and temporal variations. Spatially, cropland was primarily distributed in western coastal areas, with historical southward expansion. After the peninsula’s division, trends diverged, with continued growth in the north Korea but a decrease in the south Korea by 2000. The spatial allocation model validation results show strong spatial and quantitative agreement between the reconstructed historical cropland and the remote-sensing-based data, with 72.12% of grids differing by less than ±20%. This high consistency confirms the feasibility of the applied reconstruction method. Full article

In the context of open innovation, innovation cooperation has become an important path to strengthen the resilience of urban economics. This study aims to explore how different innovation cooperation patterns impact urban economic resilience by utilizing panel data from 280 Chinese cities from 2010 to 2020. The results show that intra-provincial buzz has a nonlinear relationship with economic resilience, while the inter-provincial pipeline consistently enhances that resilience. Furthermore, intra-provincial buzz primarily promotes economic resilience by improving the technology agglomeration level, while the inter-provincial pipeline achieves the same by fostering innovation and entrepreneurship vitality. Further analysis reveals heterogeneous effects across geographic locations, city sizes, and levels of industrial diversification. These findings highlight the complex impacts of two innovation cooperation patterns on urban economic resilience, underscoring the requirement for strategies tailored to specific situations depending on geographic and economic contexts. Full article

Exploring the impact of cultivated land transfer on grain green total factor productivity is of great significance in promoting efficient and low-carbon utilization of arable land and green and high-quality development of grain production in China. Based on the panel data of 30 provincial-level administrative regions in China from 2006 to 2022, this study employed the EBM model, Tobit model and mediation effect model to measure grain green total factor productivity across provinces, analyze its spatiotemporal evolution trends, and explore the influence and mechanisms of cultivated land transfer on the grain green total factor productivity. The findings revealed that: (i) The overall level of China’s grain green total factor productivity was relatively low, though it exhibited some improvement and regional differences during the sample period, with the highest level in grain-producing areas, followed by production-marketing balance areas, and the lowest level in grain-marketing areas. (ii) Cultivated land transfer had a significant positive impact on grain green total factor productivity. However, an excessively large scale of transferred cultivated land may also inhibit efficiency improvements. (iii) The impact of cultivated land transfer on grain green total factor productivity showed notable regional heterogeneity. In terms of coefficient magnitude, the impact was greater in production-marketing balance areas than in grain-producing areas, while it was not significant in major grain-marketing areas. The effect was stronger in the western region compared to the eastern and central regions. (iv) Cultivated land transfer could improve grain green total factor productivity through large-scale management of cultivated land, large-scale management of services and green production technology. Further analysis indicated a synergistic interaction between scale management and technological progress in green production within these pathways. To enhance grain green total factor productivity, it is essential to implement region-specific policies for cultivated land transfer and scale operations that account for local geographical and agricultural conditions. Specifically, policymakers should facilitate the integration of land scale management with service scale operation, while simultaneously promoting the coordinated advancement of scale operation and green production technology. Full article

Against the backdrop of China’s transition from the eradication of absolute poverty toward the pursuit of common prosperity, equitable access to energy has become an increasingly important policy concern. This study develops a multidimensional framework to assess energy poverty from three interrelated dimensions: energy use level, energy structure, and energy capability. Using panel data for 30 provincial-level regions from 2005 to 2020, a provincial energy poverty index (EPI) is constructed based on the entropy-weighting approach. The spatial and temporal dynamics of energy poverty are examined using Moran’s I, the Dagum Gini decomposition, kernel density estimation, and spatial Markov chain analysis. The results reveal several key patterns. (1) Although energy poverty has declined nationwide, it remains pronounced in parts of western, central, and northeastern China. (2) Energy poverty exhibits significant spatial clustering, with high-poverty clusters concentrated in resource-dependent regions such as Shanxi and Inner Mongolia, while low-poverty clusters are mainly located along the eastern coast. (3) Regional disparities follow an inverted U-shaped trajectory over time, with east–west differences constituting the primary source of overall inequality. (4) Moreover, the evolution of energy poverty displays strong path dependence and club convergence. These findings highlight the need to strengthen dynamic monitoring and governance mechanisms, promote region-specific clean energy development, and enhance cross-regional coordination to support energy security and green transformation under China’s “dual-carbon” objectives. Full article

This study employs Gaussian kernel principal component analysis to construct a composite indicator of environmental behavior willingness from nine dimensions. Using multiple categorical ordered linear regression models and their interaction models, it examines the differential influence mechanisms of social strata (economic status, education, social prestige) and environmental perception from gender, inter-provincial, and regional perspectives. Key empirical findings are the following: (1) Environmental willingness formed within the same social stratum based on shared perception levels shows consistent characteristics, with no significant gender differences observed. (2) Higher education deepens understanding of environmental policies, promoting the shift from awareness to willingness. However, it also enhances recognition of environmental complexity, which may foster a situational sense of powerlessness, often channeled into systemic advocacy rather than the belief that individual actions are insignificant. (3) Regional disparities are evident. For example, the perception of air pollution positively correlates with willingness in Hebei and Jiangsu but negatively in Beijing and Liaoning. (4) The middle social stratum in eastern and central regions shows more stimulable environmental willingness, contributing to sustainable regional environmental engagement. Conversely, in the western region, improving the economic status of lower- and middle-stratum residents is key to significantly enhancing the sustainability of overall regional willingness. This study reveals the varied drivers of environmental willingness by integrating multidimensional indicators and a social-class perspective, highlighting the regional role of environmental perception and advancing theory on socio-cognitive interactions in environmental sociology. Practically, it provides evidence for differentiated policy design, suggesting tailored incentives across social strata and regions, including measures to address “action paralysis” among the highly educated and to combine economic support in western China for fostering sustainable public environmental participation. Full article

Rural revitalization constitutes a vital strategic initiative in advancing China’s socialist modernization. At the 2023 Central Economic Work Conference, the objective of building China into a financial powerhouse was formally articulated, thereby establishing higher benchmarks for financial support of rural revitalization. A critical question arising from this agenda is how to simultaneously advance agricultural technological innovation while effectively implementing green development principles. Accordingly, it is essential to investigate the role of the integrated development of sci-tech finance and green finance in promoting rural revitalization. Against this backdrop, this study employs provincial-level panel data from China spanning the period from 2011 to 2021. A two-way fixed effects model is adopted to examine the impact of the integrated development of sci-tech finance and green finance on rural revitalization. The analysis identifies three primary transmission mechanisms: financial supply, green agricultural development, and linkages between smallholder farmers and modern agriculture. Furthermore, the study explores heterogeneity across different financial environments from two dimensions: the level of digital inclusive finance development and the intensity of financial regulation. The empirical results indicate that (1) the integrated development of sci-tech finance and green finance significantly promotes rural revitalization, exhibiting a nonlinear effect whereby its catalytic impact intensifies markedly once the coupling coordination between the two surpasses a critical threshold; (2) such integration alleviates rural financing constraints, enhances agricultural green total factor productivity, and facilitates rural revitalization through the establishment of green agricultural cooperatives; and (3) the enhanced impact of this holistic progress is particularly noticeable in areas with advanced digital financial inclusion and robust financial oversight. In light of these results, this research puts forth three policy suggestions. First, institutional and policy preparations for integrating green finance and sci-tech finance should be accelerated through coordinated government policies, financial product innovation, and financial market reforms. Second, the channels through which sci-tech finance and green finance support rural revitalization should be strengthened by expanding agricultural credit, improving the coverage of rural financial institutions, and fostering specialized green agricultural cooperatives. Third, the financial ecosystem should be optimized by prioritizing investment in digital infrastructure and reinforcing financial supervision throughout the development of digital inclusive finance, particularly in rural regions. Full article

The water footprint of grain crop production is a key indicator for assessing agricultural water stress and resource-use efficiency. This study analyzes the dynamic evolution, convergence characteristics, and driving forces of water footprints for major grain crops in China’s primary producing regions from 2011 to 2022. The results show the following: (1) Total water footprints are mainly driven by blue and green water components, while grey water contributes relatively little, and the total footprint follows a fluctuating pattern of “decline–increase–decline–increase–decline.” Rice exhibits the highest water footprint, with an average annual value of 59.8251 million m³, whereas beans and tubers show much lower levels, each with an average annual footprint below 20 million m³. Grey water footprints for all grain crops have declined significantly since 2018, with reductions exceeding 10% by 2022. (2) Significant absolute convergence is observed across provinces, with the absolute convergence rate ultimately approaching 0.1, indicating that inter-provincial differences in water footprints are narrowing and that high-footprint regions are improving more rapidly toward lower-footprint regions. (3) Conditional convergence is also confirmed, with the conditional convergence rate approaching 0.2, suggesting that provinces converge toward their own steady-state levels, though convergence speeds are influenced by heterogeneous factors such as economic development, technological progress, and population size. (4) Generalised Divisia Index Method (GDIM) decomposition reveals that per capita agricultural GDP and mechanization intensity are the core drivers of changes in water footprints, and their synergistic effects produce an amplification impact, with cumulative contributions exceeding 100%. The findings provide important policy implications for optimizing water resource management and promoting sustainable agricultural development in China’s major grain-producing areas. Full article

Financial supply side structural reform (FSSR) serves as a key for advancing the low-carbon transformation of industrial energy (LTIE) and supporting the dual carbon strategic goals. By using provincial panel data from China for the period of 2008–2022 and leveraging the national financial comprehensive reform pilot zones as a quasi-natural experiment, this study uses the difference-in-differences method to examine empirically the effect of FSSR on the LTIE and the underlying mechanisms. Research findings indicate that, first, FSSR can significantly advance the LTIE, which remained unchanged after other policies, omitted variables, and other potential influencing factors were controlled. Second, the mechanism tests indicate that FSSR can drive the LTIE by increasing green financial support, fostering green industrial development, and promoting green technological innovation. Third, the heterogeneity tests reveal that the benchmark effect is pronounced in regions with weak environmental regulation and a low level of financial development. This study provides theoretical and empirical evidence to understand the crucial role of FSSR in advancing the LTIE and insights for relevant policy formulation. Full article

This study investigates how skilled labor influences the development of the secondary sector in emerging economies, using China as a case study. We focus on the transitional process in which manufacturing growth shifts from labor-intensive expansion toward productivity-driven industrial upgrading. Using provincial-level data from 2000 to 2023, we evaluate the role of skilled labor across different stages of development by applying fixed-effects panel regressions, a difference-in-differences framework, and multiple robustness checks. Our findings reveal that skilled labor does not significantly contribute to secondary sector performance in the early phase, when growth relies primarily on low labor costs and rapid urbanization. However, once regions accumulate sufficient economic capacity and technological readiness, skilled labor becomes an important driver of value added and export performance. Stricter environmental policies further widen regional differences: developed regions benefit from green upgrading supported by skilled workers, while less developed regions face firm exits and weakening industrial output. These results highlight the importance of aligning human capital investments with industrial and environmental policies to promote more balanced and sustainable economic development in emerging markets. Full article

The social sustainability of Public–Private Partnerships (PPPs) emphasizes that PPP investment should meet local residents’ public service requirements. However, due to profit seeking, the private sectors in PPPs may ignore public requirements, which leads to the distribution of PPP investment in infrastructure sectors away from social sustainability. However, the evaluation of PPPs’ investment distribution with consideration for the public requirements has not received sufficient attention. Meanwhile, the underlying influencing factors also remain unexplored. Based on the priorities of public requirements, this study evaluated PPPs’ social sustainability effects (PPPSEs) to analyze whether the distribution of PPP investment in infrastructure sectors matches these priorities. Furthermore, this study empirically analyzed the factors that influence PPPSEs. This study used the data from China’s 28 provincial-level regions from 2017 to 2021. The results indicate that the PPPSEs vary across different regions in China. Regarding the influencing factors, the purchasing power of local residents, fiscal pressure, and PPP project experience significantly influenced the PPPSEs. This study supports decision making in choosing PPP projects and managing the PPP mode from the perspective of social sustainability. Full article

Comprehending the spatial–temporal transformation of urban resilience (UR) is fundamental for promoting sustainable urban growth in the Chinese context. In this study, a multi-dimensional index framework is developed to cover economic, social, ecological, and infrastructural aspects of resilience, assessing urban resilience across 282 prefecture-level cities between 2005 and 2022. By integrating the Time-Varying Entropy Method (TEM) with the Two-Stage Nested Theil Index (TNTI), we quantify the intensity and origins of spatial disparities in UR. Furthermore, spatial econometric models are employed to examine β convergence across regional and temporal dimensions. Additionally, the research adopts an Optimal Parameter-based Geographical Detector (OPGD) approach to explore and quantify the major determinants affecting urban resilience. The results reveal that (1) UR has significantly improved nationwide, with higher levels concentrated in eastern and southern China; (2) intra-provincial disparities are the dominant source of spatial differences, and continue to expand; (3) UR shows robust β-convergence nationally and regionally, although σ-convergence is limited to specific periods; (4) savings deposits per capita, ratio of employees, per capita fiscal expenditure and market size are identified as the core factors driving UR. The findings offer new insights into urban spatial governance under multi-dimensional constraints and challenges and serve as empirical guidance for narrowing resilience gaps and promoting balanced regional development. Full article