The green assessment policy integrates the effectiveness of environmental governance with traditional GDP assessment, which is an important lever for the government to promote sustainable economic growth. Whether a green assessment policy can break the "carbon curse" effect of resource-based cities is an urgent research question. Existing research has laid the theoretical foundation for analyzing the intrinsic relationship between green assessment policies and the "carbon curse" of resource-based cities. However, resource-based cities are unique in terms of dominant resources and development stages, and the underlying mechanism of the "carbon curse" breaking effect requires further exploration. Therefore, this study focuses on resource-based cities in China and aims to explore new paths for resource-based cities to break through the "carbon curse" development dilemma within the context of green assessment policy implementation. At the theoretical level, an attempt is made to incorporate green assessment policies into the analytical framework of the "carbon curse" breaking mechanism, clarifying the mechanism of action of green assessment policies. At the empirical level, by collecting and calculating energy-saving and emission reduction target assessment data as a proxy for green assessment policies and using variable coefficient, mediation effect, and spatial Durbin models, this study examines the effect of green assessment policies on breaking the "carbon curse" of resource-based cities. This study draws the following research conclusions: (1) A "carbon curse" effect existed in resource-based cities in China, where the degree of impact of the "carbon curse" on mature, growing, and declining cities decreased in order, and the impact on oil and gas-, coal-, and metal-based cities also showed a decreasing trend in order. (2) Green assessment policies could effectively reduce the carbon emission intensity of resource-based cities, which is conducive to unleashing their "carbon curse" breaking effects. This conclusion held true after a series of robustness tests. (3) The breaking effect of green assessment policies was achieved by enhancing the environmental attention of local governments, driving green technological progress, and promoting the optimization of production factor allocation. (4) The breaking effect of green assessment policies exhibited heterogeneity, particularly evident in declining, coal-based, and southern resource-based cities; the green assessment policy has a spatial "local neighbor" spillover effect. The green assessment policy not only significantly reduced the local carbon emission intensity but also had a breaking effect on the "carbon curse" of surrounding resource-based cities through spatial spillover effects. Based on the research findings, this study suggests three policy implications: (1) At the central level, we should focus on the long-term and construct a targeted green assessment policy system to break the "carbon curse" according to local conditions. (2) The transmission effect of local government's attention to environmental protection, green technology progress, and optimized allocation of production factors should be enhanced. (3) Attention should be paid to the spatial spillover effects of green assessment policies, and a new pattern of green and low-carbon coordinated development should be constructed. Overall, this study empirically tests the existence and heterogeneity of the "carbon curse" effect in China's resource-based cities and examines the breaking effect of green assessment policies on this "carbon curse." This assists in comprehensively understanding the effects of green assessment policies, providing decision-making references for refining policy intervention priorities and improving targeting and implementation efficiency.
Armed conflicts in the India-Pakistan region are a core security issue in South Asia, affecting the stability and security of China’s southwestern border and posing a threat to the implementation of the Belt and Road Initiative in the region. Studying this conflict is necessary not only to secure peace, stability, security, and development in China’s southwestern border areas, but also as an important practical step in China’s engagement in global security governance and its efforts to promote the building of a community with a shared future for humankind. These examinations hold significant geostrategic, security, economic, and diplomatic implications for China. Spatiotemporal patterns represent a key focus of geographical inquiry, yet existing research has devoted insufficient attention to the characteristics of the temporal evolution of conflicts. This study systematically analyses the temporal characteristics, cyclical patterns, and self-exciting and decay effects of the evolution of armed conflicts in the India-Pakistan region between 1989 and 2025. It conducts its investigation based on five key dimensions, as follows: conflict between the Indian and Pakistani governments; conflict between the Indian government and armed groups; conflict between the Pakistani government and armed groups; conflict between armed groups; one-sided violence. The results indicate that, first, different types of conflicts exhibit significant differences in their evolutionary stages and characteristics, which in turn are reflected in the number of phases, intensity levels, and developmental trends. Second, weekly periodic effects are not evident, whereas monthly and quarterly periodic effects are pronounced. Monthly peaks are concentrated from May to October, and quarterly peaks are concentrated in the second and third quarters (troughs occurr in December and the first quarter, respectively). The periodic effects explain the existence of temporal dependence. Third, the self-exciting effect is present in all five categories of conflict but exhibits heterogeneity, with the probability of a conflict recurring rising markedly within a short period after an initial outbreak. The self-exciting effect serves as the primary driver of conflict between the Indian and Pakistani governments, among armed groups, and between the Pakistani government and armed groups. Although these effects are also present in one-sided violence, their contributions remain relatively limited, and such violence is still more influenced by historical factors. Fourth, the self-exciting effect exhibits a robust net impact, reflecting genuine temporal dependence among conflict events rather than being driven by hot months or commemorative dates. Except for one-sided violence, hot months generally increase conflict intensity. Political festivals have a more pronounced influence than celebratory festivals do. This study advances the literature by moving from descriptive analysis to mechanistic analysis, quantifying conflict dynamics, and comparing conflict types to support targeted interventions. Future research may (1) refine covariate specifications to improve model accuracy and explanatory power; (2) analyze, from a temporal perspective, the evolution from conflict to negotiation and trigger effects; (3) incorporate a spatial dimension to capture the heterogeneity and geographical diffusion patterns of conflicts; (4) compare the goodness-of-fit of different decay kernels; (5) further explore mutual excitation effects in India-Pakistan conflicts.
The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has been positioned in the national strategy as an international science and technology innovation center. As innovation resources are unevenly distributed across the 11 cities, technology transfer has become a key channel through which cities acquire external technology, break path dependence and technological lock-in, and upgrade their industrial structures. However, existing studies have paid more attention to the volume of technology transfer than to its direction; thus, the spatiotemporal evolution and driving mechanisms of the directed technology transfer network in GBA remain insufficiently understood. To fill this gap, this study constructed a directed, weighted technology transfer network for the eleven GBA cities from the perspective of the "space of flows." Based on invention patent transfer records from 2005 to 2024, together with statistical data from provincial and municipal yearbooks, this study employed social network analysis (network density, hierarchical stratification, degree centrality, and betweenness centrality) and stage-specific negative binomial regression to characterize the spatiotemporal evolution of the network across four stages (2005-2009, 2010-2014, 2015-2019, and 2020-2024) and identify the mechanisms underlying its influencing factors. At the network-wide level, network density increased steadily, and technology transfer conformed to a significant rank-size rule, with transfers preferentially occurring among core cities. The network also exhibited a pronounced Matthew effect, whereby a small number of high-value city pairs accounted for a large share of the total transfer volume. At the channel level, both the number and scale of transfer channels grew continuously. Shenzhen and Guangzhou acted as radiation (outflow) centers; Huizhou, Jiangmen, Zhaoqing, and Zhongshan served as convergence (inflow) centers; Hong Kong shifted from a convergence to a radiation role; and Foshan and Zhuhai shifted from radiation to convergence. The direction of transfer shifted from mutual exchanges among core cities toward diffusion to surrounding cities, and the diffusion mode evolved from hierarchical diffusion to a mixed mode combining hierarchical, contact, and jump diffusion. In terms of advantageous flows, Guangzhou and Shenzhen exhibited both agglomeration and spillover effects. Shenzhen-Dongguan and Guangzhou-Foshan constituted the largest mutual flow pairs, and Hong Kong's advantageous flow pointed stably toward Shenzhen. At the node level, the network exhibited a polycentric structure: Shenzhen functioned as the first-tier core, with Guangzhou, Zhongshan, Foshan, and Dongguan as secondary centers, and the network evolved from a Guangzhou-Shenzhen "dual core" toward a multi-center pattern; Shenzhen, Guangzhou, and Zhongshan remained the key nodes, while Dongguan, Shenzhen, Guangzhou, and Hong Kong maintained relatively high betweenness centrality. Negative binomial regression showed that geographic distance, industrial similarity, economic development level, R&D personnel, imports, and technological absorption capacity significantly influenced technology transfer, whereas R&D expenditure and FDI were significant only at specific stages. Among them, geographic distance and economic development level exerted negative effects, confirming their constraining roles, while industrial similarity exerted a robustly positive but gradually declining effect because within the GBA, similar industrial structures reflect collaborative division of labor along the same industrial chain rather than homogeneous competition. This study constructed a directed technology transfer network from a "space of flows" perspective and revealed the spatiotemporal evolution and multi-factor driving mechanisms of technology transfer in the GBA, uncovering its evolutionary patterns across multiple scales, namely the overall network, transfer channels, and node functions. By incorporating both dyadic and node-attribute variables, this study further revealed the dynamic evolution of influencing factor effects through four stage-specific regressions. The findings provide empirical evidence and policy implications for optimizing regional technology transfer and advancing the construction of the GBA as an international science and innovation center.
As urban renewal increasingly shifts from physical reconstruction toward environmental quality and human-centered experience improvement, street shading has become an important spatial resource for mitigating summer heat exposure and supporting commercial outdoor activities. Existing studies have, however, largely relied on single-year or short-term cross-sectional data and have rarely examined whether the effects of different shading types remain stable over time or operate through street-user aggregation. Taking the six central urban districts of Nanjing, China, as the study area, this study develops a longitudinal analytical framework using street-view imagery and historical points of interest for eight years between 2014 and 2022. To reduce phenological inconsistencies among images acquired in different seasons, non-summer streetscapes were transformed into summer vegetation conditions using a CycleGAN-based unpaired image-to-image translation model. DeepLabV3+ was then applied to quantify the natural, artificial, and integrated shading resources. Pedestrians and riders were detected using Faster R-CNN to characterize street-user aggregation, whereas commercial vitality was represented by the number of commercial points of interest within 20-m street buffers. Structural equation models were estimated separately for each year to distinguish the direct from the indirect effects mediated by street-user aggregation. Our study reveals three major findings. First, all three shading resource types generally exhibited higher levels in the central areas and lower levels in the peripheral areas. Natural shading remained dominated by the very-low and low categories, which together accounted for more than 70% of street segments throughout the study period. Commercial vitality became increasingly concentrated in the very-low category (rising from 85.73% in 2014 to 90.28% in 2022), whereas high-vitality clusters became more spatially fragmented. Second, natural shading showed negative direct associations with commercial vitality (standardized path coefficient range, -0.28 to -0.09), artificial shading showed positive direct associations (standardized path coefficient range, 0.10 to 0.24), and integrated shading exhibited mostly negative direct associations (standardized path coefficient range, -0.05 to 0.07). Third, all three shading types exerted positive indirect effects through street-user aggregation. The path from street-user aggregation to commercial vitality remained comparatively stable across the years, with standardized coefficients of 0.27 to 0.66. Therefore, natural and integrated shading displayed competitive mediation, characterized by negative direct but positive indirect effects, whereas artificial shading displayed complementary mediation because its direct and indirect effects were both positive. These findings demonstrate that the influence of street shading on commercial vitality depends not only on shading quantity but also on shading type, street function, and the capacity of shaded environments to attract and retain pedestrian activity. Methodologically, this study extends shading-vitality research from static assessment to longitudinal mechanism identification by integrating seasonal correction, semantic segmentation, object detection, and year-specific structural equation modeling. These findings provide evidence for differentiated street-renewal strategies to improve the compatibility between summer thermal adaptation and commercial vitality: artificial shading should be coordinated with commercial frontages, while natural shading should be configured according to street function and pedestrian use.
This paper takes 30 provinces in China from 2012 to 2023 as research samples. By constructing a comprehensive evaluation index system for data elements and the innovative development of the circulation industry. and by characterizing their spatiotemporal evolution characteristics, this study adopts fixed-effect and interaction-term models to explore the contextual impacts of data elements on the innovative development of the circulation industry, and identify the boundary conditions of government behavior. The empirical results show that, first, the development levels of both data elements and circulation industry innovation achieved steady growth during the research period. Regional disparities tend to converge under the guidance of national strategies, while their spatial distribution still presents an unbalanced pattern of “the East taking the lead, the Central region keeping pace, and the West lagging behind.” Second, data elements serve as a driving force empowering innovative development in the circulation industry, and their empowerment effect exhibits a spatial gradient pattern: gradually increasing from the West to the East of China. Third, the empowerment effect of the data elements has a prominent contextual dependence. Human capital and industrial upgrading exert negative moderating effects, and the coefficient signs of their interaction terms conform to the theoretical characteristics of substitution moderation. Innovation output contrasts these negative effects by generating a significant positive moderating effect, indicating that higher levels of innovation output strengthen the marginal contribution of data elements. Fourth, the moderating effect of government behavior presents remarkable regional heterogeneity; excessive government intervention restrains the empowerment effect of data elements in Eastern China, whereas it has a positive synergistic relationship with data elements in Western China. Given the imperfect market mechanisms in the Western region, moderate government intervention effectively magnifies the innovation-driven effects of data elements. These findings provide an important geographical interpretation for understanding the regional adaptability of government-market relations in the digital economy era. The conclusions offer policy references for advancing the market-oriented allocation of data elements, facilitating the digital and intelligent transformation of the circulation industry, and boosting coordinated regional development. Regarding contributions, first, from a research perspective, it regards the incorporation of government behavior (into the analytical framework of data elements empowering circulation industry innovation) as an important institutional pathway; overcomes the bias in existing literature that overemphasizes “effective markets” while ignoring “proactive governments”; constructs a three-dimensional analytical framework of “data element allocation-circulation industry innovation-government behavior boundaries”; and expands the institutional analysis dimension for interdisciplinary research linking data elements and circulation economics. Second, regarding indicator construction, the study systematically constructs an evaluation system for data elements covering five dimensions (data infrastructure, development ecosystem, application level, financial support, and R&D investment), and an evaluation system for the innovative development of the circulation industry covering six dimensions (innovation, coordination, green development, openness, sharing, and security). It more comprehensively depicts the multi-dimensional characteristics and internal correlation between data elements and the innovative development of the circulation industry. Third, in terms of research methodology, this study adopts fixed-effects and interaction-term models to effectively identify the enabling effects of data elements, further explores the contingency of these effects from the perspective of three contextual dimensions (human capital, industrial upgrading, and innovation output), and reveals the regional heterogeneity embedded in the moderating effects of government behavior by incorporating spatial friction theory. Thus, it uncovers the gradient pattern, contextual dependence, and spatial adaptation mechanisms of data elements empowering the innovative development of the circulation industry from the dual dimensions of temporal evolution and spatial correlation.
