Search Results (51)

As an important direction in industrial evolution, the synergistic agglomeration of manufacturing and productive service industries has become a key path to promote the green transformation of the economy. Based on China’s provincial panel data, this study utilizes a variety of econometric methods to explore in depth the mechanisms, spatial effects and regional differences in the impact of the synergistic agglomeration of manufacturing and productive service industries on the green, low-carbon and recycling development of the economy. The empirical results show that the synergistic agglomeration of manufacturing and productive services not only directly promotes the green, low-carbon and recycling development of the economy, but also generates an indirect impact through the intermediary channel and exhibits significant spillover characteristics in the spatial dimension. This conclusion holds firm after a series of robustness tests. In addition, environmental regulations and the level of regional industrialization play a moderating role on the impact of industrial synergistic agglomeration and green, low-carbon and recycling development of the economy, and the effect of the role varies across regions and levels of economic development. This paper provides a decision-making reference for further optimizing the regional layout of China’s industries and enhancing the green, low-carbon and recycling development of the economy in each province. Full article

As the mainstream financial modality in the digital economy era, digital finance drives industrial digitization and green transformation through capital and technological support, enabling governments to advance environmental governance with greater precision, efficiency, and sustainability. Utilizing 2012–2023 panel data from 31 Chinese provinces, this study innovatively constructs a multidimensional panel data model for the quantitative analysis of the overall impact, heterogeneous effects, and spatial spillover effects of digital finance on government environmental governance. It further examines the mediating effect and the threshold effects of new quality productive forces, and the moderated mediation effects of green technological innovation and industrial collaborative agglomeration. In this study, (1) digital finance significantly drives government environmental governance, and this finding exhibits robustness; (2) digital finance exerts heterogeneous impact on government environmental governance, with more pronounced effects in eastern and sub-developed regions; (3) digital finance generates positive spatial spillover effects on government environmental governance; (4) new quality productive forces positively mediate the relationship between digital finance and government environmental governance; (5) green technological innovation exhibits dual moderation characteristics, moderating both “digital finance → new quality productive forces” and “new quality productive forces → government environmental governance,” while industrial collaborative agglomeration shows single moderation, specifically moderating “new quality productive forces → government environmental governance”; (6) the impact of digital finance on government environmental governance presents a nonlinear feature of “increasing marginal returns.” On these accounts, this study proposes targeted recommendations from six dimensions. Full article

The imbalance between urban and rural development has become a global structural problem that needs to be solved urgently. In this context, the tourism industry, with its strong correlation and cross-regional integration characteristics, provides a key practical entry point and mechanism for systematically promoting integrated development by stimulating factor flow, reconstructing the value chain, and reshaping local identity. Based on the synergetic theory, this paper constructs the theoretical framework of the synergetic evolution of the tourism industry and urban–rural integration, and analyzes the synergetic effect of the tourism industry and urban–rural integration in 58 prefecture-level cities in the Yellow River Basin from 2007 to 2021 and the dynamic characteristics of its spatio-temporal evolution by using the entropy TOPSIS, Haken model, and spatial Markov chain methods. The results show the following: ① As the order parameter of synergistic evolution, the tourism industry dominates the evolution direction of the whole system, mainly showing positive feedback effect, showing a significant stage characteristic in general, and gradually reducing the difference from the initial regional differentiation to the middle stage, finally reaching a higher level of unity. ② The synergic evolution of the tourism industry and urban–rural integration in the Yellow River Basin presents significant temporal and spatial differences in the upstream, midstream, and downstream, with the overall characteristics of “collaborative improvement in the upstream, significant agglomeration in the midstream, and reverse decoupling in the downstream”. ③ The dynamic evolution of the synergistic development of the tourism industry and urban–rural integration in the Yellow River Basin has significant characteristics of spatial interaction and dynamic transfer. Its level has the effect of “path dependence”, showing a good trend of upward transfer, and the spatial neighborhood has a significant impact on the synergetic level transfer. The development trend of each region shows that “the upstream region is upward and stable, the midstream region has significant agglomeration and diffusion effects, and the downstream region is driven by polar nuclei and spatial differentiation”. Full article

Exploring the mechanism of science and technology innovation spillover effect and collaborative innovation on the high-quality development of urban agglomerations is of great practical significance for implementing the innovation-driven development strategy. Based on the panel data of prefecture-level cities from 2012 to 2020, this study uses web crawler technology to obtain cooperative invention patent data, combines the social network analysis method to construct collaborative innovation networks, constructs a high-quality development indicator system from six dimensions such as the degree of marketization and the industrial system, and adopts the spatial Durbin model to reveal the regional innovation spillover effect. The comparative study based on the Yangtze River Delta (YRD) and Beijing-Tianjin-Hebei (BTH) urban agglomerations found the following: (1) There is significant spatial heterogeneity in science and technology innovation, with the YRD showing a positive spillover trend and BTH showing a significant negative spillover trend; (2) The collaborative innovation network shows differentiated characteristics, with the YRD having a higher density of the network and forming a multi-centered structure, and BTH maintaining the pattern of single-core radiation; (3) There is a horse-tracing effect in high-quality development, with the average score of YRD The average score of YRD is significantly higher than that of Beijing-Tianjin-Hebei, and the indicators of several dimensions are better. Based on these conclusions, city clusters should further strengthen the construction of collaborative innovation networks among cities and enhance the capacity of neighboring cities to undertake innovation, to give full play to the spillover effect and driving effect of innovation on high-quality development. Full article

Resource-exhausted cities face dual crises of economic stagnation and ecological degradation, which is primarily attributable to the inefficient use of industrial land. The redevelopment of industrial land has emerged as a crucial solution to the “resource depletion-urban decline” dilemma. The issue of inefficient industrial land use in resource-exhausted cities is of great significance as it directly impacts both economic development and ecological protection. Therefore, finding effective ways to redevelop this land is essential for the sustainable development of these cities. This research takes Hegang, a representative resource-exhausted city in China, as a case study. A multi-dimensional evaluation framework and an adaptive redevelopment strategy system are constructed in this research. By integrating data related to land use status, land use efficiency, policy constraints, and development potential, a parcel-scale assessment model is established. This model consists of 4 primary indicators and 13 secondary indicators. Through this model, 11.01 km² of inefficient industrial land in the main urban area of Hegang is identified. Standard deviation ellipse and kernel density analysis are employed to reveal the spatial pattern of inefficient land. The results show that the inefficient industrial land in Hegang exhibits a pattern of “overall dispersion with localized agglomeration”. It is found that idle and abandoned land are the dominant types of inefficient industrial land in Hegang’s main urban area, accounting for 69.7% of the total. This finding provides a clear understanding of the nature of the inefficient land use problem in resource-exhausted cities. A strategic framework is proposed, which incorporates classified governance, dynamic restoration, and multi-stakeholder collaboration. This framework offers a governance toolkit with both theoretical depth and practical value for resource-exhausted cities. Breaking the locked relationship between industrial land and resource dependence promotes the deep integration of spatial restructuring and sustainable transformation. The findings of this research provide significant scientific insights for similar cities worldwide to address the challenges they face and achieve harmony between human activities and land use. Future research could focus on further refining the evaluation framework and redevelopment strategies based on different regional characteristics and resource endowments. Full article

The digital economy has profoundly reshaped industrial organizational structures and the spatial distribution of cooperative agglomerations in the manufacturing and productive service sectors. To support the coordinated and sustainable development of China’s industries, it is essential to clarify how the digital economy influences industrial cooperative agglomeration. This study first constructs a comprehensive index system capturing the quality, quantity, and synergy of industrial cooperative agglomeration, enabling an evaluation of collaborative agglomeration levels across 30 Chinese provinces. Second, the relationship between the digital economy and industrial collaborative agglomeration is examined using both static and dynamic spatial panel models. Finally, the paper investigates regional disparities in this relationship across eastern, central, and western China. The results reveal the following findings: (1) The digital economy has a significant inhibitory effect on industrial collaborative agglomeration overall. (2) Dynamic spatial lag model results show an inverted U-shaped relationship, where the digital economy initially promotes but later inhibits industrial agglomeration, with notable temporal lags and spatial spillover effects. (3) In eastern China, digital economy growth suppresses local agglomeration while promoting it in neighboring regions; in the central region, it enhances local agglomeration but dampens it in adjacent areas; and in the western region, the relationship is nonlinear and U-shaped. Full article

Global warming has increasingly become a widespread concern of the international community, and one of the key approaches to achieving carbon neutrality goals lies in the carbon sequestration capacity of oceans. Therefore, scientifically and accurately measuring the carbon sink capacity of marine fisheries and studying its spatial effects are particularly crucial for mitigating global climate change. Marine fisheries encompass categories such as fish, shellfish, algae, and crustaceans. Given that marine fisheries-based carbon sinks are non-feed fisheries, with cultivated shellfish and algae being highly representative, this paper primarily focuses on the carbon sink capacity of shellfish and algae as the main assessment criteria for marine fisheries carbon sinks, aiming to apply this research to other countries worldwide to assist in addressing global warming. Thus, based on panel data of shellfish and algae cultivation in nine coastal provinces of China from 2007 to 2021, this paper employs the “removable carbon sink” model to calculate the carbon sink capacity of Chinese marine shellfish and algae aquaculture industry and utilizes the spatial Durbin model to analyze its spatial effects. The research findings are as follows: (1) The spatial distribution of carbon sink capacity in China’s marine shellfish and algae is uneven. (2) Moran’s Index indicates that the carbon sink capacity of marine shellfish and algae exhibits positive spatial correlation, but the degree of spatial agglomeration is unstable. Fujian Province has the highest average carbon sink capacity at 446,451.21 tons, while regions such as Hainan, Hebei, and Jiangsu have relatively lower average carbon sink capacities, with Hainan Province’s being only 3627.57 tons, sufficiently demonstrating the characteristic of uneven spatial distribution. (3) Through decomposition using the spatial Durbin model, it is found that the direct effects of marine shellfish and algae aquaculture production, technological input, technological promotion, and fishery disaster situations are positive, with the result for marine shellfish and algae aquaculture production being 1.617, significantly positive at the 1% level. The result for labor input is −0.847, with a negative direct effect. From the perspective of indirect effects, the indirect effects of marine shellfish and algae aquaculture production, technological input, and technological promotion are positive, with aquaculture production at 1.185, still significantly positive at the 1% level. The result for labor input is −2.140, with a negative indirect effect. These research conclusions provide important references for the formulation of global marine carbon sink-related policies, helping countries optimize resource allocation, strengthen regional collaboration, and increase investment in science and technology. Consequently, they can promote the sustainable development of marine shellfish and algae aquaculture industries, and contribute to enhancing marine carbon sink capacity and achieving global carbon neutrality goals. Full article

In the context of high-quality economic development, the empowering effect of regional integration policies on urban green and low-carbon development has significantly strengthened, playing a crucial strategic role in achieving the coordinated development of the economy and ecology. This study uses the expansion of the Yangtze River Delta urban agglomeration as a quasi-natural experimental scenario, analyzing the pathways and mechanisms through which regional integration policies influence urban green and low-carbon development based on panel data from Chinese cities between 2004 and 2022, using a multi-period Difference-in-Differences (DID) model. The empirical results show the following: ① Regional integration policies significantly enhance the efficiency of urban green and low-carbon development, a conclusion that remains robust after a series of robustness tests, including PSM-DID estimation, placebo tests, instrumental variable methods, indicator reconstruction, and policy interference exclusion. ② Mechanism tests reveal that regional integration policies mainly drive the green and low-carbon transformation through three channels: innovation investment, industrial upgrading, and talent aggregation. ③ Heterogeneity analysis indicates that the positive impact of regional integration policies on the green and low-carbon development of cities is more significant in eastern regions, resource-based cities, small and medium-sized cities, and old industrial cities. Spatial effect tests show that regional integration development has a significant spatial spillover effect on urban green and low-carbon transformation. Based on these findings, it is recommended that, in the future, in global efforts should be made to continuously improve the regional collaborative governance system, strengthen multi-dimensional linkage mechanisms in urban agglomerations, and build a policy support framework that drives innovation and optimizes the allocation of factors. This study not only provides empirical support for the green efficiency enhancement mechanisms of regional integration policies but also offers decision-making references for promoting regional coordinated development and achieving green economic growth in the digital economy era. Full article

This study investigates the competitive and cooperative relationships within urban agglomerations, specifically focusing on the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Using the Lotka–Volterra model from ecology, the research aims to analyse and predict the dynamic relationships among cities in this area. The purpose is to understand how competition and cooperation influence regional integration, and their complex economic connections. This paper employs both qualitative and quantitative methods, including time-series analysis and the application of the Lotka–Volterra model, to evaluate economic interactions and the roles of various cities or regions within the GBA. The study reveals that mutualistic, competitive, predatory, commensal, and parasitic relationships coexist among them, with core cities such as Shenzhen, Guangzhou, Hong Kong, and Macao assuming pivotal roles in shaping the overall dynamics. The findings highlight the importance of functional division, regional cooperation, and innovative collaboration to enhance sustainable development. Policy recommendations are provided to foster a balanced and integrated growth model, emphasizing inter-city cooperation, resource sharing, and avoidance of industrial homogeneity. Full article

The clustering and collaborative development among cities, as a strategic measure concerning regional inclusivity and sustainable development, is both a current practice and a future trend, as evidenced by numerous successful cases worldwide. Scholarly research has extensively validated, from a macro-level perspective, its positive effects on social and economic aspects. However, relatively little research has examined its impact on the behavior of micro-level enterprises. To bridge this gap, this study leverages China’s urban integration strategy as a natural experimental framework and employs a two-way fixed effects model to conduct an in-depth investigation. The empirical results indicate that coordinated urban agglomeration development significantly enhances the technological complexity of enterprises within the region. The primary mechanism underlying this relationship is that the urban integration strategy facilitates regional financial concentration, fosters industrial collaborative agglomeration, and advances firm specialization, thereby enhancing the innovation capacity of enterprises. Furthermore, the heterogeneity analysis indicates that the findings are particularly pronounced for core cities within urban clusters, cities with lower levels of industrial specialization, and those with higher levels of financial development. Additionally, the effects are more significant for firms that face fewer financing constraints and inherently possess strong innovation capabilities. These findings not only augment the existing research on the micro-level effects of urban cluster development but also provide valuable insights for local governments in crafting policies to further enhance the sustainable innovation capacity of enterprises. Full article

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

Specialized villages, which are centered around product supply and driven by market demand, serve as critical vehicles for rural industrial revitalization. This study utilizes a sample of 13,702 national-level industrial villages to examine the spatial distribution patterns of specialized villages in China across multiple dimensions. The research employs the Spatial Design Network Analysis (sDNA) model and the Coupling Degree Model to identify regional characteristics of product supply accessibility and the alignment of market demand in these villages. Finally, the paper integrates the spatial analysis results of both supply and demand to propose an optimized layout strategy for specialized villages at the county level. The findings indicate the following: (1) Specialized villages in China exhibit extensive coverage and strong agglomeration, with a high concentration in the eastern region, forming seven core zones arranged in an arc. The provinces with the highest numbers of specialized villages are Zhejiang, Heze, and Yiwu. (2) The spatial distribution of specialized villages demonstrates multi-scale differentiation and spatial autocorrelation, with the most uneven distribution and strongest local autocorrelation occurring at the county level. (3) The zoning results for both supply and demand aspects are closely related to economic divisions and population geographical boundaries, forming nine combination types. These can further be classified into four distinct zones: Demonstration Leading Zones, Optimization Development Zones, Collaborative Promotion Zones, and Cultivation Guidance Zones. (4) Each zone type plays a unique strategic role in the revitalization of rural industries and necessitates differentiated development strategies for specialized villages. The conclusions of this study provide a foundation for optimizing the spatial layout and zonal development of specialized villages in China. Full article

The accelerated growth of the global economy has given rise to a multitude of environmental concerns that demand immediate attention. At this juncture, the total global carbon emissions are exhibiting a gradual increase. China, the United States, India, Russia, and Japan represent the top five countries in terms of global carbon emissions, collectively accounting for approximately 60% of the global total. Of these, China’s carbon emissions are the highest in the world, representing over 30% of the global total. As urbanization accelerates, the carbon emissions from urban agglomerations constitute a substantial share of the nation’s total emissions, rendering the carbon emissions of urban clusters a critical issue. In the context of China’s urban agglomerations, the Beijing–Tianjin–Hebei region, due to factors such as industrial structure, accounts for a relatively high proportion of carbon emissions, approximately 11% of the national total. The future trajectory of carbon emissions in the Beijing–Tianjin–Hebei region will significantly impact the high-quality development of the entire urban cluster. Consequently, research on carbon emissions in the Beijing–Tianjin–Hebei region is of vital importance. This paper takes the carbon emissions of the power industry in the Beijing–Tianjin–Hebei region as the research subject, analyzes its carbon emissions status, and builds a multi-regional input–output model for the Beijing–Tianjin–Hebei region based on the input–output tables and carbon emissions data of each province. This study explores the key influencing factors of carbon emissions from the power industry in this region from 2012 to 2017 and analyzes the carbon emissions transfer and structural evolution from the perspective of the region and the industry to clarify the carbon reduction responsibilities of the Beijing–Tianjin–Hebei region and provide references and recommendations for the formulation of regional collaborative emission reduction policies. The results show that the direct carbon emissions from the power industry in the Beijing–Tianjin–Hebei region account for a higher proportion compared to the indirect carbon emissions it generates by driving other industries. Industries with relatively high indirect carbon emissions in the key path include coal mining and selection, equipment manufacturing, transportation, services, etc. The capital input process from Tianjin and Hebei to Beijing is accompanied by a relatively high carbon transfer. Promoting the widespread adoption of carbon emission reduction technologies will have an effective suppressive effect on carbon emissions in the Beijing–Tianjin–Hebei region, especially in Hebei; Beijing and Tianjin should pay attention to the stimulating effect of increased final demand on carbon emissions; the transfer of carbon emissions between regions and industries shows a downward trend as the power sector undergoes transformation. Full article

This research centers on one of northern China’s most crucial economic regions—the Beijing–Tianjin–Hebei urban agglomeration. This paper primarily addresses the present circumstances, developments, and obstacles pertaining to industrial green development and industrial innovation in the region, with a particular focus on its role in fostering integrated economic and environmental growth. This study utilizes a global super-efficiency SBM model and a coupled coordination model, along with a panel data analysis technique, to determine the extent of green development, innovation, and green innovation collaboration in the Beijing–Tianjin–Hebei urban agglomeration cluster between 2018 and 2022. The study revealed that, despite notable advancements in industrial green development in the Beijing–Tianjin–Hebei urban agglomeration in recent years, the disparity in urban development persists, with some cities exhibiting a relatively low input–output ratio for green innovation. There is a pressing need to enhance overall efficiency through policy guidance and technical support. Furthermore, the study underscores the significance of bolstering regional collaboration and facilitating the sharing of resources and technological exchange to attain harmonized regional development. Full article

This study focuses on the 13 cities within the Beijing–Tianjin–Hebei (BTH) urban agglomeration, developing a sophisticated rating index system grounded in a factor–environment–effect framework to assess the coupling and coordinated development of the cultural and tourism industries across the region, alongside their spatiotemporal evolution dynamics. The study further delves into the internal constraints and external driving forces, aiming to identify the current state and key bottlenecks of regional cultural–tourism integration. The findings indicate that: (1) On the whole, the cultural and tourism industries in the region exhibit a fluctuating yet upward trajectory, with a robust coupling between the two systems. The coupling coordination has transitioned from the “uncoordinated state” to the “transition stage”. (2) Regionally, the degree of coupling coordination evolves from “uncoordinated” to “coordinated”. Cities have progressively advanced in their coupling coordination levels and shown certain spatial clustering characteristics. Based on the evolving types of coupling coordination, six distinct patterns are identified. Beijing and Tianjin have emerged as models of synchronized cultural–tourism development, while cities in Hebei are increasingly shifting toward a tourism-prioritized development model. (3) Cultural development effects represent the primary obstacle factors, while technological innovation, urban infrastructure, digital construction, and government investment emerge as the major driving forces. Specifically, the interactions between industrial structure and government investment, industrial structure and technological innovation, and urban environment and economic scale have a more significant impact on the development of the cultural–tourism coupling coordination development. Based on the preceding analysis, it is recommended to implement targeted policy measures to enhance collaboration between Beijing, Tianjin, and the surrounding cities in critical sectors. This should focus on expanding the synergies between culture and tourism, leveraging digital technologies to foster innovation and integration within the cultural and tourism industries. Such initiatives will help mitigate the regional disparities in the development of cultural–tourism integration and promote a more balanced and sustainable growth trajectory. Full article