The “Belt and Road” has developed from a Chinese initiative to an international consensus, and Silk Road cities are becoming a strategic step for its high-quality development. From the perspective of industrialization, the “Belt and Road” can be regarded as a “spillover” effect of the industrialization process in China. With the spatial shift of Chinese industries along the “Belt and Road” and their clustering in Silk Road cities, the development and change of industrial land in Silk Road cities has become a new area of concern for governments and scholars. In this paper, the driving mechanism of industrial land change in 129 cities along the Silk Road in China is empirically studied by the GeoDetector method. The findings include: first, the development and changes of industrial land in Silk Road cities are significantly spatially heterogeneous, and the “Belt and Road” reshapes the town system and economic geography along the route by virtue of the differentiated configuration and changes of industrial land, changing the social, political, landscape and spatial relations in cities on the line. Second, the driving forces of industrial land change in Silk Road cities under the influence of the “Belt and Road Initiative” are increasingly diversified and differentiated, with significant two-factor enhancement and non-linear enhancement interaction between two driving factors, and growing complexity of the driving mechanisms, requiring policy makers to design policies based on key factors, comprehensive factors and their interaction. Third, the environmental effect of industrial land change is highly complex. The industrial land quantity has a direct impact on the ecological state parameter and plays a decisive role in the quality of the ecological environment and its changes in Silk Road cities. However, changes in the industrial land affect the ecological state change indirectly, mainly interacting with it through the coupling of pollutant and carbon dioxide emissions, energy use, ecological planning and landscape design and policy interventions. Finally, this study provides a new framework and method for Silk Road scholars to analyze the spatial and temporal evolution characteristics of land use and coverage in cities along the “Belt and Road” and their influence mechanisms, and provides a basis for the government to make decisions on industrial land supply and layout planning and spatial governance policy design, which is of great theoretical significance and practical value.

The level of service-industry development has become an important symbol of the competitiveness and influence of cities. The study of the dynamic evolution characteristics and patterns of urban service-industry land use, the driving factors and their interactions is helpful to provide a basis for decision making in policy design and land use planning for the development of service economies. In this study we have conducted an empirical study of China, based on the methods of spatial cold- and hot-spot analysis, Tapio’s decoupling model, and GeoDetector. We found that: (1) the scales of land use, output efficiencies and development intensities of service-industries are increasing with a trend that takes the form of a “J”, “U” and “inverted U”, respectively; (2) Spatial variabilities and agglomerations are significant, with a stable spatial pattern of the scale of service-industry land use, and a gradient in the distribution of cold- and hot-spots. The dominant spatial units of output efficiency and development intensity have changed from low and lower to high and higher, and the cold- and hot-spots gather in clusters; (3) The development of service-industries is highly dependent on the input of land-resources, and only a few provinces are in a state of strong decoupling, while most are in a state of weak decoupling, with quite a few still in a state of expansive coupling, expansive negative decoupling, or even strong negative decoupling; (4) There are many driving factors for land use changes in the service-industry, with increasingly complicated and diversified relationships between each other, ranked in intensity as the scale effect > informatization > globalization > industrialization > urbanization.

As the primary drivers of the chemical industry, chemical industrial parks should be characterized by industrial symbiosis, which is essential for realizing the worldwide transformation from linear to circular economies based on sustainable development. At present, a lack of sufficient attention is paid to analyzing the structural characteristics and interaction patterns of industrial symbiosis networks in chemical industrial parks, especially in large-scale specialized chemical industrial parks on a national scale. In this context, with Nanjing Jiangbei New Materials High-Tech Park as an example, this study applies a social-network analysis to empirically investigate the structural characteristics and interaction patterns of an industrial symbiosis network. The results revealed that the industrial symbiosis network of Nanjing Jiangbei New Materials High-Tech Park is currently in a state of low-level agglomeration with a poor transitivity index and that short-distance straight chains are the main connections between enterprises with few transverse connections. Recycling enterprises occupy the core position in the network, while chemical manufacturing enterprises are mostly located on the periphery of the network and fail to establish sufficient effective connections. In terms of individuals, stakeholders’ understanding and evaluation of industrial symbiosis are insufficient; in terms of enterprises, the obstruction of byproducts and waste information circulation and other factors are the main obstacles restricting the industrial symbiosis activities in Nanjing Jiangbei New Materials High-Tech Park. Some policy recommendations are proposed to improve the industrial symbiosis network in large-scale specialized chemical industrial parks on a national scale, and these include establishing industrial symbiosis information systems for the parks, fostering multiple central nodes, and advancing nested development among industrial chains.

In recent years, manufacturing development has received renewed attention from developing and developed countries alike. As mega-city regions (MCRs) are where manufacturing industries converge, the research on urban networks of MCRs under the dominance of manufacturing transaction linkages is currently insufficient. Based on the buyer–supplier linkages of listed manufacturing firms, this paper investigated the characteristics of the urban network in the Yangtze River Delta region (YRDR) in China using the social network analysis method; explored the determinants of nodal centrality and city dyads of the urban network by the stepwise regression and quadratic assignment procedures, respectively; and proposes a “characteristics-determinants-strategies” technical framework for the analysis and optimization of interurban collaboration in manufacturing transactions within MCRs. The findings were as follows: (1) The characteristics of the urban manufacturing transaction networks differed from those of transaction linkages of advanced producer services (APS) firms, intra-firm organization hierarchies, and innovation cooperation networks; (2) the network and geographical “core-periphery” structure of urban power and the circulation corridor of the urban manufacturing transaction network was formed within the YRDR; (3) cooperation parks, innovation collaboration, high-speed rail (HSR) linkage, and geographical proximity between cities were found to facilitate the formation of urban manufacturing transaction networks, and the similarity of industry structures and driving distance between cities inhibits the network; (4) the number of urban industrial firms, GDP per capita, and city government spending on science and technology contributed to the centrality of a city in urban manufacturing transaction networks, while the urban population in a city had a negative impact. The research provides a complementary perspective to the urban network research of MCRs under the perspective of production factors and product circulation and provides policy and urban planning insights for the synergistic development of interurban manufacturing in MCRs.

This study investigates the dynamics of innovation element flows among metropolitan areas and examines the underlying proximity mechanisms that are crucial for elevating urban agglomerations’ innovation levels and spurring their development. Utilizing collaborative publication and patent data, this research constructs knowledge and technological innovation networks within the Nanjing metropolitan area (NMA) from 2013 to 2020. It analyzes the evolution of network structures and applies the Multiple Regression Quadratic Assignment Procedure to discern the proximity mechanisms driving the urban innovation networks’ evolution in NMA. The main findings are as follows: (1) The knowledge collaborations within NMA cities remain largely confined to cities within Jiangsu province, whereas the technological collaborations are shifting from intra-province to cross-province cooperation. (2) Both knowledge and technological innovation networks display a “core-periphery” configuration, with Nanjing maintaining a dominant central position. The scale of the KIN surpasses that of the TIN, while the latter’s growth rate outpaces the former’s. Technological collaborations demonstrate more pronounced spillover effects than their knowledge counterparts. (3) At the metropolitan area level, organizational, social, cognitive, and technological proximities exert varying degrees of influence on innovation cooperation among different innovation entities across various years. Cognitive proximity exhibits the most substantial explanatory power. Based on these findings, the study proposes relevant policy recommendations for constructing an innovative NMA and promoting collaborative innovation development among cities within the NMA.

The stagnation of multinational and cross-regional goods circulation has created significant disruptions to manufacturing supply chains due to the outbreak of the COVID-19 pandemic. To explore the impact of COVID-19 on the circulation of manufacturing industry products at different geographical scales, we drew upon a case study of development zones in the city of Weifang in China to analyze the characteristics of firms’ logistics networks in these development zones, and how these characteristics have changed since the outbreak of the COVID-19 pandemic. The data used in this study were collected from fieldwork conducted between 26 August 2020 and 15 October 2020, and included the supply originations of firms’ manufacturing sources and the sales destinations of their goods. We chose the two-mode network analysis method as our study methodology, which separates the logistics networks into supply networks and sales networks. The results show the following: First, the overall structure of firms’ logistics networks in Weifang’s development zones is characterized by localization. In the context of the COVID-19 pandemic, the local network links have further strengthened, whereas the global links have seriously declined. Moreover, the average path length of both the supply and sales logistics networks has slightly decreased, indicating the increased connectivity of the logistics networks. Second, in terms of the network node centrality, the core nodes of the supply logistics networks are the development zones and the city in which the firms are located, whereas the core nodes of the sales logistics networks are the core companies in the development zones. However, since the outbreak of the COVID-19 pandemic, the centrality of supply originations and sales destinations at the local scale has increased, whereas the centrality of supply originations and sales destinations at the global scale has decreased significantly. Third, the influencing factors of such changes include controlling personnel and goods circulation based on national boundaries and administrative boundaries, forcing the logistics networks in the development zones to shrink to the local scale. Moreover, there are differences in the scope of spatial contraction between supply logistics networks and the sales logistics networks.