The use of multi-perspective and multi-scalar city networks has gradually developed into a range of critical approaches to understand spatial interactions and linkages. In particular, road linkages represent key characteristics of spatial dependence and distance decay, and are of great significance in depicting spatial relationships at the regional scale. Therefore, based on highway passenger flow data between prefecture-level administrative units, this paper attempted to identify the functional structures and regional impacts of city networks in China, and to further explore the spatial organization patterns of the existing functional regions, aiming to deepen our understanding of city network structures and to provide new cognitive perspectives for ongoing research. The research results lead to four key conclusions. First, city networks that are based on highway flows exhibit strong spatial dependence and hierarchical characteristics, to a large extent spatially coupled with the distributions of major megaregions in China. These phenomena are a reflection of spatial relationships at regional scales as well as core-periphery structure. Second, 19 communities that belong to an important type of spatial configuration are identified through community detection algorithm, and we suggest they are correspondingly urban economic regions within urban China. Their spatial metaphors include the administrative region economy, spatial spillover effects of megaregions, and core-periphery structure. Third, each community possesses a specific city network system and exhibits strong spatial dependence and various spatial organization patterns. Regional patterns have emerged as the result of multi-level, dynamic, and networked characteristics. Fourth, adopting a morphology-based perspective, the regional city network systems can be basically divided into monocentric, dual-nuclei, polycentric, and low-level equilibration spatial structures, while most are developing monocentrically.

The knowledge economydefined here as production and services based on knowledge intensive activitiesis widely recognized to have accelerated knowledge production and spillovers through a deepening of collaborative networks that can extend over extensive geographical distances. However, limited by data availability, the geography of China's knowledge production and collaborative networks, segmented by different disciplines, has been little studied in economic geography or innovation studies. This paper draws on data on academic publications that were extracted from the China Academic Journal Network Publishing Database (CAJD) in order to construct knowledge production and collaboration networks for different disciplines in China. The results depict a series of maps that show that: (1) the 'hard' sciences (natural sciences and engineering) outperform much more than the 'soft' sciences (humanities and social sciences) both in article number and collaboration strength; and (2) large metropolises have overwhelming advantages in the terms of both paper production and the collaboration strength for all disciplines, despite varying among different disciplines. These uneven geographical patterns can be partially attributed to a high concentration of scientific resources in a few large cities, which was inherited from the Maoist period.

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While the redevelopment of urban brownfield sites in China has received much attention, the role of political ideology in this process is usually downplayed or sidelined to a set of stylized assumptions. This paper invites giving a greater analytical focus to the evolving and nonorthodox nature of China’s politico-ideological model as a factor shaping urban change and redevelopment. The paper provides an analytical framework integrating multi-level and evolutionary perspectives while exploring the experiences of the formation and post-industrial redevelopment of brownfield sites in Beijing. The analysis demonstrates that neoliberal economic policies and the communist political doctrine are co-constitutive in the production of China’s post-industrial urban space. This produces a sense of spatial hybridity that combines and co-embeds what may be assumed to be mutually exclusive.

The high separation of crude oil supply and demand markets has led to the formation of a global crude oil trading system. This paper constructs global crude oil trade networks, integrates macro, meso, and micro network analysis methods, combines geospatial visualization techniques, and then portrays the spatiotemporal patterns and topological evolution of the global crude oil trade networks. Thus, it attempts to dig deeper into the world crude oil competition and cooperation links and evolution laws and provides a scientific reference for a comprehensive understanding of the global crude oil market dynamics. The results show that: (1) After three fluctuations of increase and decrease since 2000, the global crude oil trade volume is entering the adjustment period, and the scale of the crude oil market is rising slowly. (2) The international crude oil trade has formed trade network patterns with complex structures, clear hierarchy and unbalanced distribution. The “rich club” phenomenon is significant, with large trading countries dominating the trade network. (3) The scale and density of the global crude oil trade network show a trend of increasing and then decreasing, the network agglomeration pattern becoming more obvious, the inter-nodal links continuously strengthening, and the network connectivity improving. (4) The global crude oil trade networks are characterized by core–periphery structures, and the polarization effect is significant. The US, Russia, China, Japan, the Netherlands, and South Korea hold the core positions in the crude oil trade network, and the major importing countries have become the dominant forces in the trade network. In addition, we present policy suggestions for different types of countries for energy transformation and security in the global trade market system, which can be used as a reference for policymakers.