Fang Wang

This study analyzes the structure of China’s overall railway transport network and its sub-networks of conventional railway and high-speed railway, with the aim to understand the country’s economic spatial structure that is reflected by or underlines the railway transport network. First, the results indicate that compared with developed cities, backward cities not only have fewer train services but also lack a symmetrical transport plan; backward cities tend to connect with developed cities rather than within themselves. Second, the national-level urban hierarchy was established using the proposed algorithm, which helped reveal the economic geography of three economic plates in China. Third, the law of the primate city is not prominent in a large country such as China, which is undergoing regional restructuring with the economic center of gravity shifting to the coastal area while also moving south.

In the new consumption era, the popularization and application of information technology has continuously enriched residents’ consumption channels, gradually reshaping their consumption concepts and shopping behaviors. In this paper, Hohhot is taken as a case study, using open-source big data and field survey data to theorize the characteristics and mechanism of residents’ shopping behaviors in different segments of consumers based on geography. First, communities were divided into five types according to their location and properties: main communities in urban areas (MCs), historical communities in urban areas (HCs), high-grade communities in the outskirts of the city (HGCs), mid-grade communities in urban peripheries (MGCs), and urban villages (UVs). On this basis, a structural equation model is used to explore the characteristics of residents’ shopping behaviors and their influencing mechanisms in the new consumption era. The results showed that: (1) The online shopping penetration rate of residents in UVs and HCs is lowest, and that of residents in HGC is highest. (2) The types of products purchased in online and offline shopping by different types of community show certain differences. (3) From the perspective of influencing mechanisms, residents’ characteristics directly affect their shopping behaviors and, indirectly (through the choice of community where they live and their consumption attitudes), their differences in shopping behaviors. Different properties of communities cannot directly affect residents’ shopping behaviors, but they can affect them indirectly by influencing consumption attitudes and then affect such behaviors. Typical consumption attitudes of the new era, such as shopping for luxuries and emerging consumption, have the most significant and direct influence on shopping behaviors, as well as an intermediate and variable influence.

The rapid spread of COVID-19 and its global growth constitutes an international public-health emergency, posing a serious threat to global health, safety, and social economy. In this paper, we systematically studied the temporal and spatial characteristics of COVID-19, infectivity, and the impact of Hubei province’s quarantine on the national railway system on the basis of epidemic and national train data. This study found the following: (1) The overall growth of the epidemic was exponential, and the outbreak of Hubei had a strong spread in the eastern and southern directions. The epidemic was generally more serious in the capital or developed cities in each province, and the epidemic outside Hubei was under control after the imported growth ended. (2) On the basis of analyzing the disturbance of the spread of the epidemic by traffic control, the average incubation period of COVID-19 was approximately 4 days. The ratio of the number of cured people to the number of deaths gradually increased, indicating that, given sufficient medical service, the cure rate can be greatly improved. (3) The quarantine of Hubei had greater impact on cities with higher centrality, especially in the Yangtze River Delta region, and smaller impact on the overall connectivity of the national railway network. For local people, quarantine had great impact on the outflow of local people to neighboring provinces.

Previous studies on the space of flows have mainly focused on a single flow element and have given less consideration to the joint effect of complex correlations among multiple flows. To fill this gap, in the context of the coordinated development of the urban agglomeration of the Yellow River Ji‐shaped bend (UAYB), in this study, three flows, namely population flow, logistics flow, and information flow, are selected to research the spatial patterns of the UAYB. The results show the following: (1) The information flow among cities in the UAYB is the strongest, followed by logistics flow and population flow. (2) Hohhot, Ordos, Yinchuan, and Taiyuan are the core cities and have attracted more flows to converge there; different flows have formed different central features. (3) Regarding the correlation of the three flows, information flow has a strong correlation with the other two flows. (4) From the perspective of the joint effects of the three flows considered, the hierarchy of UAYB is dominated by Hohhot and Taiyuan and sub‐dominated by Yinchuan and Ordos; four prominent city groups have been formed with these four cities as the center. On the basis of our results, we put forward some recommendations on the integrated development of cities at various levels within the UAYB to provide a reference for its spatial optimization strategy.

Despite the rising interest in understanding the various uses of space of flows, few studies have combined the traditional static urban development level with dynamic space of flows concepts. In the context of the coordinated development of the urban agglomeration of the Yellow River Ji‐shaped bend (UAYB), this study identifies the hierarchical spatial structure of the UAYB through a combination of Baidu migration big data and traditional data. The following conclusions can be drawn. (1) The cities with the strongest regional comprehensive power are Ordos, Taiyuan, Hohhot, Yinchuan, and Yulin, which cause the UAYB to present a significant “center‐periphery” spatial pattern. (2) The biggest population flows mostly occur between cities in the same province, while interprovincial population flows mainly exist between cities with the strongest comprehensive power. (3) The hierarchical spatial structure of the UAYB forms a multitree structure, with Ordos as the core. (4) The attractiveness of the UAYB is very weak, being only slightly attractive to individual surrounding provinces, while the population outflow index to economically developed areas is high. Several policy implications are proposed, which can provide important insights for planning intercity connections among the UAYB, in order to achieve more coordinated regional development.