In the context of an overall improvement in the national economy, residents' demand for nutrition and health has been increasing. An industry that provides healthy eating plays an increasingly important role in urban development. Few studies, however, have focused on the relationship between the urban road network structure and the vitality of the healthy catering industry (VHCI). Based on social media data and urban traffic network data, in this study, we explored the impact mechanism of street centrality on the VHCI through a case study of Jinan, China, using geographic detectors and multiscale geographically weighted regression (MGWR) methods. The results show the following: First, the vitality of the catering industry in the main urban area of Jinan has multicore spatial distribution characteristics, and the high-value areas of the vitality of the catering industry are highly matched with the main business districts in the city in space. Second, we found clear spatial differences in street centrality between the walking and driving modes. With an increase in the search radius, the trend of high-value areas closely gathering in the urban center became clearer. The distribution of betweenness was observed from sheet to grid, and the multicenter structure of straightness was more prominent. Third, differences in the residents' perception of the road network structure caused by different travel modes affected their choice of dining places. In the driving mode, betweenness and straightness had a greater impact on the vitality of the catering industry, and the effect of closeness in the walking mode was more obvious. Fourth, the influence of street centrality on the vitality of the healthy catering industry had obvious spatial heterogeneity. In the walking mode, the spatial heterogeneity of straightness was the strongest, followed by betweenness, and closeness was the weakest; in the driving mode, the spatial heterogeneity of closeness was the strongest, followed by straightness, and betweenness was the weakest. From the perspective of residents' travel, the results of this study revealed the influence mechanism of urban road network characteristics on the VHCI. This information can aid planning for urban space optimization and improve residential living quality.

A resource-based city is a type of city characterized by the exploitation and processing of natural resources as the leading industry in the region. Such cities provide essential resources for China’s economic development and support long-term rapid economic growth. However, resource-based cities (RBCs) face challenges, including resource depletion, economic recession, environmental pollution, and ecological damage, to which not enough attention has been paid. In the context of China’s increased focus on environmental protection and the economy, improving industrial ecological efficiency of RBCs has become ever more important. In the present study, the Super-SBM model was used to measure the industrial ecological efficiency of 114 RBCs in China from 2003 to 2016. The results show that during the study period, the industrial ecological efficiency of RBCs in China improved significantly, particularly in the central and western regions. The results from a Tobit model show that appropriate environmental regulation and financial pressure have a positive impact on the industrial ecological efficiency of RBCs. However, when faced with the dual pressures of environmental regulation and financial difficulty, improvement in industrial ecological efficiency was inhibited. The impact of environmental regulation and financial pressure on industrial ecological efficiency of cities in different regions and development stages and with different resource types shows heterogeneity. In accordance with the study findings, differentiated measures and suggestions are proposed to improve the industrial ecological efficiency of RBCs.

In the existing literature on the correlation between street centrality and land use intensity (LUI), only a few studies have explored the disparity of this correlation for different types of LUI and the differences across various locations. In response to the above shortcomings, in this study, the main urban area of Jinan, China, was taken as an example, and the disparity and spatial heterogeneity of the correlation between street centrality and LUI were explored for different categories of land use. The multiple centrality assessment (MCA) model was used to calculate the closeness centrality, betweenness centrality, and straightness centrality of the traffic network. Based on the floor area ratio (FAR) of each parcel, the utilization intensities of the residential, industrial, commercial, and public service land uses were measured. Employing the kernel density estimation (KDE) method, the street centrality of the traffic network vis-à-vis the urban LUI was rasterized into the same spatial analysis framework. The Pearson correlation coefficient and geographically weighted regression (GWR) were used to measure the correlation between the two variables and the spatial heterogeneity of the correlation, respectively. The results showed that traffic network street centrality strongly correlated with the LUI of the residential, commercial, and public service land use types, but it had a very weak association with the LUI of industrial land use. The GWR results also confirmed the spatial heterogeneity of the correlation. The results of this research highlighted the important role of traffic network street centrality in understanding the urban spatial structure. The study also helped to explain the dynamic mechanism of the road network form and the topological structure of urban spatial evolution.

Existing research underscores the significance of block form in fostering urban vitality. However, there is a dearth of evidence on its influence on the catering industry’s vitality. Additionally, current studies investigating the correlation between block form and urban vitality have frequently neglected disparities among various types of blocks with dominant functions. We employ a multi-scale geographically weighted regression and a geographic detector to elucidate the effects of block form and the heterogeneity of blocks with dominant functions on the catering industry’s vitality. Our findings suggest that the suitable block form can mitigate the catering industry’s reliance on factors such as the regional population and public transportation infrastructure, to a certain degree. High-rise buildings and irregular block plans positively influence the catering industry’s vitality, while the effects of block area, building density, and functional density display considerable spatial heterogeneity. Commercial blocks are most influenced by block form, whereas public service blocks are least affected. The methodology of this study can be replicated globally to guide urban planners in judiciously allocating commercial facilities, based on the varying spatial form requirements of different blocks, thereby fostering a vibrant city.