Urban spatial structure has a significant impact on the sustainable development of cities. An important step of urban spatial structure analysis is the identification of urban centers. From the perspective of urban function distribution, this study developed a theoretical framework of three layers for urban center identification. In the first layer, point-of-interest data were collected from geospatial databases and utilized to capture the spatial distribution of urban functions. In the second layer, the density-based spatial clustering of application with noise (DBSCAN) algorithm was employed to group points of interest into urban centers according to their inter-distances and urban functions. In the third layer, the spatial distribution of the identified urban centers was visualized by the ArcGIS platform. This framework was applied in the urban center analysis of Beijing. The results showed that Beijing is in the process of transitioning from monocentric to polycentric with urban functions distributed unevenly throughout the city. To facilitate this transition, strategies such as the construction of super-large communities, the development of branch campuses and higher-education parks, and the enhancement of modern culture industries should be considered for the 11 new towns of Beijing.

Culture-led regeneration projects (CRPs) have been identified as an effective means for enhancing the sustainable development of cities. Related topics have been investigated; however, relatively little information is known about what factors are critical for achieving success in these kinds of regeneration projects. Based on a literature review and five case studies, this study contributes to the body of knowledge by identifying 25 critical success factors (CSFs) for managing CRPs in China. A questionnaire survey was designed to evaluate the relative importance of these factors from practitioners’ and researchers’ perspectives. In addition, a factor analysis was carried out to group these CSFs into five categories, namely government policies and culture-led regeneration strategies, stakeholder management and financing support, technical solutions for CRPs, social security, and industry development. The results demonstrated that cultural value management, integrating cultural development with urban planning, adopting sustainable development principles, reconstructing the city image and brand, and the availability of culture-led planning methods played the most important roles in the success of CRPs. The findings of this study can help practitioners enhance their regeneration project performance.

To examine how cross-strata neighboring behavior in a mixed-income community can influence the consumption choices of individuals in low-income groups, and to improve the prediction accuracy of the consumption choice model of low-income groups for small sample sizes, we developed a support vector machine (SVM) algorithm based on the influence of neighboring behavior. We substituted the predicted latent variables into the SVM classifier and constructed an SVM prediction model with latent variables based on reference group theory. We established the model parameters using cross-validation and used low-income residents from a mixed-income community in Shanghai as study objects to empirically test the model’s performance. The results show that the SVM selection model with latent variables has good prediction accuracy. The proposed model’s accuracy was improved by 1.29% on the basis of the particle swarm optimization (PSO)-SVM model without latent variables, and by 19.35% on the basis of the SVM model with latent variables. The proposed model can be employed to predict the consumption choices of individuals in low-income groups. This paper offers a theoretical reference for investigating neighboring behavior in a mixed-income community and the consumption choices of individuals in low-income groups and is practically important for urban community planning systems.

Housing is one of the fundamentals for the society and housing affordability is one of the key factors related to the socioeconomic stability and development of a country. This research attempts to examine the issue of housing affordability from the micro household perspective in Cheng Du on a set of online questionnaire data. Including not only income, housing provident fund and other economic attributes, this study also focuses on the important implication of social capital for households’ house-purchasing decisions. The analysis shows that the household affordability is highly related to their social-economic conditions, such as their age, birthplace, income, and housing provident fund. This research provides new explanation for the homeownership condition in urban China. It helps deepen our understanding of the rationales behind the housing purchasing decision and will have meaningful implications to the practitioners.

By analogy with the electromagnetic radiation effect in physics, the commercial center has a radiation effect on housing price. The author establishes a model of the radiation effect of commercial center on housing price. Select the brand influence, scale and distance of the commercial center as the characteristic indicators, Hedonic Price Model (HPM) is used to solve the model. 200 houses in Dao Li District of Harbin were selected for research. The results show that brand influence has a significant influence on housing price, influence coefficient is 0.024. The distance of commercial center has significant influence on residential buildings, influence coefficient is −0.026. The scale of commercial center and brand influence has collinearity.

The housing security system has achieved considerable development since China established it in 1998. However, there are still many deficiencies in the indemnification housing system. This research attempts to examine the issue of low and middle-income group's satisfaction with indemnification housing policy from a micro perspective based on CGSS 2015 data. This research used two-step cluster analysis method to define low and middle-income groups, and a multiple linear regression model to explore the influencing factors. It is found that three factors: the housing area, socioeconomic status compared to peers, personal perceived social fairness significantly affect the satisfaction of the low and middle-income groups on the policy. This research gave explanations for satisfaction with indemnification policy among low and middle-group in China. On the basis of this, suggestions are provided for the formulation of policy.