Abstract
Housing rents in cities is an important topic in the study of urban geography and an area that needs to be focused on to develop livable cities. As a critical component of the urban environment, the social environment influences housing rents and should not be neglected. However, little research examines how spatial heterogeneity in the social environment impacts housing rents. To address this gap, this paper performs a case study of Guangzhou, China and constructs a livability-oriented social environment conceptual framework that covers five aspects: educational background, occupation, unemployment, floating population, and rental household. It then develops datasets of the influencing factors such as the social environment as well as the building, convenience, physical environment, and location characteristics for 1,328 communities in Guangzhou. Ordinary least squares (OLS) and mixed geographically weighted regression (mixed GWR) model are then employed for further analyses. The results show that the mixed GWR model is more effective than the OLS and classical GWR models. Four aspects of the social environment—educational background, occupation, floating population, and rental household—have a spatially heterogeneous relationship with housing rents. The impact of the social environment on housing rents is more evident in suburban districts. The current findings help to better understand the spatial limitation of the social environment’s impact on housing rents, which enables policy makers to develop evidence-based, spatially differentiated affordable rental housing programs and provides theoretical support for the development of livable cities.
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Acknowledgments
This research was funded by the National Natural Science Foundation of China (No. 41871150 and 41801168), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (No. GML2019ZD0301), GDAS Project of Science and Technology Development (No. 2020GDASYL-20200104001), National Key Research and Development Program (No. 2019YFB2103101), Special Project of the Institute of Strategy Research for Guangdong, Hong Kong, and Macao Greater Bay Area Construction (No. 2020GDASYL-2020201001), and Open Fund of Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation(2018-02).
The authors declare that they have no conflict of interest.
Funding
This research was funded by the National Natural Science Foundation of China (No. 41871150 and 41801168), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (No. GML2019ZD0301), GDAS Project of Science and Technology Development (No. 2020GDASYL-20200104001), National Key Research and Development Program (No. 2019YFB2103101), Special Project of the Institute of Strategy Research for Guangdong, Hong Kong, and Macao Greater Bay Area Construction (No. 2020GDASYL-20200201001), and Open Fund of Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation(2018-02).
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Conceptualization, Yang Wang; methodology, Kangmin Wu and Yongxian Su; formal analysis, Yang Wang, Kangmin Wu, and Jing Qin; writing—original draft preparation, Yang Wang, Lixia Jin, and Yuling Zhang; writing—review and editing, Yang Wang, Lixia Jin, Gengzhi Huang, and Hong’ou Zhang; visualization, Yang Wang and Jing Qin.
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Wang, Y., Wu, K., Jin, L. et al. Identifying the Spatial Heterogeneity in the Effects of the Social Environment on Housing Rents in Guangzhou, China. Appl. Spatial Analysis 14, 849–877 (2021). https://doi.org/10.1007/s12061-021-09383-6
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DOI: https://doi.org/10.1007/s12061-021-09383-6