Identifying the Spatial Heterogeneity in the Effects of the Social Environment on Housing Rents in Guangzhou, China

被引:1
|
作者
Yang Wang
Kangmin Wu
Lixia Jin
Gengzhi Huang
Yuling Zhang
Yongxian Su
Hong’ou Zhang
Jing Qin
机构
[1] Guangzhou Institute of Geography,Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application
[2] Guangdong Academy of Sciences,School of Geography and Planning
[3] Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),School of Tourism Sciences
[4] Sun Yat-Sen University,undefined
[5] Beijing International Studies University,undefined
[6] Research Center of Beijing Tourism Development,undefined
来源
Applied Spatial Analysis and Policy | 2021年 / 14卷
关键词
Mixed geographically weighted regression model; Guangzhou; Social environment; Housing rents; Spatial heterogeneity;
D O I
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中图分类号
学科分类号
摘要
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.
引用
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页码:849 / 877
页数:28
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