SPATIAL DIFFERENTIATION PATTERNS AND INFLUENCING FACTORS ANALYSIS OF HOUSING PRICES IN SHENYANG
XU Dan-meng1, LI Xin1, ZHANG Su-wen2
1. School of Public Administration, Nanjing Agricultural University, Nanjing 210014, China;
2. School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
Abstract Affordable housing plays a significant role for the wellbeing of people all over the world. However, against the background of housing commodification and market reforms since 1978 in China, housing price in many cities especially mega cities such as Beijing, Shanghai, Shenzhen and Guanghzou in China has undergone rapidly increasing. The fact negatively affects housing accessibility of many residents and leads to socio-spatial polarization of many cities. Driven by this concern, this research explores the spatial distribution pattern of housing prices and the influencing factors of Shenyang, a typical old industrial city in China. Based on POI data and the Kriging method, we firstly simulated the spatial distribution pattern of housing prices in Shenyang. Then, 11 independent variables were selected (consisting of community characteristics, public facilities and public transportations) to investigate mechanisms underlying the spatial differential pattern of housing prices of Shenyang, based on the Geographically Weighted Regression model (GWR). The results are as following. First, the housing price of different communities in Shenyang spatially forms a multi-center structure. Changbai region has replaced Shenhe and Heping districts as the new peak price area. Second, the independent variables show significant spatial heterogeneity. Variables related to community characteristics, such as ratio of green space, parking lot ratio and neighbourhoods management fees, have significant positive effects on housing price in general. Third, we found that urban housing market development of old industrial cities such as Shenyang has long been featured by the "strong government, weak market" development strategies.
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2021, Vol. 36 
