Spatial Heterogeneity of Public Service Facilities in the Living Circle and Its Influence on Housing Prices: A Case Study of Central Urban Dalian, China

The spatial layout of public service facilities (PSFs) markedly influences residents&rsquo: quality of life. Based on Baidu map data, spatial information on 27,552 PSFs across eight categories was collected for urban Dalian, China, and analyzed using the nearest neighbor index and nuclear density. Then, PSF accessibility across eight dimensions of residential quarters was calculated based on the cumulative opportunity method, and its impact on housing prices was analyzed. The results revealed the following: (1) The degree of spatial agglomeration for PSFs varied, with that of business facilities being higher than that of other public welfare facilities. The distribution of business facilities was characterized by a dense center and sparse periphery, whereas public welfare facilities were laid out in a relatively balanced &ldquo:multi-center&rdquo: distribution across the study area. (2) Significant spatial differences in the number and types of accessible resident facilities were identified. The number of accessible PSFs in the core area of central urban regions was large and the types were relatively complete, whereas the accessible PSFs in the western and northern marginal areas were limited in number, few in type, and lacking across certain categories, such as educational facilities and life services. (3) The spatial distribution of PSF accessibility was unbalanced. The accessibility of various PSFs in the Shahekou District was the highest, followed by that in the Zhongshan, Xigang, and Ganjingzi Districts. (4) The accessibility of educational, sport, and cultural facilities, and the total accessibility and greening rate of residential areas were the most significantly positively correlated with housing prices: however, the number of households in residential areas and the distances between residential areas and large shopping centers were significantly negatively correlated. Our findings will expand the research perspective of PSFs, provide a basis for meeting residents&rsquo: needs and a rational allocation of PSFs, and provide references for people&rsquo:s decisions to buy houses.