城市服务设施更新对房价异质性作用研究——以成都市为例  

Study on the Impact of Urban Service Facilities Renewal on the Heterogeneity Housing Prices:Taking Chengdu City as an example

作　　者：李晨阳 梁娟珠[1] LI Chenyang;LIANG Juanzhu(Digital China Research Institute (Fujian),Fuzhou University,Fuzhou 350003,China)

机构地区：[1]福州大学数字中国研究院(福建),福州350003

出　　处：《科技和产业》2022年第6期315-320,共6页Science Technology and Industry

基　　金：福建省科技计划项目(2020L3005)。

摘　　要：以2013—2021年成都市二手房价格数据和城市服务设施POI数据为例,探究1 km×1 km空间格网尺度下房价和城市服务设施的时空关系演化。研究表明:城市服务设施和居住空间分布一致,沿交通干线呈“米”字状放射特征,城市服务设施逐步丰富但速度小于房价增长;城市服务设施分布与房价相关性显著,却逐渐减弱,尤其营利性设施相关系数降幅更为明显,区域内部房价分异态势日益加深;地理探测器模型能够有效识别出不同变量对房价影响差异,人口密度、建筑年份、路网密度影响最强,初级教育设施与其他设施交互对房价解释力显著增强。Taking the price data of second-hand houses and the POI data of urban service facilities in Chengdu from 2013 to 2021 as an example,the spatio-temporal relationship between house prices and urban service facilities under the spatial grid scale of 1 km×1 km is explored.The results show that spatially,the distribution of urban service facilities and living spaces was consistent,and the overall“meter”radial features along the traffic trunk line are the same.The correlation between the distribution of urban service facilities and housing prices was significant,but it was gradually weakening,especially the decline in the correlation coefficient of for-profit facilities was more obvious,and the differentiation of housing prices within the region was deepening.The geographical detector model could effectively identify the differences in the impact of different variables on housing prices,with the strongest impact on population density,building year,and road network density,and the interaction between primary education facilities and other types of interaction has higher interpretation of housing prices.

关 键 词：时空异质性 地理探测器 城市服务设施 房价 

分 类 号：K902[历史地理—人文地理学] F129.9[经济管理—世界经济]