住房价格与公共服务设施水平的关系研究 ——以苏州市主城区为例
Research on the Relationship between Housing Price and Public Service Facilities Level: A Case Study of Main Urban Area in Suzhou
邱煜卿
苏州科技大学，建筑与城市规划学院 硕士研究生
张振龙
苏州科技大学，建筑与城市规划学院 副教授，硕士生导师
摘要: 近年房价高企成为城市居民居住生活面临的棘手问题，受到了学者的广泛关注。大数据时代背景下，房价研究的详细数据
资料更为全面，且获取便捷。研究借助数据抓取工具，以2017年3月苏州市主城区普通二手商品房房价（POI）数据为研究
对象，运用探索性空间数据分析和空间插值方法，模拟苏州主城区房价空间分布特征，探索分布规律。同时,应用地理加权
回归模型建立房价与公共服务设施之间的线性联系，分析不同公共服务设施对房价的影响程度。结果表明，各类影响因素
与房价的关系在空间上呈现正负相关交替的现象，各类设施影响程度不同，房价空间差异是受多种因子共同作用的结果。
Abstract: Housing price is among the most pressing issues in urban China in recent years, and it has been widely concerned by scholars. In the
past, detailed data on housing price were difficult to obtain. In the background of big data, it is more convenient and comprehensive
to acquire. With the help of data acquisition tools, this study takes the data of ordinary second-hand commercial housing price (POI)
in the main urban area of Suzhou in March 2017 as the research object, and simulates housing price spatial distribution feature to
reveal regularities by using exploratory spatial data analysis and spatial interpolation method. Meanwhile, geographically weighted
regression (GWR) model is used to establish the linear relationship between housing price and public service facilities, aiming to
study the extent of the impact of different public service facilities on housing price. The result shows that the relationship between the
various factors and the price of house is positive and negative by turns and the impact of various types of facilities is different. Spatial
differences of housing price are the results of a combination of multiple factors.
关键词：住房价格、公共服务设施、地理加权回归、苏州市主城区
Keyword: Housing price，Public service facilities，Geographically weighted regression， Main urban area in Suzhou
中图分类号：TU981
文献标识码: A
[1]周亚杰. 北京居住与公共服务设施的空间分布差
异研究[D]. 北京：清华大学，2011.
ZHOU Yajie. Study on discrepancy in distribution
between housing and public facilities in case of
Beijing[D]. Beijing: Tsinghua University, 2011.
[2]方媛. 城市公共设施分布对商品住宅价格影响研
究[D]. 沈阳：沈阳建筑大学，2016.
FANG Yuan. Study on the influence of urban public facilities distribution on the price of commercial
property[D]. Shenyang: Shenyang Jianzhu
University, 2016.
[3]曾祎瑾，周红. 厦门市房价空间分布与基础设施
水平关系的研究[J]. 工程管理学报，2017（1）：
146-152.
ZENG Yijin, ZHOU Hong. Research on the
relationship between spatial distribution of housing
price and infrastructure level [J]. Journal of
Engineering Management, 2017 (1): 146-152.
[4]HAURIN D R, BRASINGTON D. School quality
and real house prices: inter-and intrametropolitan
effects[J]. Journal of Housing Economics, 1996,
5(4): 351-368.
[5]STEVENSON S. New empirical evidence on
heteroscedasticity in hedonic housing model[J].
Journal of Housing Economics, 2004 (13): 136-
153.
[6]ROSIERS F D, LAGANA A, THERIAULT M, et
al. Shopping centers and house values: an empirical
investigation[J]. Journal of Property Valuation and
Investment, 1996, 14 (4): 41-62.
[7]GLASCOCK J L，丰雷，刘迎梅，等. 公共交通易
达性对香港房价的影响分析——Hedonic模型的
应用[J]. 统计与决策，2011（3）：30-33.
GLASCOCK J L, FENG Lei, LIU Yingmei, et
al. Analysis of the impact of public transport
accessibility on Hong Kong' s housing prices: the
application of Hedonic Model[J]. Statistics and
Decision, 2011 (3): 30-33.
[8]任辉. 南京市住宅地价空间分异及其驱动的实证
研究[D]. 南京：南京农业大学，2011.
REN Hui. Empirical research on the spatial
variation of urban housing price and its driving
in Nanjing[D]. Nanjing: Nanjing Agricultural
University, 2011.
[9]陈笑双. 基于GIS的商品住宅价格空间分布研究[D]. 南昌：江西财经大学，2013.
CHEN Xiaoshuang. Study on the spatial
distribution of commercial housing price by
GIS[D]. Nanchang: Jiangxi University of Finance
and Economics, 2013.
[10]赵婷，杨旭艳. 黄土高原降水量空间插值方法研
究[J]. 地下水，2012，34（2）：189-191.
ZHAO Ting, YANG Xuyan. Research on
spatial interpolation methods of annual average
precipitation on Loess Plateau[J]. Ground Water,
2012, 34(2): 189-191.
[11]谷兴，周丽青. 基于地理加权回归的武汉市住宅
房价空间分异及其影响因素分析[J]. 国土与自然
资源研究，2015（3）：63-68.
GU Xing, ZHOU Liqing. Spatial differentiation
and influencing factors of Wuhan' s housing price
based on GWR model[J]. Research on Land and
Natural Resources, 2015(3): 63-68.
[12]刘贵文，王丽娟. 城市住房价格影响因素及其空
间规律研究——基于地理加权回归模型的实证
分析[J]. 技术经济与管理研究，2013（9）：81-
86.
LIU Guiwen, WANG Lijuan. Factors and
spatial variation research of housing pricebased
on geographically weighted regression
model[J]. Research on Technology Economy and
Management, 2013(9): 81-86.
