| At present,many Chinese cities are experiencing rapid urbanization.In the process of urban expansion and renewal,the real estate market is booming,and the spatial differentiation of housing prices is becoming increasingly fierce.At the same time,the contradiction between supply and demand of public service facilities within the city is also increasingly prominent.The spatial disequilibrium allocation of public service facilities resources has influenced the residential location choice of buyers.This process has led to the increasingly significant spatial differentiation of urban housing prices,which has led to the formation and evolution of urban housing market price spatial fluctuations.This paper focuses on the topic of "accessibility of public service facilities affect housing prices",and follows the research idea of "status analysis--hypothesis proposed--empirical analysis--hypothesis verified--conclusion drawn".First of all,the main urban area of Jinan city is the research area,and the housing price characteristics of Jinan city are analyzed by using the housing price data collected by Anjuan.com.Secondly,four kinds of public resources such as education,medical treatment,public transportation and park green space are selected.Based on the analysis of the accessibility of public service facilities and the spatial characteristics of housing price,10 indicators are selected from the three aspects of location characteristics,architectural characteristics and neighborhood characteristics based on the traditional characteristic price theory,and a geographically weighted regression model is constructed to explore the influencing factors of housing price quantitatively.Explain the reasons for the spatial differentiation of housing prices.Thirdly,based on the training model of random forest method,the partial dependence graph is used to analyze and accumulate local effects,so as to explore the difference of influence of various public service facilities on housing prices and the interaction effect of accessibility of different facilities on housing prices.Finally,based on the research results,the equal allocation of public service facilities is proposed.Research shows:(1)The spatial distribution of public service facilities in Jinan is uneven,and there are large differences in the distribution of public service resources among residents.The accessibility of public service facilities generally presents a distribution trend of "decreasing from the center to the outside".There are significant differences in the accessibility of public service facilities in the 15-minute walking circle.The housing price in the region is extremely poor and has obvious characteristics of change.High-priced houses are mainly located in the southeast of the city.The housing price in the periphery of the city is relatively low,and the housing price shows an increasing trend from west to east.The spatial correlation between housing price and accessibility of public service facilities is significant.(2)There is spatial heterogeneity in the impact of public services on housing prices.The global regression results show that the regression coefficients of the accessibility of public service facilities that affect the housing price have all passed the significance level of 1%.The park accessibility has the most significant impact on the housing price,followed by hospital accessibility,followed by primary and secondary school accessibility.The GWR model is better than the global regression model in explaining the housing price.The regression results of the GWR model show that the impact of all variables on the housing price has great heterogeneity on the spatial scale.(3)There are differences in the importance of factors affecting housing prices in Jinan.The location characteristics have the most important impact on the housing price,and contribute 41.9% to the prediction of housing price;Secondly,the characteristics of public services in the neighborhood contributed 39% to the prediction of housing prices.The importance of the accessibility of public services to the housing price is in the order of education service accessibility,medical service accessibility,park accessibility,bus station accessibility and subway station accessibility,with the impact of 12.4%,10.6%,9.2%,4.5%and 2.3% respectively.When people choose houses,they pay more attention to the educational attributes of houses,followed by the accessibility of medical services and park services,and finally the traffic attributes of houses.(4)The accessibility of public service facilities has a threshold effect on the housing price.The impact of park accessibility on housing prices shows a trend of "increasing first,then flattening".When the park accessibility is less than 4,housing prices show an increasing trend;The impact of hospital accessibility on housing prices shows a trend of"fluctuating first,then increasing,and then stabilizing".When hospital service accessibility is at 1-2,housing prices show an increasing trend;The impact of educational accessibility on housing prices shows an inverted "U" trend of "increasing first,then decreasing".When the accessibility of educational services is less than 9,housing prices increase significantly;The impact of public transport accessibility on housing prices shows an inverted "N" trend of "first decreasing,then increasing,and then decreasing".When the accessibility of public transport stations is at 1-5,housing prices show a significant increasing trend.The threshold effect of the impact of a single public service facility on housing prices is confirmed.(5)Public service accessibility and location conditions have interactive effects on housing prices.The results show that,(1)the interaction between traffic accessibility and residential location attributes on housing prices is negative,and residential residents with poor location conditions have higher demand for traffic conditions;(2)In places with good residential location conditions,accessibility of education services and accessibility of park services have a positive impact on housing prices.When the housing location is poor,the high accessibility of education services and park services has no positive impact on the housing price. |
