Study On Influencing Factors Of Spatial Differentiation Of Residential Rental Price In Hefei

As a way to meet people’s living needs,the price of residential leasing not only reflects the supply and demand in the market,but also reflects the quality of life of lowincome people.On the one hand,the rental price is an important signal of the market,which regulates the effective supply of the whole rental market.Too high or too low residential rental sales ratio will bring different problems,and too low will restrain the supply side;If it is too high,some landlords will be greedy for rent and divide the nonconforming partition housing groups to rent,so as to increase the potential security risk of tenants.On the other hand,in order to achieve the goal of housing,it has become a very important issue to introduce appropriate policies to adjust the rental price.As one of the first pilot cities of leasing,Hefei needs to be cautious about how to regulate the price of rental housing,which plays an exemplary role for the latecomers.At present,the research on rental price is relatively rare,and due to different conditions in different regions,specific analysis is needed.Therefore,the research on the causes of spatial differentiation of residential rental price in Hefei has theoretical and practical significance.Referring to the relevant literature of predecessors,this paper constructs an index system with building characteristic factors,neighborhood characteristic factors,location characteristic factors and rental characteristic factors as the primary indicators,with a total of 21 secondary indicators.Taking Hefei as an example,the listing records of rental houses that can be obtained by crawlers on the Hefei housing rental transaction service platform are used to study the influencing factors,and the POI data of Hefei are obtained by using Gaode map programming interface.Use Arc GIS software to import house data points and location feature data points into Hefei administrative division map,and establish Hefei rental price map database.This paper analyzes the spatial distribution characteristics of residential rental price in Hefei by using Kriging interpolation method,and estimates the influence of each characteristic variable on rental price by using ordinary least square method and geographic weighted model respectively.It is found that the distribution of rental price of residential units in Hefei presents two characteristics: multi-core and decreasing from inside to outside.The smaller the distance from the three cores of the old urban area,Swan Lake and Binhu New Area,the higher the unit rental price,and vice versa.Secondly,the rental price of three areas in the study area is significantly higher than that of the surrounding areas,which are located near Dashu mountain,Swan Lake and the central business district.Among the three regions,Swan Lake has the highest rental price.Through the distribution study,it is also found that the residential rental prices in Hefei are normally distributed,and there is a spatial positive autocorrelation between residential rental prices.The characteristic variables were selected by OLS model regression to participate in GWR Model regression.Compared with OLS,the geographical weighted regression model fits well.According to the regression results of OLS model,on the whole,the greening rate,area and distance from kindergartens are significantly positively correlated with the residential rental price.The distance from the third class a hospital,cultural and entertainment facilities,key junior middle schools,universities,subway stations,office buildings,industrial parks,house age,floor ratio,orientation and payment method are significantly negatively correlated with the residential rental price.The plot ratio,park square,scenic spots,primary schools There is no significant correlation between the distance between primary medical treatment points,key senior middle schools,supermarkets and bus stops and residential rental prices;The distance between office buildings,key junior middle schools,universities and residential rental prices showed a U-shaped change,that is,first increased and then decreased.The results of GWR Model show that among the above explanatory variables,the influence direction of building area and residential age on residential rental price does not change with the change of spatial location,only the influence size changes,while the influence of other variables on house price has spatial differences in direction and size.Finally,according to the research results and the actual situation of Hefei,the corresponding suggestions are put forward.figure 21 table 10 reference 53...