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Research On The Spatial Variation Of Hedonic Prices Of Hangzhou Office Rent Price Based On Geographically Weighted Regression Model

Posted on:2018-04-15Degree:MasterType:Thesis
Country:ChinaCandidate:M Y YuFull Text:PDF
GTID:2359330518477502Subject:Engineering Management
Abstract/Summary:PDF Full Text Request
With the continuous improvement of urbanization,the urban economy grows up rapidly,social division and collaboration of labor go to further promotion and improvement,given birth to a large number of new office space and demand.However,the supply of office space is far beyond the current demand,Hangzhou,as with other second-tier cities,new office supply is out of the demand,which the size of city,the economic structure of the fundamentals create does not match the growing stock market.Exploring the price characteristics of urban office buildings,mastering the influence of office rent variables,and analyzing the characteristics of spatial differentiation of urban office space will help the market parties grasp the demand quickly,and promote the long-term development,operation and management of office buildings.This paper firstly reviews the literatures of the hedonic price study,discusses the basic theory and calculation method of the hedonic price model and the geography weighted model,and summarizes the current research on the office buildings.This paper summarizes a set of price variable system which is suitable for China's office rent by combining domestic and foreign research results,practical experience,domestic office market characteristics and relevant professionals' experience accumulation.Based on data characteristics,each hedonic variable is divided into internal and external variable.Then,the paper analyzes the distribution and composition of office buildings in Hangzhou,analyzes the characteristic rents of office rents by OLS method,discusses the regression effect of four kinds of functions,gradually studies the fitting results under different function forms,and compared the linear logarithmic function model with the characteristics of automatic linear modeling,and finally builds the hedonic price regression model is established under OLS method.The variables entering the regression are 3 internal characteristics(property service,elevator number,building plane)and 3 external characteristics(Distance from Wulin Square,distance from the civic center,traffic conditions).Based on the best hedonic price function,the GWR model,which heterogeneous spatial regression,is established.The results show that the GWR model of Hangzhou office rent is better than the traditional hedonic price model of the return effect.In view of the internal characteristics,the larger the building standard layer area has a significant positive effect on the rental price in the traditional old city office space,and the opposite is true to the urban new district(Binjiang District,Qianjiang New City).The impact of the rental price is very significant of the property service for the same as that of Hangzhou,while the traditional district core area of the price increase is more obvious,the city's new district to enhance the price is weak;the number of elevators have a more significant impact on the Hangzhou office rent prices,the rental price of the promotion embodied in the Wulin square around the traditional business district core area.From the external characteristics of view,from the Wulin Square distance variables on the various regions are more significant,in line with the Hangzhou City to Wulin Square as the center of the expansion of the general decline in the price of rental judgments;and distance from the civic center on the rental price is limited,especially in the core area of the traditional business district,the same as the Qianjiang New City of Binjiang District,as a new district;traffic conditions(that is,the number of buses)on the Binjiang District office rent price impact is very significant,the other five traffic conditions are relatively uniform.
Keywords/Search Tags:Hangzhou, Office Rents, Hedonic Price Model, Geographically Weighted Regression, Ordinary Least Squares
PDF Full Text Request
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