Open AccessAnalysing the Differentiation of Housing Price Influence Based on PCA Clustering-Entropy Weight Method: A Case Study in Sichuan
Author(s) -
Xuedong Liang,
Qian Lü,
Qian Lü
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/780/7/072054
Subject(s) - real estate , renting , cluster analysis , differential (mechanical device) , business , china , rental housing , economics , finance , geography , computer science , engineering , archaeology , machine learning , political science , law , aerospace engineering
The immobility of real estate products and the regional nature of the consumption of real estate products make the real estate industry have obvious regional characteristics. The current policy adjustments in the real estate market emphasize differentiation, that is, the regulation methods of each city are becoming more and more different, not only because of the policy of the city, but also the policy of the district. For exploring the basis of differential regulation, the article takes Sichuan Province of China as an example. Through the selection of four first-level indicators and thirteen secondary indicators, 21 cities (districts) are divided into four types of areas. Then the entropy method is used to obtain the factors that affect the housing prices in each category. Based on these, it is suggested to improve the real estate market related policies from the three aspects: promoting the construction of the housing rental market, guiding the rational expectations of buyers and correctly guiding the flow of people.