As Shanghai is committed to building a vibrant, thriving home for all residents, the pursuit of a high quality of life is correspondingly strengthening. In particular, housing has probably become an important indicator to measure the quality of people's lives and the house price is the key to the housing problem. This article analyses the annual date of the commodity house prices in Shanghai from 2001 to 2020 and aims to explore the affecting factors of commodity housing price, which include the number of ordinary high schools, medical and health institutions and cultural institutions in Shanghai, urban green coverage and residents' disposable income. Therefore, a multiple linear regression model of commodity house price has been established and successfully underwent the test of multicollinearity, heteroscedasticity and sequence correlation.

Xinyu Shen. Analysis of Commodity Housing Price in Shanghai Based on Multiple Linear Regression Model. Academic Journal of Business & Management (2022) Vol. 4, Issue 3: 83-86. https://doi.org/10.25236/AJBM.2022.040315.

[1] Ma Lili. Influencing factors and Empirical Analysis of real estate price in Kunming city: A Case study of housing market [D]. Kunming: Yunnan University of Finance and Economics,2008.Fangfang. Research on power load forecasting based on Improved BP neural network [D]. Harbin Institute of Technology, 2011.

[2] Dai Lei, Li Xueting. Analysis of Influencing Factors of Second-hand House Price Based on Multiple Linear Regression Model -- A Case study of Certain District in Chengdu city [J]. Henan Building Materials, 2019 (05): 80-82.

[3] Liu Meifang, Liu Weiyue. An Empirical Study on the Influencing Factors of Commercial housing Price in Tianjin -- Based on multiple Linear Regression Model [J]. Times Economics and Trade, 2017(16): 84-87.