The Urban Competitiveness of Southwest Cities in China Based on Factor Analysis
Download PDF


Data mining
Factor analysis
Urban competitiveness



Submitted : 2022-10-31
Accepted : 2022-11-15
Published : 2022-11-30


Factor analysis is an important way of data mining which can be performed using MATLAB, Python, and so on. We studied the urban competitiveness of Southwest cities in China using factor analysis. Two factors were extracted among 22 original variables. The factor score of cities was obtained using Python and were classified into three categories: Chongqing, Chengdu, Kunming and Guiyang are the first-tier cities; Baoshan, Pu’er, Lincang and Lijiang cities are of the lowest tier; the remaining cities belong to the second tier.


Si S, Sun X, (eds) 2020, Mathematical Experiment and Modeling in Python, Science Press, Beijing.

Wu X, 2019, Multivariate Statistical Analysis with R and Python, Renmin University of China Press, Beijing.

Xue W, 2007, SPSS Statistical Analysis Method and Application. Publishing House of Electronics Industry, Beijing.

Ni P, 2004, China’s Urban Competitiveness Report: Making Chinese Cities Win-Win, Social Science Literature Publishing House, Beijing.

Sun L, Tan C, Hou S, 2007, Comprehensive Analysis of the Strength of Urban Development in Hebei Province, Journal of North China Institute of Aerospace Engineering, 17(3): 33–35.

Zheng R, 2005, Factor Analysis Method for Performance Evaluation of Central City Competitiveness, University of Shanghai for Science and Technology, 27(6): 555-559.

Chu L, Mu N, 2020, Research on The Competitiveness of Anhui Province Based on Factor Analysis. Economic Research Guide, 2020(13): 119–121.

Sun H, Song R, The Application of Factor Analysis in City's Competitiveness, Green Economy, 29(7) 128–131.

Wang X, 2017, Applied Multivariate Analysis to Statistical Analysis, Shanghai University of Finance and Economics Press, Shanghai.

2020 China City Statistical Yearbook, 2021, China Statistics Press, Beijing.