Academic Journal of Business & Management, 2022, 4(5); doi: 10.25236/AJBM.2022.040510.
Tiantian Li1, Xinyue Chen2
1School of Mathematics and Statistics, Hubei University of Arts and Science, Xiangyang, Hubei, China
2Cryptographic Engineering Institute, Inforamation Engineering University, Zhengzhou, Henan, China
Economic strength has always been an important indicator for evaluating a county and a city. In this paper, a total of 19 indicators are used to construct an evaluation index system for regional economic. Taking 21 cities and autonomous prefectures in Sichuan Province as samples, three principal component indexes are selected to reflect most of the information of the original indexes, and the ranking of their comprehensive economic strength is obtained. According to the cluster analysis model, the 19 selected economic impact indicators are divided into five categories through correlation. In each sub-category, combined with principal component analysis, the ranking of cities is obtained, and the final ranking of Sichuan's comprehensive economic strength is given by comparing the results of two rankings. Then we gave Suggestions for adjustment and development.
Comprehensive economy; Principal component analysis; Cluster analysis; KMO and Bartlett test
Tiantian Li, Xinyue Chen. Study on Economic Impact Indicators of Different Cities Based on Principal Component Analysis and Cluster Analysis. Academic Journal of Business & Management (2022) Vol. 4, Issue 5: 47-51. https://doi.org/10.25236/AJBM.2022.040510.
[1] Huang Yuting. Evaluation of economic development level in the Yangtze River Economic Belt based on cluster and factor analysis [J]. The Farmers Consultant, 2020(04): 242-243.
[2] Zhang Dong, Li Zhixiao, Li Zhenzhen. Empirical analysis on comprehensive evaluation of new urbanization level in Cangzhou city [J]. Economic Research Guide, 2020(07): 112+115.
[3] YU Na, CHEN Jiang-hua, YANG Cheng-gang. The Economic Development Evaluation of Yangtze River Delta Urban Agglomeration Based on Principal Component Analysis [J]. Journal of Hefei Normal University, 2019, 36(02): 31-38.
[4] Sichuan Provincial Bureau of Statistics. Sichuan Statistical Yearbook 2017. Website of Sichuan Provincial Bureau of Statistics: http://tjj.sc.gov.cn/
[5] SEOK J, WARREN H S, CUENCA A G, et al. Genomic responses in mouse models poorly mimic human inflammatory diseases[J]. Proceedings of the National Academy of Sciences, 2013, 110(9): 3507-3512.
[6] Bai Xue. Similarity Measures in Cluster Analysis and Its Applications [D]. Beijing Jiaotong University, 2012.
[7] Yang Fangwen, Yang Zihao. Evaluation of urban competitiveness in Anhui Province [J]. Co-Operative Economy & Science, 2018(11): 48-50.
[8] REN Ping, ZHOU Jieming. Research on the Comprehensive Appraisal for Regional Difference of Economic Development Level in Sichuan Province [J]. Journal of Sichuan Normal University (Natural Science), 2007(01): 102-105.
[9] WANG Na. Evaluation of economic development efficiency in Sichuan Province based on DEA model [J]. Times of Economy & Trade, 2018(14): 98-99.
[10] Shu Fuhua. Evaluation of Urban Economic Development Level in Sichuan Province Based on Principal Component Analysis [J]. Journal of Aba Teachers University, 2018, 35(04): 63-68.