Assessment of General Region Level of Economic Benefit of Industrial Enterprises above Designated Size in China using Multivariate Statistical Techniques
In this paper, multivariate statistical techniques such as cluster analysis (CA), factor analysis (FA) and discriminant analysis (DA) methods have been used to assess and discriminate general region level of economic benefit of industrial enterprises above designated size in China. The FA yielded three factors explaining more than 88％ of the total variance under rotation sums of squared loadings condition: the first factor explained 35.583％, comprising number of times of turnover of working capitals and proportion of products sold; the second factor explained 31.994％, comprising ratio of total assets to industrial output value and ratio of profits to industrial cost; the third factor explained 20.857％, comprising only assets liability ratio. Hierarchical cluster analysis grouped 31 provinces, autonomous regions and municipalities into eight clusters. That of the DA was in agreement with the result obtained for the CA. This study demonstrated that multivariate statistical techniques are effective data mining methods for classification and evaluation of general region level of economic benefit of industrial enterprises above designated size in China.
Data Mining Multivariate Statistical Techniques Factor Analysis Cluster Analysis Discriminant Analysis Industrial Enterprises above Designated Size
Qi Wang
School of Life and Environmental Sciences, Wenzhou University, Wenzhou, China
国际会议
武汉
英文
319-323
2010-06-06（万方平台首次上网日期，不代表论文的发表时间）