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  • 标题:Investment attractiveness modeling using multidimensional statistical analysis methods
  • 本地全文:下载
  • 作者:Volodymyr Shinkarenko ; Maksym Matskul ; Dean Linok
  • 期刊名称:SHS Web of Conferences
  • 印刷版ISSN:2416-5182
  • 电子版ISSN:2261-2424
  • 出版年度:2019
  • 卷号:65
  • 页码:1-6
  • DOI:10.1051/shsconf/20196504007
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The article examines the investment attractiveness of the main branches of the food industry of Ukraine as a latent variable. For the first time in this area, a combination of various methods of multivariate statistical analysis is used for research (cluster analysis and factor analysis – the principal component method). These methods made it possible to use a large number of various indicators of the activities of industries to characterize investment attractiveness. As a result, the set of the branches was divided into three groupsclusters: “leaders” are the most attractive sectors for investment, “middle peasants” are attractive branches for investment, and “outsiders” are the least attractive branches for investment. The generalizing factors (principal components), which influence the resulting factor – investment attractiveness, were found. The interrelation of the generalizing factors and initial indicators is established. As a result of the research, it was possible to make an objective assessment of the investment attractiveness (as a latent indicator) of the main branches of the food industry in Ukraine, using instead of a multitude of indicators only three latent factors.
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