Geodesic
Research of investment attractiveness based on cluster analysis
Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, Tome 19 (2023) no. 2, pp. 199-211 Cet article a éte moissonné depuis la source Math-Net.Ru

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The continued economic development of various countries or regions has resulted in increased competition in global markets, leading to a concentration of investors and skilled labour in locations with high investment attractiveness. The investment attractiveness of a given country or region is determined by its investment potential and risk, which are characterized by a combination of various significant factors.This paper seeks to develop an econometric model to estimate the amount of investment in fixed capital in a specific region, taking into consideration the linear relationship between the observed results, in order to determine the main conditions that are necessary for achieving stable and high economic growth. These conditions include the acceleration of investment activity and the implementation of major national reforms to ensure the effectiveness of the investment process. To assess the overall influence of the financial and economic indicators studied on the volume of investment, multiple regression analysis was utilized as the primary mathematical tool of the study. Furthermore, assumptions were made regarding the rank of the observations. To validate this hypothesis, a cluster analysis was conducted, grouping the observations into four clusters based on their results, depending on the volume of investment or the geographical characteristics of the region.
Keywords: investment attractiveness, cluster analysis, hierarchical regression model, multiple regression models, correlation analysis, least squares method. 
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D. Qi; V. M. Bure. Research of investment attractiveness based on cluster analysis. Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, Tome 19 (2023) no. 2, pp. 199-211. http://geodesic.mathdoc.fr/item/VSPUI_2023_19_2_a5/

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