title: Research of investment attractiveness based on cluster analysis
metadata.name: dc.contributor.author
metadata.value: Qi, Dongfang
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Bure, Vladimir M.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2023-08-22T17:05:25Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2023-08-22T17:05:25Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2023-06
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Qi D., Bure V. M. Research of investment attractiveness based on cluster analysis. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2023, vol. 19, iss. 2, pp. 199–211.
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/spbu10.2023.206
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/43828
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: 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.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 19; Issue 2
metadata.lang: -
metadata.name: dc.subject
metadata.value: investment attractiveness
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: cluster analysis
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: hierarchical regression model
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: multiple regression models
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: correlation analysis
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: least squares method
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Research of investment attractiveness based on cluster analysis
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 06.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/43828/1/06.pdf
resources.format: Adobe PDF
resources.size: 958,9 kB