Application of Multidimensional Statistical Analysis Technology for Grouping Regions by the Investment Attractiveness Level

Pavlo Hryhoruk, Nila Khrushch, Svitlana Grygoruk, Olena Ovchynnikova, Olena Ovchynnikova

2022

Abstract

The paper is devoted to studying multidimensional statistical analysis tools for grouping regions by the level of their investment attractiveness and identifying changes in the structure of regions in the context of the continued destructive impact of the COVID-19 pandemic. An analysis of approaches to assessing investment attractiveness identified their strengths. Insufficient attention to the application of methods of multidimensional statistical analysis to a grouping of regions is stated. The authors consider the clustering of regions of Ukraine in the context of their level of investment attractiveness by the method of k-means and identify their structure according to the level of investment attractiveness in 2019 and 2020 in the context of the COVID-19 pandemic. To verify the correctness of the conclusions, the method of principal components with the rotation of the space of the selected factors by the quartimax technique. Further grouping of regions in the space of selected principal components showed results identical to the application of the cluster analysis method. Potential investors can use the research results to determine priority areas of investment. Also, the results are useful for local self-government bodies, as they provide information on the relative level of investment attractiveness of a specific region compared to other territorial units and also allow identifying weak points in specific areas of activity.

Paper Citation

in Harvard Style

Hryhoruk P., Khrushch N., Grygoruk S. and Ovchynnikova O. (2022). Application of Multidimensional Statistical Analysis Technology for Grouping Regions by the Investment Attractiveness Level. In Proceedings of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy - Volume 1: M3E2; ISBN 978-989-758-640-8, SciTePress, pages 145-155. DOI: 10.5220/0011932000003432

in Bibtex Style

@conference{m3e222,
author={Pavlo Hryhoruk and Nila Khrushch and Svitlana Grygoruk and Olena Ovchynnikova},
title={Application of Multidimensional Statistical Analysis Technology for Grouping Regions by the Investment Attractiveness Level},
booktitle={Proceedings of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy - Volume 1: M3E2},
year={2022},
pages={145-155},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011932000003432},
isbn={978-989-758-640-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy - Volume 1: M3E2
TI - Application of Multidimensional Statistical Analysis Technology for Grouping Regions by the Investment Attractiveness Level
SN - 978-989-758-640-8
AU - Hryhoruk P.
AU - Khrushch N.
AU - Grygoruk S.
AU - Ovchynnikova O.
PY - 2022
SP - 145
EP - 155
DO - 10.5220/0011932000003432
PB - SciTePress