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

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dc.contributor.authorHryhoruk, Pavlo
dc.contributor.authorKhrushch, Nila
dc.contributor.authorGrygoruk, Svitlana
dc.contributor.authorOvchynnikova, Olena
dc.date.accessioned2025-06-02T12:45:18Z
dc.date.available2025-06-02T12:45:18Z
dc.date.issued2023
dc.description.abstractThe 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
dc.description.sponsorshipState budget project of Khmelnytskyi National University “Modeling the strategies for safe development of innovation-oriented socio-economic systems”, project’s registration number 0122U001212.
dc.identifier.citationPavlo M. Hryhoruk, Nila A. Khrushch, Svitlana S. Grygoruk, Olena R. Ovchynnikova. Application of Multidimensional Statistical Analysis Technology for Grouping Regions by the Investment Attractiveness Level. Proceedings of 10th International Conference on Monitoring, Modeling & Management of Emergent Economy, Odesa – Ukraine, November 17 - 18, 2022. Edited by Serhiy Semerikov, Vladimir Soloviev, Andriy Matviychuk, Vitaliy Kobets, Liubov Kibalnyk, Hanna Danylchuk and Arnold Kiv. SCITEPRESS – Science and Technology Publications, Lda , Setúbal, Portugal. 2023. Pp. 145-155. DOI: 10.5220/0000159100003432
dc.identifier.isbn978-989-758-640-8
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/18434
dc.language.isoen
dc.publisherSCITEPRESS – Science and Technology Publications, Lda , Setúbal, Portugal
dc.subjectSocio-Economic Development
dc.subjectRegion
dc.subjectInvestment Attractiveness
dc.subjectClustering
dc.subjectK-Means Method
dc.subjectPrincipal Component Method
dc.subjectQuartimax Technique
dc.titleApplication of Multidimensional Statistical Analysis Technology for Grouping Regions by the Investment Attractiveness Level
dc.typeСтаття
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Кафедра економіки, аналітики, моделювання та інформаційних технологій в бізнесі