Multidimensional statistical analysis of investment attractiveness and regional changes in the COVID-19 pandemic

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dc.contributor.authorHryhoruk, Pavlo M.
dc.contributor.authorKhrushch, Nila A.
dc.contributor.authorGrygoruk, Svitlana S.
dc.contributor.authorOvchynnikova, Olena R.
dc.date.accessioned2024-10-07T10:22:24Z
dc.date.available2024-10-07T10:22:24Z
dc.date.issued2023
dc.description.abstractThis paper delves into an in-depth exploration of multidimensional statistical analysis techniques aimed at categorizing regions based on their levels of investment attractiveness, while also scrutinizing the evolving regional structures in light of the persistent and adverse effects of the COVID-19 pandemic. Through a comprehensive review of various approaches to assessing investment attractiveness, the study highlights their respective strengths. Notably, the research underscores the underutilization of multidimensional statistical analysis methodologies in the regional grouping context. The authors undertake the task of clustering Ukrainian regions based on their investment attractiveness levels, employing the well-regarded 𝑘-means method. This analysis extends to the identification of the regions’ investment attractiveness structure in both 2019 and 2020, amid the COVID-19 pandemic. Substantiating the validity of their findings, the authors employ the principal component method in conjunction with the quartimax technique to rotate the space of selected factors. Remarkably, the subsequent regional grouping in this transformed principal component space mirrors the outcomes of the cluster analysis method. The research outcomes hold practical value for potential investors, enabling them to pinpoint key investment areas. Furthermore, local self-governing bodies stand to benefit from these findings, gaining insights into specific regions’ relative investment attractiveness levels compared to their counterparts, while also uncovering vulnerabilities in distinct activity domains
dc.identifier.citationPavlo M. Hryhoruk, Nila A. Khrushch, Svitlana S. Grygoruk, Olena R. Ovchynnikova. Multidimensional statistical analysis of investment attractiveness and regional changes in the COVID-19 pandemic. CEUR-WS. 2023. Vol. 3465 – pp. 150-167. URL: https://ceur-ws.org/Vol-3465/paper17.pdf
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/16905
dc.language.isoen
dc.publisherCEUR-WS
dc.subjectsocio-economic development
dc.subjectregional analysis
dc.subjectinvestment attractiveness
dc.subjectclustering,
dc.subject𝑘-means method
dc.subjectprincipal component analysis
dc.subjectquartimax method
dc.titleMultidimensional statistical analysis of investment attractiveness and regional changes in the COVID-19 pandemic
dc.typeСтаття
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Кафедра фінансів, банківської справи, страхування та фондового ринку