Multidimensional statistical analysis of investment attractiveness and regional changes in the COVID-19 pandemic
| dc.contributor.author | Hryhoruk, Pavlo | |
| dc.contributor.author | Khrushch, Nila | |
| dc.contributor.author | Grygoruk, Svitlana | |
| dc.contributor.author | Ovchynnikova, Olena | |
| dc.date.accessioned | 2025-06-02T12:49:28Z | |
| dc.date.available | 2025-06-02T12:49:28Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This 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.description.sponsorship | e State budget project of Khmelnytskyi National University “Modeling the strategies for safe development of innovation-oriented socio-economic systems”, 162 project’s registration number 0122U001212. | |
| dc.identifier.citation | Hryhoruk P. M., Khrushch N. A., Grygoruk S. S., Ovchynnikova O. R. 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.uri | https://elar.khmnu.edu.ua/handle/123456789/18438 | |
| dc.language.iso | en | |
| dc.subject | socio-economic development | |
| dc.subject | regional analysis | |
| dc.subject | investment attractiveness | |
| dc.subject | clustering | |
| dc.subject | 𝑘-means method | |
| dc.subject | principal component analysis | |
| dc.subject | quartimax method | |
| dc.title | Multidimensional statistical analysis of investment attractiveness and regional changes in the COVID-19 pandemic | |
| dc.type | Стаття |
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