Tetiana Kulinich

With the emergence of the global COVID-19 pandemic in 2019, a process of transformation of the modern economic system took place, which requires new approaches to assessing economic processes. One of such processes is the assessment of public welfare. The purpose of this study is to develop an approach to assessing the level of public welfare of the population of Ukraine in the context of the COVID-19 pandemic and economy digitalization. To solve this problem, the methods of artificial intelligence, in particular the method of fuzzy sets theory, which allows using the incomplete information and making high-quality forecast calculations, are used. The factors influencing the level of public welfare during the COVID-19 pandemic have been identified. These are the following factors: gross domestic product, poverty rate, welfare index, human development index, subsistence level, and indicators that characterize the COVID-19 pandemic (i.e. the total number of COVID-19 cases, the total number of deaths from COVID-19, and the total number of vaccinations from COVID-19 in Ukraine). Using fuzzy sets theory, an economic-mathematical model for assessing the level of public welfare in the context of the COVID-19 pandemic in Ukraine was built. Two-dimensional dependences of the level of public welfare of Ukraine in the context of the COVID-19 pandemic on indicators such as gross domestic product, subsistence level, and the total number of cases of COVID-19 in Ukraine were obtained. The results of the study established that the level of public welfare in the context of the COVID-19 pandemic on the 0-100 scale is predicted to be as follows points: 2021 – 17, 2022 – 23, 2023 – 27, 2024 – 19, 2025 – 35 and will not meet international standards.

The study aims to investigate the relationships between the volume of net migration and the economic development of individual European countries, which will make it possible to forecast the level of GDP and strengthen their migration policy. Correlation-regression analysis was used based on statistical data from Eurostat and the State Statistics Service of Ukraine for the period 2014−2021 for selected European countries (the EU-27 member states, Switzerland, and Ukraine). The correlation-regression analysis showed a relationship between the volume of net migration and the level of GDP. The linear correlation equations forecasted the value of the GDP level depending on the influence of a single factor – the volume of net migration. The attention is focused on the importance of migration, which ensures economic growth for Poland. It is attractive due to a simpler mechanism for moving immigrants than in other EU-27 countries, ease of language learning and easier adaptation, territorial proximity, and a higher standard of living compared to neighboring countries that were part of the Soviet Union. Thus, an increase in net migration to Poland by 1% will lead to an increase in gross domestic product by 1.43 million euros. Due to Russia’s war against Ukraine, net migration from Ukraine to Poland has increased significantly, potentially increasing Poland’s GDP in 2023 by 0.08% or 529.54 million euros.

Ukrainian universities operate under uncertain conditions and numerous challenges during wartime, significantly affecting their stability. This paper aims to identify and classify the key risks to the stability of Ukrainian universities during wartime and propose proactive tools for their mitigation. The study focuses on financial, personnel, and social risks, which are highlighted as the most critical under current circumstances. The data were sourced from the official websites of 10 universities, Open Budget, and the official websites of the Ministry of Finance of Ukraine and the State Statistics Service of Ukraine. The methodology combines theoretical analysis and statistical evaluation, including calculating marginal income – representing the portion of income covered by variable costs – and the operating margin ratio, defined as the ratio of marginal income to total income. Financial risks include a 7.9% reduction in education budget allocations, decreased subsidies, and insufficient state support. Personnel risks are analyzed through indicators, e.g., uncompetitive average hourly wages, leading to staff attrition and reduced motivation. The findings propose a multi-level classification of risks, categorizing them into external and internal with subcategories such as financial, personnel, and social ones. Non-traditional financial measures, such as unpaid leave and allowance reductions, were observed as short-term crisis strategies but require further evaluation to assess their long-term impact. The paper contributes to academic discourse by outlining challenges to university stability during wartime and providing a foundation for future research into effective risk mitigation strategies.