Ivan Zayukov

Given rapid changes in global financial and economic processes caused by rapid transformations in the institutional environment and the onset of force majeure circumstances, there is a need to develop new approaches to assessing the level of bankruptcy. Most models that estimate the probability of enterprise bankruptcy are based on internal information, while external information is used to a limited extent. The growing threat of force majeure requires using not only the existing discrete models but also those that consider the external environment of enterprises when assessing the probability of bankruptcy. The purpose of this study is to develop a model for preventingbankruptcy of Ukrainian enterprises in force majeure conditions based on the use of artificial intelligence methods ‒ the theory of fuzzy logic– which allows for a comprehensive assessment of bankruptcy prevention. The paper uses analytical data from the World Bank. The model consists of interrelated groups of factors: organizational, informational and legal, and economic. As a result, a comprehensive indicator of prevention of corporate bankruptcies (D) was calculated on a neurolinguistic scale from 0 to 10; the indicator was estimated for Ukraine (5.644) and Romania (4.520) (as countries close in terms of economic and geopolitical development). The simulation results show that the level of prevention of enterprises’ bankruptcy in Ukraine falls into the average interval.

In 2020, due to the COVID-19 pandemic, a moratorium was imposed on launching bankruptcy proceedings for enterprises in Ukraine. It was canceled in 2022 because of the war to encourage the company management to improve the efficiency of liquidity and solvency management, seeking ways to increase companies’ profitability and reduce the probability of bankruptcy. The study aims to determine the impact of liquidity on unprofitability, which can be considered an element in the management decision-making system to prevent bankruptcies of Ukrainian companies. The correlation-regression analysis was based on statistical data from Ukrainian companies for 2012–2019 and 2013–2020. The study found practically no connection between the unprofitability of Ukrainian companies and the decrease in the number of court cases in which a decision was made to recognize the bankruptcy of Ukrainian companies. On the other hand, there is a strong connection between Ukrainian companies’ liquidity and unprofitability. The constructed regression equation is statistically reliable and characterized by a high level of adequacy to real economic processes and phenomena. An increase in the general liquidity ratio by 1% leads to an increase in the unprofitability of Ukrainian companies by 0.0346%. According to the company size construct, the most substantial connection is recorded for medium-sized companies (the correlation coefficient is 0.927, the coefficient of determination is 0.860, and the built correlation-regression equation is characterized by statistical reliability and adequacy). In contrast, large, small, and micro enterprises have a weak and moderate connection.

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.