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Перегляд за Автор "Serhii Kozlovskyi"

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Academic management in war conditions: Chronicles of aggression and resistance experience of Ukrainian universities
(Суми: LLC “Consulting Publishing Company “Business Perspectives”, 2023-04-10) Serhiy Kozmenko; Yuriy Danko; Serhii Kozlovskyi
The full-scale aggression unleashed by the russian invaders against Ukraine on February 24, 2022, became an unexpected horror that struck the life of this European country. The war radically changed absolutely everything and for everyone. It has crippled the fate of millions of innocent people, claimed the lives of tens of thousands. The crazy decisions of the russian leadership and the influx of its hordes have turned a huge number of Ukrainian cities and towns into hell. Destroyed or damaged urban infrastructure, homes and businesses, hospitals and schools. These monsters did not spare the universities either.
Assessing the probability of bankruptcy when investing in cryptocurrency
(Суми: ТОВ «Консалтингова видавнича компанія «Перспективи бізнесу», 2022-09-14) Serhii Kozlovskyi; aroslav Petrunenko; Hennadii Mazur; Vira Butenko; Natalya Ivanyuta
The cryptocurrency market is not regulated, people and companies wishing to invest in cryptocurrency do not have the same protection as when investing in other assets. In the absence of information and regulatory laws, investors should decide if cryptocurrencies make sense for their financial goals and what kind of investment strategy to choose not to go bankrupt. The aim of the study is to determine the probability of “tail events” and to assess in this way the probability of bankruptcy when investing in cryptocurrency using the Monte Carlo method. The analysis is carried out on the period from September 1, 2014 up to July 1, 2022. Despite the fact that today there are more than 10,000 types of cryptocurrencies, Bitcoin was chosen to assess the probability of bankruptcy. The reason is that Bitcoin is the world’s first decentralized cryptocurrency and its data is stored in a long-term history, which allows testing a long-term investment strategy. Besides, Bitcoin has not gone through a period of persistent inflation that makes the result of testing a short-term investment strategy more reliable. To date, there are around 25 million Bitcoin holders, representing 42.2% of the crypto market. Almost all cryptocurrencies have been proven to follow Bitcoin. The probability of bankruptcy for a short-term cryptocurrency investment strategy is about 17%-23%. For a long-term cryptocurrency investment strategy, the probability of bankruptcy fluctuates from 13% to 16%. Contrary to popular belief, investors looking to avoid bankruptcy should prefer a long-term strategy. The best way for cryptocurrency investors to protect themselves from bankruptcy is to alternate long and short investment periods.
Assessment of public welfare in Ukraine in the context of the COVID-19 pandemic and economy digitalization
(Суми: LLC “Consulting Publishing Company “Business Perspectives”, 2021-03-18) Serhii Kozlovskyi; Iaroslav Petrunenko; Viktoriia Baidala; Viktoriia Myronchuk; 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.
Assessment of the Association Between Industrial Production Indicators and Business Expectations: Implications for Sustainable Economic Development
(Licensee MDPI, Basel, Switzerland, 2025-11-11) Serhii Kozlovskyi; Oleksandr Dluhopolskyi; Volodymyr Kozlovskyi; Anna Sabat; Tomasz Lechowicz; Ivan Zayukov; Larysa Oliinyk
Economic development and its sustainability are influenced not only by material, human, financial, and intellectual factors, but also by psychological factors. In particular, the levels of business expectations, trust, and confidence significantly affect the resilience of the economy, especially in crucial sectors such as industry and, more specifically, industrial production. Based on political, economic, social, and legal stability, businesses are likely to assess their opportunities more optimistically and realistically. This, in turn, enables them to look confidently toward the future and provides a foundation for investing in further development. Conversely, a decline in business expectations and confidence can slow socio-economic development, potentially leading to recession or depression. The purpose of the article is to identify the association between business confidence (Impact of the Business Confidence Indicator, IBCI) and the level of industrial production (Industrial Production Index, IPI), as a crucial aspect of ensuring sustainable economic development. A correlation–regression analysis conducted using Ukraine as a case study—a country candidate for EU accession—and statistical data from the State Statistics Service of Ukraine (SSSU) for the period from 1 February 2022 to 1 September 2024 demonstrated that there is a stable, positive, and strong relationship between IBCI and IPI levels (r = 0.7; D = 0.49). The constructed linear correlation model indicates that, with other factors held constant, a one-percentage-point increase in positive business expectations may lead to a 2.23-point rise in the industrial production activity of enterprises in Ukraine’s manufacturing sector. Furthermore, approximately 49.0% of the variation in industrial production levels is likely explained by changes in business expectations. Verification of the constructed regression equation and assessment of its parameters indicate that it is statistically reliable and consistent with real economic processes. Specifically, the Fisher coefficient (F = 5.30) exceeds the critical (tabular) value (Ft = 2.04), with Se = 0.45 and C_95% = 1.96; the causality test based on the Granger methodology revealed the presence of a causal relationship, indicating that the IBCI influences the IPI. The obtained statistical results for the applied models and tests are as follows: MDF (p < 0.05), KPSS (p > 0.10), Durbin–Watson ≈ 2.0, Breusch–Godfrey (p = 0.32), White (p = 0.41), ARCH (p = 0.27), and SER (p = 0.36). The constructed correlation–regression equation also allowed forecasting based on trend line modeling—how IPI levels will change depending on business confidence. According to the forecast, the IPI in Ukraine at the beginning of 2030 is expected to increase by 63.48 percentage points compared to the beginning of 2024, reaching 153.6%.
Comparison and Assessment of Factors Affecting the COVID-19 Vaccination in European Countries
(Kyiv: PHEI European University, 2021) Serhii Kozlovskyi; Daria Bilenko; Mykhailo Kuzheliev; Natalya Ivanyuta; Vira Butenko; Ruslan Lavrov
The Covid-19 spread has become a major challenge for humanity in the last decade. It was believed that the Covid19 vaccine development would have to end the pandemic. On the contrary, society has faced a new challenge which is that there are both countries that cannot afford to purchase the Covid-19 vaccine and inhabitants who do not trust new vaccine. Without adequate Covid-19 vaccination level, the global pandemic is not going to end. The object of this study is factors affecting the vaccination Covid-19 in European countries. The subject of the study is the statistical analysis methods to compare and assess of factors affecting the vaccination Covid-19 in European countries. The aim of the study is to find out which concerns about vaccination are more important and have an impact on the Covid-19 vaccination level in European countries. It is examined six factors; three of them relate to the government vaccine administration, the other three are about a public opinion on Covid-19 vaccination. The analysis is carried out in 22 European countries. The result of the study allows to state that public opinions factors are more important in pandemic and have more impact on the vaccination rate.
Dark personality traits and job performance of employees: The mediating role of perfectionism, stress, and social media addiction
(Суми: LLC “Consulting Publishing Company “Business Perspectives”, 2021-09-22) Mehmet Kiziloglu; Oleksandr Dluhopolskyi; Viktor Koziuk; Serhii Vitvitskyi; Serhii Kozlovskyi
The purpose of this study was to explore the indirect and direct relationships of Big5 and dark personality traits (i.e., extroversion, neuroticism, agreeableness, openness, conscientiousness, narcissism, Machiavellianism, psychopathy, sadism, and spitefulness) with job performance via perfectionism, stress, and social media addiction. A total of 514 private sector employees filled out a query sheet that included the assessment tools for the variables. Path analysis using a multiple mediation model indicated that neuroticism was negatively directly and indirectly related to job performance via stress and social media addiction. Machiavellianism and spitefulness were directly positively associated with job performance, and Machiavellianism-related higher social media addiction diminished the direct positive effect of Machiavellianism on job performance, indicating complex relationships. Furthermore, stress, social media addiction, and perfectionism were related to different personality traits positively and negatively. Findings of the present study suggest that an anti-social personality may promote higher job performance. However, job performance may be adversely affected by the adverse consequences relating to these traits. Professionals and firms that attempt to increase job performance should take anti-social personality traits and their complex effects on job performance into account.
Determinants of COVID-19 Death Rate in Europe: Empirical Analysis
(Vinnytsia: Institute of Feed and Agriculture of Podillya National Academy of Agrarian Sciences of Ukraine, 2021) Serhii Kozlovskyi; Daria Bilenko; Oleksandr Dluhopolskyi; Serhii Vitvitskyi; Olha Bondarenko; Oleksandr Korniichuk
At the end of 2019, the new virus called Coronavirus disease (COVID-19) spread widely from China all over the world (including Europe). Most countries in Europe at the beginning of 2020 have been quarantined. The aim of the work is to develop the system dynamics model for assessing the impact of the different factors on the COVID19 death rate in Europe. There were tested three hypotheses about factors of reducing the COVID-19 death rate with the help of linear regression analysis. The density of the population of European countries doesn’t affect the COVID-19 death rate. Also, COVID-19 death rate does not drastically affect mortality statistics. But the level of country’s economic development is a factor of COVID-19 death rate because in high developed countries the pandemic death rate is lower, regardless of the mechanisms of the spread of the disease and its impact on human health.
DETERMINATION OF THE RISK-FREE RATE OF RETURN ON AN INVESTMENT EFFICIENCY BASED ON THE FRACTAL MARKETS HYPOTHESIS
(Варшава: УНІВЕРСИТЕТ WSB, 2020) Andrii KozlovskyI; Daria Bilenko; Serhii Kozlovskyi; Ruslan Lavrov; Oleh Skydan; Natalya Ivanyuta
In determining the economic efficiency of an investment project, the rationale and choice of the discount rate is the most difficult step. The methods of investment assessment are built on the rate of return used to discount future cash flows back to their present value. To increase the accuracy of calculations and reduce the subjective assessments of experts, statistical methods are used. The market process is known to be stochastic. Therefore, investors know that the application of statistical methods is not practical, and thus prefer to use their ntuition and professional experience. The alternative group of methods such as the Fractal Markets Hypothesis is not widely used because it is difficult to carry out calculations according to the proposed formulas in practice. In this paper, the aim is to propose a method for determining the risk-free rate of return on an investment project based on the Fractal Markets Hypothesis for identifying long-term dependence and assessing the contribution to the total result of changes in inflation. The objective of the study is the determination of the risk-free rate of return on an investment project. The real risk-free rate is calculated as the existing inflation rate. The result of this paper is the definition of inflation boundaries for Poland, Ukraine and Russia, which may be used for determining the risk-free rate of return on an investment project.
Efficiency Assessment of Tax Measures in the European Countries Against the Effects of COVID-19
(Вінниця: Vinnytsia National Technical University, 2022) Daria Bilenko; Serhii Kozlovskyi; Natalya Ivanyuta; Viktoriia Baidala; Ruslan Lavrov; Volodymyr Kozlovskyi
Ongoing global Covid-19 pandemic is not only health crisis but the economic challenge. The future of society depends on how successfully the authorities find a balance between imposition of stringent restrictions and economic development. Tax policies play a role in reducing losses caused by the Covid-19 lockdowns. All countries are taking tax measures to mitigate the impact of the effects of Covid-19 pandemic on society. While the Covid19 pandemic has not yet been defeated, it is too early to draw conclusions about which tax measures against the effects of Covid-19 are efficient. On the other hand, correct trajectory of economic recovery can be missed if not to analyze the other countries experience. The object of this study is tax measures in the European countries against the effects of Covid-19. The subject of the study is the fuzzy set theory to assess the efficiency of tax measures in the European countries against the effects of Covid-19. The aim of the study is to find out which European countries have been more succeeded in tax measures implementing and type of their immediate crisis response. The analysis is carried out in 29 European countries. The result of the study allows to state that the number of tax measures against the effects of Covid-19 does not affect their efficiency and the most popular type of immediate crisis response has been the business cash-flow enhances.
Forecasting Demand for Eco-Friendly Vehicles Using Machine Learning Technologies in the Era of Management 5.0
(MDPI AG Switzerland, 2025-05-13) Serhii Kozlovskyi; Tetiana Kulinich; Taras Popovskyi; Tetiana Dluhopolska; Artur Kornatka; Yurii Popovskyi
Management 5.0 represents a new paradigm in business strategy and leadership that integrates sustainability, advanced digital technologies, and human-centered decision-making. The article explores the application of machine learning technologies for forecasting demand for eco-friendly vehicles as a key tool for enhancing manufacturers’ competitiveness. This research supports key UN Sustainable Development Goals (SDGs), including SDG 7 (Clean Energy), SDG 9 (Innovation and Infrastructure), SDG 11 (Sustainable Cities), and SDG 12 (Responsible Consumption). Based on an analysis of the European market from 2019 to 2023 and forecasting through 2027, a comprehensive approach was developed using ARIMA, Prophet, and Random Forest models. Empirical findings indicate that implementing predictive analytics can reduce inventory costs by 18–25% and optimize working capital by 15–20%. Model performance varied by market type: Random Forest excelled in smaller markets, while Prophet delivered strong results in trend-stable environments. The results confirm that accurate demand forecasting, supported by machine learning technologies, creates significant competitive advantages in the era of management 5.0 through production process optimization and improved market positioning.
Forecasting the competitiveness of the agrarian sector of Ukraine in the conditions of War and European integration
(Болгарія: Сільськогосподарська академія, 2023) Serhii Kozlovskyi; Tetiana Kulinich; Hennadii Mazur; Natalia Varshavska; Mariia Lushchyk; Illya Khadzhynov; Volodymyr Kozlovskyi
The war in Ukraine, since 24 February 2022, the processes of integration of Ukraine into the European Union in June 2022, the presence of powerful competitors in the European markets encourage the formation of a set of measures with the distinction of tools to ensure the competitiveness of the agrarian sector of the state. The necessity of ensuring the competitiveness of Ukraine’s agrarian sector on the basis of determining the competitive advantages dictate the urgency of scientific search for new methods, forms, tools for its enhancement, which will further promote the market relations in Ukraine and will have a direct impact on the well-being of the population. The aim of the work is to develop an innovative economic-mathematical model for assessing and fore-casting the level of competitiveness of the agrarian sector of Ukraine, based on fuzzy sets in the conditions of war and European integration. The object of the research is the process of ensuring the competitiveness of the Ukrainian agrarian sector. The subject of the research is methodological aspects of economic and mathematical modeling of the competitiveness of the agrarian sector of Ukraine in the conditions of war and European integration. The methodology of the study is based on the principles and mathematical provisions of fuzzy sets, which allows to use both qualitative and quantitative indicators of influence on the process under study. As a result of the research, based on fuzzy set theory, which allows taking into account both quantitative and qualitative factors of influence on the level of competitiveness, an innovative economic-mathematical model of valuation and forecasting of the level of competitiveness of the agrarian sector of Ukraine has been developed. The classification of factors influencing the level of agrarian sector competitiveness has been formed. The forecast (before the war and after the war), until 2026, of the level of competitiveness of the agrarian sector of Ukraine has been made, which will allow formulating a strategy of development of the agrarian sector of Ukraine in the conditions of war and European integration.
FORMATION OF THE MODEL OF SUSTAINABLE ECONOMIC DEVELOPMENT OF RENEWABLE ENERGY
(2023-11-04) Oleksandr Dluhopolskyi; Serhii Kozlovskyi; Yurii Popovskyi; Svitlana Lutkovska; Vira Butenko; Taras Popovskyi; Hennadii Mazur; Andrii Kozlovskyi
The article considers the use of sustainable energy as a potentially effective alternative energy source capable of replacing traditional natural fuels. The aim of the research is to develop a complex model of sustainable economic development able to promote introducing and expanding sustainable power engineering as potential alternative energy source, providing sustainable economic development, energy efficiency and reducing damages to the environment. The hypothesis lies in introduction of a model for sustainable economic development due to expansion of renewable energy which will result in economic growth, rise in energy efficacy and reducing hazards to the environment. A comparative analysis of costs and revenues of various types for using energy sources was carried out to estimate the economic efficiency and feasibility of renewable energy. The data analysis toolkit uses MS Power BI software, in which the data model was created. The conducted regression analysis provided valuable nu-merical and practical results on formation of the model of sustainable economic development of renewable power engineering. The research is based on the analysis of the impact “share of energy” on the level of electric energy import and CO₂ emissions. It is recommended to intensify efforts to develop renewable energy as a key direction for sustainable economic development to ensure energy security, reduce negative environmental impact and achieve global sustainable development goals.
Healthcare sector in European countries: Assessment of economic capacity under the COVID-19 pandemic
(Суми: LLC “Consulting Publishing Company “Business Perspectives”, 2022-04-07) Anastasiia Simakhova; Oleksandr Dluhopolskyi; Serhii Kozlovskyi; Vira Butenko; Volodymyr Saienko
The year 2020 showed certain unpreparedness of the world’s countries for the challenges of the COVID-19 pandemic due to the unpopular measures of closed borders and total quarantine. The leading social component that opposes a pandemic is the healthcare system. Thus, the purpose of this paper is to assess the ability of European countries to respond to the COVID-19 pandemic. The cluster modeling was performed using the STATISTICA 7.0 package. As a result of modeling, the studied countries were divided into 4 clusters. The first cluster included nine countries. According to the smallest distance, the core countries in this cluster are Ireland and Bulgaria. The second cluster included seven European countries. The core country in this cluster is Sweden. Five of the studied countries were part of the third cluster. The core country in this cluster is Estonia. The fourth cluster included economically developed European countries with a Scandinavian social economy model and countries with a transitive social economy model. The core country in the fourth cluster is Germany. The recommendations for European countries can be introducing educational activities at the state level among the population on the importance of vaccination against COVID-19, increasing the staffing of the healthcare system, conducting the audit on the effectiveness of using public funds, and developing the medical infrastructure.
How does strategic flexibility make a difference for companies? An example of the Hungarian food industry
(Суми: LLC “Consulting Publishing Company “Business Perspectives”, 2022-08-25) Allam Yousuf; Serhii Kozlovskyi; Jomana Mahfod Leroux; Abdul Rauf; Janos Felfoldi
IDENTIFYING MOMENTS OF DECISION MAKING ON TRADE IN FINANCIAL TIME SERIES USING FUZZY CLUSTER ANALYSIS
(Kyiv National Economic University named after Vadym Hetman, 2023) Vladyslav Kabachii; Roman Maslii; Serhii Kozlovskyi; Oleksandr Dronchack
The article investigates the problem of identifying trading decision points in financial time series using the Fuzzy C-Means (FCM) method. The authors argue that classical forecasting methods have limited effectiveness for decision-making in trading, as they do not take into account market structure and nonlinear patterns. The proposed methodology involves analysing time series using additional features derived from technical indicators (MACD, Stochastic) and further clustering based on FCM, which allows identifying market entry and exit points. In contrast to traditional approaches based on the assessment of forecasting accuracy (e.g. MAE, RMSE, MAPE), this study focuses on financially oriented metrics such as Net Profit, Max Drawdown, Win Rate and Profit Factor, which more accurately reflect the effectiveness of trading strategies in real market conditions. Experiments on the currency pairs EUR/USD, AUD/USD, USD/JPY, USD/CAD on daily and four-hour timeframes have demonstrated that the use of the proposed approach can improve the efficiency of trading strategies. The simulation results showed fairly high stable profitability results with low risks (drawdown). The proposed approach can be useful in developing automated trading systems and further research in the field of financial analytics.
IMPACT OF ENERGY INNOVATIONS ON THE UKRAINE’S ECONOMY: STRATEGIC DIRECTION AND MANAGERIAL PRACTICES
(Бієліна: Інститут Ойкос - дослідницький центр, 2022-09-30) Olena Trofymenko; Olha Ilyash; Serhii Voitko; Tetiana Dluhopolska; Serhii Kozlovskyi; Svitlana Hrynkevych
Diversification of energy sources and innovative development of the energy sector are one of the main directions for ensuring sustainable development and decarbonization of the economy. The aim of the article is to identify connections and interactions between the parameters of energy innovation development and economic growth. Factor analysis was used for this purpose. The results and conclusions determine the most influential factors among the 5 components identified in accordance with the functional areas of innovative development of the national economy in energetics. The analysis allowed to identify the main trends in the development of factors, which allowed to identify positive and negative changes. The egularities of the influence of certain factors on energy innovations have been determined, which has allowed to provide recommendations for their further development and regulation
INTELLECTUAL CAPITAL MANAGEMENT OF THE BUSINESS COMMUNITY BASED ON THE NEURO-FUZZY HYBRID SYSTEM
(Kyiv: National Economic University named after Vadym Hetman, 2022-08-20) Serhii Kozlovskyi; Petro Syniehub; Andrii Kozlovskyi; Ruslan Lavrov
The modern economy needs to address the issue of assessing intellectual capital as the basis for the development of market relations. The search for ways to solve this problem is possible based on the use of soft methods. The aim of the article is to develop a structural model for managing the intellectual capital of the business community based on an ppropriate neuro-fuzzy system. Developed on the basis of soft computing methods, an innovative model for estimating intellectual capital of the business community is able to process “non-rigorous”, incomplete or distorted input data, work with qualitative concepts, ambiguous and uncertain statements, perform operations with weak formalized economic parameters. The experimental results obtained made it possible to formulate the methods for evaluating the intellectual capital of business communities (or other similar economic systems) characterized by fuzzy relations between input and output parameters, considerable difficulties in formalizing the factors of influence, capability of using linguistic experts’ statements for building an information and analytical system, etc. The developed hybrid neuro-fuzzy system “Board” for evaluating intellectual capital of a business community enables to process both quantitative and qualitative input data, and was built up according to the criteria of digital economy transformation projects.
Modelling Regional Sustainable Development in Ukrainian Crisis and War
(Зальцбург:Європейська академія наук і мистецтв, 2023-01-01) Olena Shevchuk; Olha Ilyash; Glib Mazhara; Nadiia Roshchyna; Svitlana Hrynkevych; Ruslan Lavrov; Serhii Kozlovskyi
The article investigates the impact of force majeure crisis factors that appeared in the Ukrainian economy as a result of the global recession, the events of 2014-2021 (annexation of Crimea, temporary occupation of part of the industrial territories of Donetsk and Luhansk regions, military operations in Donbas, during the fight against pandemic (COVID-19), war in 2022 on the stable development of regions. Based on the analysis of official indicators of the State Statistics Service of Ukraine, it was proved that the said factors create additional multiplier and acceleration effects that adversely affect the dynamics of the gross regional product in the crisis conditions. It has been determined that the result of these effects is the transformation of crisis signals from a proactive to an active phase. The construction of a heat map of GRP correlation indicators made it possible to determine the existence of a disbalance between the economic and social development of the regions. Building a model of linear regression, allowed us to draw conclusions about the existing disbalance of GRP regions during the crisis and war
Neurolinguistic Exchange Rate Forecasting at War as a Bankruptcy Economic Protection Mechanism
(Подгориця : НВУ «ELIT – Економічна лабораторія досліджень перехідного періоду», 2024-01-15) Serhii Kozlovskyi; RODION POLIAKOV
The problem of forecasting financial indicators and exchange rates refers to one of the most difficult and topical economic and financial tasks. The interest and complexity of forecasting the currency exchange rate in Ukraine has increased manifold since the beginning February 24, 2022 of a full-scale war between Russia and Ukraine. Forecasting the exchange rate in Ukraine has become extremely important primarily for the existence of the national economy in military conditions and prevention of bankruptcy of enterprises. The object of research is the average exchange rate of the US dollar to the Ukrainian hryvnia. The subject of the research are the instrumental and economicmathematical methods of artificial intelligence, the theory of fuzzy sets, genetic algorithms, which enable a verified forecast of the exchange rate in Ukraine for a period of one year. The hypothesis of the study is the assumption that the exchange rate of the Ukrainian currency under the war conditions will fall 2-7 times within 1 year. The purpose of the research is to forecast the currency exchange rate in Ukraine in the conditions of war using methods of neurolinguistic modeling, based on a linguistic description of the factors influencing the exchange rate, as well as to obtain linguistic and quantitative forecast values to reduce the risks of bankruptcy. 16 factors of influencing the currency exchange rate in Ukraine grouped into economic, political, military factors have been identified and also described in a linguistic form. A neurolinguistic economic-mathematical model of forecasting the currency exchange rate in Ukraine was developed and a forecast of this indicator for 1 year was made. The results of the study suggest that the currency exchange rate in Ukraine can decrease more than twice within 1 year which can create a risk for the bankruptcy of enterprises. The dependence of the currency exchange rate of Ukraine on the state of the economy and the war was also plotted.
Relationship between net Relationship between net migration and economic tion and economic development of European opment of European countries: Empirical conclusions
(Суми: ТОВ «Перспективи бізнесу», 2024-03-18) Serhii Kozlovskyi; Tetiana Kulinich; Ihor Vechirko; Ruslan Lavrov; Ivan Zayukov; Hennadii Mazur
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

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