Viktoriia Baidala

The current state of development of Ukraine’s national economy involves strengthening the processes of transition to social market economy, aimed at accelerating the rates of economic growth of the country. The presence of peculiarities of activity of agrarian producers and increase of the socioeconomic importance of the agrarian sector of the economy contribute to the need to develop and substantiate the methodological conditions aimed at solving multidimensional and diverse problems of ensuring the development of agrarian economic systems. In the work, the directions of the formation of the mechanism of management of agrarian economic systems, which consist in the transition to a new quality level of the use of information and intellectual resources of the management system on the basis of modern information technologies and modeling, which allowed to develop a structural scheme of the mechanism of management of the agrarian sector of the economy. The understanding of the mechanism of management of agrarian economic systems, factors and functions of this mechanism are determined. The mechanism of management of agrarian economic systems should be considered as a system of principles, rules, norms and procedures, within the framework of which the goals and objectives of the agrarian economy are developed in accordance with the current economic laws. This mechanism should be in line with the ownership of the subjects of state domination of the region, organizational structures of management, market social and economic relations, natural conditions of economic activity and state economic policy concerning the development of agrarian production, etc., and also take into account the main economic relationships that exist between the individual structural components of the agrarian economic system.

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.

Organic farming is an essential approach to agriculture that seeks to reduce the negative impact of human activities on the environment and ensure the sustainability of food production. The study aims to determine the integral index of the development of organic farming and to create a clustering model of organic farming in European countries. As a research methodology, additive-multiplicative convolution was used to determine the integral index of organic farming development. Cluster analysis (the Ward method and the k-means clustering method) identified respective clusters. The integrated index is based on eight indicators of organic farming from the Eurostat database, 2012–2020, and ranges from zero to one. The following countries have the highest value of the integral index: Italy (0.57), France (0.54), Spain (0.54), Germany (0.45), and Turkey (0.47). Three clusters were identified according to eight indicators of organic agriculture. The first cluster includes countries-leaders in agricultural territories (about 2.1 million hectare) with the highest state financial support for agricultural research and development (1.1 billion euros). The second cluster includes countries with the most minor organic farming operators (50-100 operators). The third cluster includes countries with the highest index of annual income from the sale of farm products (200-220 points) but with the highest level of usage of dangerous pesticides (250 points). The heterogeneity of clusters allows one to determine the strengths and weaknesses of organic farming in European countries.