Наукові публікації у періодичних виданнях, які індексуються у WoS

Постійне посилання колекціїhttps://dspace.krok.edu.ua/handle/krok/120

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  • Ескіз
    Документ
    Financial support and forecasting of food production using economic description modeling methods
    (FINTECHALLIANCE LLC, 2021) Rumyk, I.; Laptev, S.; Seheda, S.; Akimova, L.; Akimov, O.; Karpa, V.; Румик, Ігор Іванович; Лаптєв, Сергій Михайлович
    The article considers the financial programs used by the state to support food production based on the use of methods of economic descriptive modeling. It is established that the interpretation of the essence and strategy of financing in practice has quite different approaches. It has been proven that the formation of an effective system of financing food production involves the relationship and effective redistribution between different sources of financial resources. It is substantiated that agriculture has all the prerequisites for productivity growth provided that investment in the Ukrainian agricultural sector increases and effective budget financing. In this regard, the features of food production based on the use of descriptive modeling capabilities using the software package Statgraphics XVII Centurion. Because of the analysis, it is established that the main parametric criterion, which depends on the level of food production in the country as a whole and individual regions, determines the indicator of agricultural production, quantitative parameters of which are taken as a basis for calculating self-sufficiency, import coverage, calories, consumption, profitability and others. Estimation of this indicator by means of modeling allowed to make the forecast of dynamics of change of its volumes for the next twelve time periods for the purpose of preliminary definition of level of food production. For this purpose, the economic and mathematical tools of estimation of forecast dynamics of change of volumes of agricultural production for the future periods are used. Modeling of the indicator of agricultural production per person per year was carried out by research on the normality of distribution using Kolmogorov Smirnov, Anderson - Darling compliance tests and a modified Kolmogorov - Smirnov test. According to the results of comparative analysis of seventeen different models and five compliance tests, it was found that most of the statistical tests are quadratic model, based on which the projected volumes of agricultural production per person per year and calculated for each forecast year (period) with a reliability of 95% lower and upper limits of the studied indicator. It is established that by 2030 in Ukraine with a high probability the growth trend of agricultural production will continue, and at a high rate. The article outlines the benefits of using economic modeling methods in the study of a particular problem
  • Ескіз
    Документ
    Methodology of corporate financial diagnostics in the period of a crisis
    (MAGNANIMITAS Assn., 2021) Mihus, Iryna; Denysenko, Mykola; Rumyk, Igor; Pletenetska, Svetlana; Laptiev, Mykhailo; Kupriichuk, Vasyl; Мігус, Ірина Петрівна; Румик, Ігор Іванович; Плетенецька, Світлана Михайлівна; Лаптєв, Михайло Сергійович
    The article is devoted to corporate financial diagnostics' peculiarities in the context of ideas about organizational crises. The economic signs of a crisis enterprise are considered in conjunction with the critical signs of a crisis: a threat to priority goals, suddenness, and lack of time for making anti-crisis decisions. The study of scientific ideas about the crisis, in conjunction with the enterprise's financial characteristics, is a necessary stage in the formation of the methodology of corporate financial diagnostics.
  • Ескіз
    Документ
    Formalization of the influence of exogenous and endogenous processes on the financial activities of agribusiness enterprises
    (Fintech Aliance LLC, 2024) Rumyk, Ihor; Galetska, Tetiana; Klymchuk, Oleksandr; Tkalenko, Svitlana; Derii, Zhannae; Seheda, Serhii; Румик, Ігор Іванович; Ткаленко, Світлана Іванівна
    The functioning of business structures in the agricultural sector has recently become significantly more complicated. In today's conditions, it is becoming more and more difficult to develop security strategies for agribusiness enterprises, because factors that have arisen relatively recently, especially of an external nature, have a significant negative impact on the financial activities of enterprises. In order to make optimal financial decisions, the entire toolkit, developed and tested by many years of business experience in the agricultural sector both abroad and in the middle of our country, should be used. One of these methods is economic descriptive cognitive modeling, which allows to analyze external and internal factors influencing the activities of enterprises, evaluate the strength of their interaction, and graphically display cause-and-effect relationships in a dynamic system. The method of cognitive modeling was studied in order to formalize the influence of exogenous and endogenous processes on the financial activity of agribusiness enterprises. As a result of the research, the components of the development of enterprises in the agricultural sector were analyzed from the standpoint of ensuring the efficiency of their financial activities using cognitive modeling. A matrix of causality and a cognitive map of the influence of a number of factors on the target component "financial activity of the agribusiness enterprises" were built. Impulse modeling of the influence of given concepts was carried out. The results of the conducted cognitive modeling of the influence of factors can be used to develop a safe strategy for the sustainable development of enterprises of other industries in the conditions of dynamic changes. The application of the cognitive approach made it possible to foresee various processes of development of situations in this system that may arise in it under the expected influence of various factors, as well as the influence of regulatory and control systems. © 2024 by the author(s).