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The article develops economic and mathematical models as a tool for conducting factor financial analysis of the prospects for the development of an industrial enterprise. The functioning of the developed economic and mathematical models is based on the DuPont model, which allows analyzing the dynamics of the company’s profitability in the course of two-factor and three-factor financial analysis. The proposed model tools are based on the convergence of deterministic financial analysis methods embedded in the DuPont model and simulation methods that allow analysis under the influence of random factors. The constructed economic and mathematical models for forecasting profitability use the company’s retrospective data on its financial condition: the amount of profit, revenue, assets, and equity. The constructed simulation models are implemented in the OMEGA software product and included in the computer technology for predicting the profitability of an industrial enterprise. The architecture of the proposed tools is presented, and the results of simulation experiments performed on models are demonstrated.
Alex Borodin; Irina Mityushina; Elena Streltsova; Andrey Kulikov; Irina Yakovenko; Anzhela Namitulina. Mathematical Modeling for Financial Analysis of an Enterprise: Motivating of Not Open Innovation. Journal of Open Innovation: Technology, Market, and Complexity 2021, 7, 79 .
AMA StyleAlex Borodin, Irina Mityushina, Elena Streltsova, Andrey Kulikov, Irina Yakovenko, Anzhela Namitulina. Mathematical Modeling for Financial Analysis of an Enterprise: Motivating of Not Open Innovation. Journal of Open Innovation: Technology, Market, and Complexity. 2021; 7 (1):79.
Chicago/Turabian StyleAlex Borodin; Irina Mityushina; Elena Streltsova; Andrey Kulikov; Irina Yakovenko; Anzhela Namitulina. 2021. "Mathematical Modeling for Financial Analysis of an Enterprise: Motivating of Not Open Innovation." Journal of Open Innovation: Technology, Market, and Complexity 7, no. 1: 79.
The purpose of this article is to study the theoretical foundations of the concept of fiscal decentralization, as the main path of self-development of the national economy of any country, and to develop mathematical tools that support decision-making in the aspect of “hard” budget constraints. The study of the problems of fiscal policy formation in foreign countries presented in modern scientific literature has revealed that the degree of application of the concepts of “soft” and “hard” budget restrictions is an actual topic in the theory of fiscal federalism. It has been substantiated that decision-making within the framework of “soft” budget constraints (financial assistance) leads to low tax autonomy of territories and limited liability of regional and municipal authorities for the results of their financial policy. As a research hypothesis, we put forward the thesis that it is necessary to create conditions for encouraging subnational authorities to support the territorial economy by granting them the possibility to use part of the taxes collected in the respective territories. The implementation of this thesis has given rise to the problem of quantifying decisions made regarding the establishment of standards for the distribution of tax revenues between budgets of different levels of the hierarchy of the country’s budget system. In terms of solving this problem, the author has constructed mathematical models based on the use of synthesis of mathematical apparatus of the theory of stochastic automata, fuzzy algebra, and simulation. In terms of solving this problem, the author proposed the use of mathematical modeling methods. The article presents the results of constructing economic and mathematical models to support decision-making in the vertical distribution of tax revenues between budgets. The models include stochastic automata, as mathematical abstractions, describing the expedient behavior of an economic agent when choosing management alternatives for territories of different levels of economic development. The transition functions of automaton models are formally described on the basis of the synthesis of mathematical apparatus of the theories of stochastic automata operating in random environments and fuzzy sets. The expediency property of the behavior of automaton models is justified by proving the corresponding theorems. The random environment in which stochastic automata are immersed is formed by a simulation model. The article demonstrates the results of experiments carried out on models, as well as a conceptual scheme of interaction between the automaton and simulation models.
Irina Yakovenko. Fuzzy Stochastic Automation Model for Decision Support in the Process Inter-Budgetary Regulation. Mathematics 2020, 9, 67 .
AMA StyleIrina Yakovenko. Fuzzy Stochastic Automation Model for Decision Support in the Process Inter-Budgetary Regulation. Mathematics. 2020; 9 (1):67.
Chicago/Turabian StyleIrina Yakovenko. 2020. "Fuzzy Stochastic Automation Model for Decision Support in the Process Inter-Budgetary Regulation." Mathematics 9, no. 1: 67.
This article is devoted to the creation of intelligent modelling tools for decision support in the evaluation of intellectual projects submitted for financing, as based on qualitatively defined characteristics. The economic and mathematical models that form the basis of the toolkit are constructed using the mathematical apparatus of fuzzy logic, which allows for the description of poorly structured knowledge of specialists, as well as their application in solving questions about the extent of the impact of the proposed projects on the environment. The authors classify investment projects according to the degree of impact on the environment, the environmental criteria required by the investor for the evaluation of investment projects, and the formal formulation of the problem of evaluation of investment projects when taking into account the environmental factor. The toolkit was created based on the concept of intellectualization, where economic and mathematical models for the evaluation of investment projects are programmatically implemented via the tools and functions available in the MATLAB package.
Sayabek Ziyadin; Elena Streltsova; Alex Borodin; Nataliya Kiseleva; Irina Yakovenko; Elmira Baimukhanbetova. Assessment of Investment Attractiveness of Projects on the Basis of Environmental Factors. Sustainability 2019, 11, 2544 .
AMA StyleSayabek Ziyadin, Elena Streltsova, Alex Borodin, Nataliya Kiseleva, Irina Yakovenko, Elmira Baimukhanbetova. Assessment of Investment Attractiveness of Projects on the Basis of Environmental Factors. Sustainability. 2019; 11 (9):2544.
Chicago/Turabian StyleSayabek Ziyadin; Elena Streltsova; Alex Borodin; Nataliya Kiseleva; Irina Yakovenko; Elmira Baimukhanbetova. 2019. "Assessment of Investment Attractiveness of Projects on the Basis of Environmental Factors." Sustainability 11, no. 9: 2544.