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Intelligent management of an innovative oil and gas producing company under conditions of the modern system crisis
(2023) Krasnyuk, Maxim; Hrashchenko, Iryna; Goncharenko, Svitlana; Krasniuk, Svitlana; Kulynych, Yurii
This publication presents the part of the research results and practical results obtained by the authors regarding the hybrid use of economic-mathematical modelling, knowledge-oriented decision support technology of an oil and gas production company using fuzzy logical inference. The purpose of this research is the development of theoretical provisions of modelling and knowledge-oriented decision support means at the macro level of oil and gas production companies. The purpose of the work determined the solution of the following tasks: - development of science-based recommendations regarding the architecture of a knowledge-oriented DSS of an oil and gas company, the basic model of knowledge presentation, features of the logical conclusion mechanism, etc.; - development of a complex system of economic and mathematical support for decision-making at the macro level of an oil and gas production company in modern economic conditions. The object of the study is the oil and gas production industry. The subject of the research is information processes, economic-mathematical models and knowledge-oriented methods and means of supporting the adoption of management decisions at the strategic level on economic and production issues of the domestic oil and gas production project. Methods/Approach: Economic and mathematical methods, methods of artificial intelligence, methods of logical generalization, expert evaluations and situational approach are used to solve the tasks set in the work. Results: The main scientific result of the work consists in the creation of the concept that allows creating a hybrid DSS of an oil and gas company on the basis of the developed systems of economic and mathematical decision-making support at the macro level of an oil and gas production company, focused on knowledge of technology and intelligent technologies. Conclusions: The scientific, theoretical and applied practical solutions proposed in this publication are universal for implementation by both state and private oil and gas resident and non-resident companies for emerging markets, however, in order for a specific oil and gas company to obtain special additional competitive advantages over others, additional industry-specific Big Data Analysis of collected and stored heuristics, expertise and project development are required
Iterative methodology of bankruptcy forecast of logistic companies in emerging markets, taking into account global/regional crisis
(2020) Hrashchenko, Iryna; Krasnyuk, Maxim; Krasniuk, Svitlana
Taking into account the globalized, regional, sectoral and pre-crisis specific of the above mentioned task of FA, it is relevant to critically analyze the main methods (and practice of their use) of financial analysis in order to to develop an complex iterative script methodology of FA for LC on emergent markets in pre-crisis or crisis conditions. Summarizing the comprehensive analysis of existing and used methods of FA for LC, and given the author's practical industry experience, it can be confidently stated that no existing algorithm of FA can not give an adequate forecast of the financial status of LC applicable at all stages of the LC life cycle and all phases of a possible crisis in emerging markets. In this article, the important and urgent task is solved: the development of a step-by-step iterative integrated methodology of financial analysis and forecasting the bankruptcy of a logistics company on emergent markets in pre-crisis and crisis conditions, applicable at all stages of the LC life cycle and all phases of a possible crisis.
Methodology of effective application of economic-mathematical modeling as the key component of the multi-crisis adaptive management (on the example of companies in the logistics industry)
(2021) Krasnyuk, Maxim; Kulynych, Yurii; Tkalenko, Antonina; Krasniuk, Svitlana
The two main groups of results will provide an adequate, systemic multi-modal response to a variety of crisis events and situations. The process of assembling and configuring the elements of the anti-crisis program / plan is inherently an open, heuristic, intellectual process of making managerial decisions and scenarios. The intellectual and professional abilities of the manager / specialist / auditor / controller performing this task play a significant role in the development and implementation of effective anti-crisis management plans and programs. This determines the importance of the personal factor and experience in preparing for decision-making in open problems, determines the requirements for the selection and organization of work in the ad-hoc mode of internal and external experts / auditors / controllers. However, a study of the management practice of logistics companies in emerging markets (especially in the context of the current global pandemic) showed a significant and negative potential impact of subjective factors on decisions of the management of logistics companies, their auditors, and controllers (cheating, corruption, raiding, inattention, industrial espionage, etc.). To limit the influence of the above subjective factors, the authors conducted research in the field of economic and mathematical modeling on two main tasks: “development of a methodology and model for the formation of a crisis plan for a logistics company in the context of a possible multi-level crisis” and “development of methodology and improvement of models for predicting the results of a possible implementation of an anti-crisis three-level adaptive program for a logistics company, taking into account the influence of the current multi-level crisis features and conditions”.

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