This paper presents an analysis of existing methods and models designed to solve the problem of planning the distribution of financial flows in the operational management cycle of the enterprise; it also offers tools for process management of enterprise financial flows based on the method of dynamic programming, which allows for determining the optimal combination of factors affecting the financial flow of the enterprise, taking into account existing restrictions on changes in the influencing parameters of the model. The current study develops an innovative model that maximizes the economic efficiency of investment in the sale of food products through retail chains and the practical implementation of the developed model based on the data from the financial reports of LLC "Kraft Heinz Vostok". The theoretical and methodological basis of the research includes the works of Russian and foreign experts in the fields of methodology of economic and mathematical modeling and decision-making, dynamic programming, system analysis, information approach to the analysis of systems, process management of enterprise financial flows, and human resource management. The author's methodology makes it possible to increase the company's profitability in key clients and categories in the range of 4 to 6 million dollars and to increase the return on investment by 10–17%. The scientifically innovative aim is to develop a toolkit for process management of enterprise financial flows, characterized by a systematic combination of methods of dynamic programming, social financial technologies, and economic evaluation of investments, which allows for the creation of mechanisms for managing the development of enterprises of all organizational and legal forms and the development of model projects of decision support systems with the prospects of their incorporation into existing information and analytical systems. Doi: 10.28991/ESJ-2023-07-03-017 Full Text: PDF
Background and purpose: The use of artificial intelligence (AI) models for data-driven decision-making in different stages of employee lifecycle (EL) management is increasing. However, there is no comprehensive study that addresses contributions of AI in EL management. Therefore, the main goal of this study was to address this theoretical gap and determine the contribution of AI models to EL management. Methods: This study applied the PRISMA method, a systematic literature review model, to ensure that the maximum number of publications related to the subject can be accessed. The output of the PRISMA model led to the identification of 23 related articles, and the findings of this study were presented based on the analysis of these articles. Results: The findings revealed that AI algorithms were used in all stages of EL management (i.e., recruitment, on-boarding, employability and benefits, retention, and off-boarding). It was also disclosed that Random Forest, Support Vector Machines, Adaptive Boosting, Decision Tree, and Artificial Neural Network algorithms outperform other algorithms and were the most used in the literature. Conclusion: Although the use of AI models in solving EL management problems is increasing, research on this topic is still in its infancy stage, and more research on this topic is necessary.
This research focuses on the professional development of teachers in rural areas based on digital literacy. It aims to measure the existing digital literacy and competence of rural teachers in Indonesia, Russia, and the Middle East and to assess the extent of digital literacy training provided to rural teachers for their professional development in these regions. In pursuit of this objective, a quantitative research method was incorporated into the study. The survey was conducted specifically for the research, and SPSS was used for statistical analysis. The report reflected the challenges that digitalization faces in rural areas and the differences in the provision of digital literacy training in Indonesia, Russia, and the Middle East. Various limitations are identified as hampering the integration of digital literacy in underdeveloped areas, such as the lack of proper digital infrastructure. However, the situation was found to be somewhat better in the case of Russia, with the teachers reporting the provision of adequate hardware and infrastructure, which were lacking in the cases of Indonesia and the Middle East. The same pattern was found in the case of the provision of digital literacy training opportunities in Indonesia and the Middle East, which lag behind Russia. All in all, it is imperative to develop introductory courses for using the internet and their general application for teachers in rural areas. Doi: 10.28991/ESJ-2022-06-06-019 Full Text: PDF
The main contradiction identified in the study is that the existing scientific and methodological solves of economy development management processes does not create prerequisites for improving the efficiency of their work, the introduction of progressive technologies for material and moral stimulation of the work of performers and administrative and managerial personnel, advanced social mechanisms for country's economy development and social security employees. Economic and mathematical modeling of the complex system of social financing of enterprises and the economy of the country, scientifically sound personnel policy and the system of motivation of performers and administrative and management personnel is an important and urgent problem. The purpose of the study is to develop and implement an economic and mathematical model of a comprehensive system of social financing of enterprises and the economy of the country, optimizing the wages of the workforce, consistent with revenue growth, deductions for the development of the enterprise (relevant for the employer and the entire workforce), taxation and social contributions (important for the state). The results of the studies conducted and presented in this article allow us to conclude that the proposed social financial technologies for the development of enterprises and the economy of Russia, make it possible, at quite achievable rates of growth of gross domestic product (revenue of enterprises) by 3% per year, to ensure an increase in the wages of working citizens for 5 years by 34 %, which will make it possible to practically end poverty, and to increase contributions to the development fund over 5 years by 16%. Starting from 2026, increase receipts from income tax, tax on profit rate and value added tax and bring this growth to 30% by 2041, which will allow the state to solve many social problems.
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