Vol 19, No 1 (2024)

Introduction. The current economic situation determines specific requirements for the development of domestic industrial structures. These requirements are designed to enhance structures’ innovation activities and accelerate scientific and technological update for technological sovereignty and higher competitiveness in the world market. However, a number of challenges hinder the innovative development of enterprises and prevent a change in their ranking status among leading high-tech companies. A lack of efficient innovation activities could be explained by the imperfect methodological tools applied to innovation management and template thinking typical for the majority of top managers, which both erects barriers to progressive changes and provides prerequisites for new formidable challenges in strategy implementation for the rapid development of the Russian economy.

Purpose. The key goal of the scientific research is to develop a model for an efficient development of innovative activities in industrial enterprises. The model is designed to contribute to favorable conditions for the growth of highly efficient businesses flexibly adapting to current realities and challenges.

Materials and Methods. To achieve the goal, the author referred to the methods of structural analysis and synthesis, generalization, analogy, modeling, system analysis, and optimization.

Results. The analysis led to working out scientific recommendations for better efficient functioning of domestic enterprises in the field of innovation. Unlike the existing recommendations, these ones contribute to the qualitative bifurcation of their innovation systems and the achievement of a synergistic effect. Conclusions. The conclusions drawn are of high practical importance for improving the innovative activities of the Russian enterprises and increasing their competitive advantages in the context of global changes. The strategic guideline for further research is the issues of methodological and technological support for the developed proposals.

Introduction. Stock market volatility simulation and forecast are relevant issues which could contribute into lower risks and higher revenues of the market transactions. These days, AI-based methods, including deep neural networks, are quite promising for volatility simulation.

Purpose. The paper verifies a hypothesis concerning a higher accuracy of LSTM neural network compared to the classical autoregressive models (e.g. ARIMA) and long memory models (e.g. ARFIMA).

Materials and Methods. To check the hypothesis, the authors conducted simulation experiments with S&P 500 index data generally illustrating the dynamics of the US stock market. Results. The LSTM neural network gave significantly more accurate forecasts compared to the ARIMA- and ARFIMA-based forecasts for learning and test samples; ARFIMA model was more accurate than ARIMA, which supports previous data.

Conclusions. The results of the work prove that the LSTM neural network is a promising method to forecast stock market volatility and could be further examined in this area. Machine learning methods, including the neural networks, could be used to define the future dynamics in the revenues of financial asserts and optimize current algorithms of portfolio imbalances, approximation and simulation of risk metrics, approximation of probabilistic characteristics for financial instruments.

Introduction. The article analyzes the interpretations of the concept “megaproject” and proposes the author’s definition of the concept presupposing explicit and implicit beneficiaries and ensuring high-tech products with a high potential for market sales. Purpose. Based on the results of the regression analysis, the paper draws conclusions and describes the behavior strategies of the explicit and implicit beneficiaries in the megaproject when its results are being registered and after it.

Materials and Methods. Theoretically and methodologically, the paper refers to the works of scientists examining megaprojects. The regression analysis for thirty constituent entities of the Russian Federation made it possible to determine that the indicators of their budget revenues illustrate that cash flows determined by the investment return from the investments in fixed capital go through the budget system with a minimal tax burden.

Results. It has been found that in the analyzed period, the return on investment in fixed assets was determined by the investors’ speculative motives when using financial market instruments under personal guarantees of the heads of the constituent entities of the Russian Federation. At the same time, the applied financial market instruments gave the minimum inflow of taxes into the budget system of the Russian Federation.

Conclusions. In its model, Russia is closer to the continental civilizational type; the balance in the socio-economic relations determined by megaprojects with their maximum contribution to GDP could be achieved when national self-identification is distinctly shaped; national self-identification could only be developed with due regard to the quantitative and structural composition of population.

Introduction. Regional development is currently aimed at creating conditions for human life, improving the living standard and quality of life, which is reflected in the regulatory and legal regional policy. However, the definitions of the categories “living standard” and “quality of life” are debatable; therefore, choice of tools and mechanism could arise difficulties to achieve these goals in the frame of regional development. This scientific study suggests the category “population’s well-being in the region” as one of the comprehensive goals of the regional policy to resolve these controversial issues.

Purpose. The paper identifies the essential characteristics of the population's well-being in the region such as a set of benefits, their relationship and correlation with the concepts of “living standard” and “quality of life”, determines the place of this concept in the regional policy, and describes a new approach to the definition of the concept “population’s well-being in the region” from the perspective of the theory of goods.

Materials and Methods. To achieve this purpose, scientific sources were theoretically analyzed, and the obtained data was synthesized to accumulate new knowledge about the category “population’s well-being in the region”.

Results. The study revealed that the well–being of the population in the region is a complex and multidimensional category comprising of both the level of life and its quality for the population, as well as represented by economic and non-economic, tangible and intangible goods of a social, economic, environmental, and institutional nature.

Conclusion. A region being the object of regional policy is a system of interrelated elements, therefore regional development is the subject of the regional policy with the goal to increase the well-being of the population in the region. The comprehensive nature, versatility of this human-orientated category put it to the global concept of sustainable development with due regard to the regional interests in improving the level and quality of people’s lives.