Статья: MANAGEMENT OF SOCIOECONOMIC DEVELOPMENT: NATIONAL PLANNING AND ITS IMPACT ON THE HUMAN DEVELOPMENT INDEX IN RUSSIA (2024)

The purpose of this study is to consider the phenomenon of ‘capital flight’ as a threat to the economic security of the country. This goal is achieved using general scientific methods, including analysis and synthesis, induction and deduction, abstraction, systematisation, and comparison. The study highlights the differences between the concepts of ‘capital outflow’ and ‘capital flight’, assesses the scale of capital flight and outflow, analyses the causes of these phenomena, and explicates the goals of capital flight. One of the causes of capital flight, namely tax evasion, is specified. The findings underscore the main directions of the impact of capital flight on the economic security of the country, and key measures to combat capital flight are proposed.

The complicated geopolitical situation has become a factor in domestic tourism development in the Russian Federation. A significant number of objects of tourist interest have generated increased competition between Russian regions to attract tourists. A necessary condition for increasing tourist flow is the development of tourist infrastructure, including transport. The authors used various types of transport in the vast majority formation of tourist products, as well as in independent tourism. The purpose of this study is to analyse the relationships between tourist flow dynamics and the transportation system development indexes of St. Petersburg and the Leningrad region. Comparative, correlation and regression analyses showed a strong positive correlation between tourist flow and passenger transport by buses and suburban railway transport (especially in St. Petersburg). The study confirmed the problem of data reliability and availability for analysing tourist flow within the St. Petersburg agglomeration, although the palace suburbs, which are popular with tourists, are located within agglomeration boundaries. To solve the problem of tracking tourist flows when using transport in the agglomeration, the authors propose the development and implementation of a transport tourist map with advanced functionality. This digital tool application will allow not only the reliable tracking of tourist flows but also the optimization of the transport system of the St. Petersburg agglomeration. In addition, the analysis of tourist flow dynamics should be used to increase the positive effects of tourism development and reduce the negative effects of overtourism in achieving the sustainable development goals of St. Petersburg and the Leningrad region.

The Russian economic space is characterised by a significant differentiation in the levels of socioeconomic development of the country’s various regions, which manifests itself in natural, territorial, socio-cultural, economic, political and other aspects. The results of socio-economic differentiation are unique regional socio-economic systems, which necessitates the formation of individual approaches to managing their development. Therefore, management decisions made at the federal centre, as well as by regional authorities, affect the activities of economic entities in the regions and the population’s level of well-being in different ways. Social security is an integral element of the high quality of life of the population and is largely the basis for improving the economic status of the region, increasing the value of human capital. Thus, it is necessary to develop methods and tools for ensuring the social safe development of regional socio-economic systems, considering the specific characteristics of each region. From these perspectives, we can discuss the stability and social performance of the regional economy. Despite a broad scientific background, the factors contributing to the development and the results of regional socio-economic systems, considering the need for social security, have not been examined. The present research aims to fill this gap by developing a management model for the social and safe development of Russia’s regions, using the city of St Petersburg as the case study

With the rapidly changing economic environment and inherent market conditions, risk assessment is becoming a major priority for companies involved in innovative projects. Innovative projects are characterized by great uncertainty and their success largely depends on a variety of factors. To improve the quality of risk assessment for such projects, it is essential that you use methods that consider the complex relationships between many variables. This paper suggests a model based on fuzzy sets and Bayesian networks that allows you to effectively analyse and manage the risks of innovative projects. Using fuzzy sets can help you take into account the uncertainty in the data and work with fuzzy information, which is of prime importance, as there are a lot of diverse data that must be considered in innovative projects. With Bayesian networks, you can model probabilistic relationships between risks and project factors, which gives you a more accurate idea of potential risks and helps you predict possible scenarios for the project. Our model represents an innovative approach to assessing the risks of innovative projects and contributes to more effective risk management and informed decision-making in the case of complex projects. It can also facilitate sustainable development of the innovation sector and increase the competitiveness of companies due to the more efficient use of resources and a higher probability of successful innovative initiatives in the long run