Volume 4, Issue 3, 2024

The definitions set out in the article are the result of a systemic analysis of the environment, existing forecasts of future conditions based on strategic thinking, which help explain the theory of the emergence of agglomeration effects in territorial planning in the region. The essence of strategizing is focusing on the implementation of a set of interests. Therefore, the agglomeration strategy should be aimed at realizing long-term interests, such as creating new industries, improving the quality of life of the population, maintaining positive dynamics of demographic indicators, thereby ensuring the interests of a larger number of parties and achieving an agglomeration effect for the subject of the Russian Federation. It is the interests of the population, aimed at restoring the integrity of the territory in terms of the main economic indicators within the agglomeration, that are the main resulting factor reflecting the effectiveness of the strategy. At the stage of planning strategic priorities, it is important to pay attention to the transport accessibility of territories. Intraregional differences in the level of socio-economic development in Kuzbass, including the level of unemployment, prove the need for investment in the development of new industries. The lack of resource availability reduces the effectiveness of strategy and does not contribute to socio-economic development. An analysis of the economic mechanisms existing in the region and the fundamental principles of spatial development determines the possibilities of choosing between scenarios to achieve the agglomeration effect. The developing explanatory theory reveals the fact that limited resources can never satisfy uncertain desires and needs, and only a formalized strategy that combines forecast, priorities, long-term goals and objectives with a detailed scenario, the use of a strategic monitoring system, and assessment of resource limitations will achieve agglomeration effects in region.

The solution of the issues of increasing labor productivity is significant at the state, regional, corporate and project levels. The purpose of the article is to form a systemic and conscious perception by senior managers of the role of digital technologies and modern methods of big data processing in solving the problems of increasing labor productivity, the importance of the strategizing methodology for finding and recording points of growth of added value at the enterprise. Based on the scientific works of Academicians Askar A. Akayev and Viktor A. Sadovnichy, a review of the predicted changes in the main subsystems of the World-System is conducted, it is shown that under these conditions the relevance of a comprehensive analysis that takes into account not only long-term trends, but also the interaction of all important factors: technology, demography, economics, sociosphere, politics, etc. increases many times over. The methodological basis of the study is formed by the fundamental laws and rules of the methodology of strategizing of Academician Vladimir L. Kvint. It is shown that the instrument for the practical implementation of the system of strategic management of labor productivity growth processes is digital transformation. The solution to the problem of increasing labor productivity is provided by the large-scale implementation of end-to-end digital technologies in the production life cycle, ensuring the convergence of human and intelligent machine labor - automatic execution of the overwhelming majority of routine operations and offering the best possible solution to a person. The process of managing the strategic process of increasing labor productivity consists of the following stages: monitoring and analysis of indicators; identifying potential growth points; building a digital model of the process and conducting simulation experiments; developing organizational and technical measures and creating a decision support management system. A decisive factor for enterprises seeking to increase labor productivity is the use of artificial intelligence to automate everyday tasks, which allows employees to focus on more strategic activities.

As western sanctions affect Russia’s foreign policy, its foreign trade policy takes a turn to the East. Econometric modelling applied to the strategy of trade flows may reveal some important factors that affect the volume of Russian trade with Asian countries. The authors assessed the prospects for the development of trade relations between Russia and some countries of East and South-East Asia. The study focuses on international trade relations between the Russian Federation and some countries of East and South-East Asia, i.e., China, India, Vietnam, and Singapore. The methods included econometric and graphical modeling, as well as a comparative analysis. The gravity model confirmed Russia’s reorientation to the East. However, the geographic distance has a negative impact on the trade volume, increasing the delivery cost and time. Free trade areas, on the other hand, facilitate the trade, e.g., with Vietnam and Singapore. According to the gravity model, the coming years will witness an increase in the trade cooperation between the Russian Federation and the abovementioned Asian countries as Russia’s foreign trade policy gathers pace in the new geopolitical reality. A potential free trade area will strengthen Russia’s trade bonds with the People’s Republic of China.

The article introduces a conceptual model for strategizing the socio-economic development of resource regions. The research relied on the theory of strategy and methodology of strategizing developed by Professor Vladimir L. Kvint. The model, which consisted of several stages, covered trend analysis, internal environment analysis, mission formation, strategic priorities, and their assessment by mathematical, statistical, and cognitive methods. It is shown that the developed model can be used to develop strategies for resourceoriented regions, and also expanded for use in regional strategizing in general.

The problem field of healthcare staffing is a highly relevant area for research efforts in strategizing. This study featured the human resource potential of the domestic healthcare system in a national and regional contexts. The theory and methodology of strategizing developed by Professor Vladimir L. Kvint made it possible to trace some indicators of human resourcing potential in the healthcare sector, i.e., age, regional structure, reproduction of labor-power, etc. Effective strategizing depends on the patterns that kept repeating since the beginning of the century. The research revealed the key principles of personnel strategizing in healthcare. First, constant high-quality monitoring helps to follow the changes in the patterns of reproduction of human resources, including regional specifics. Second, global trends in healthcare, e.g., digitalization, optimize the work and increase its efficiency. Third, personnel strategizing takes into account current and projected changes in morbidity, technological development, unexpected challenges like the COVID-19 pandemic, etc. Fourth, healthcare strategizing needs accounting, identification, instrumentalization, and institutionalization of factors that contribute to the growth of human resources. Fifth, strategizing in this sphere requires coordination with human resourcing in other industries, especially those connected with intellectual labor. Finally, attraction, retraining, and advanced training of foreign specialists and students are of great importance for effective strategizing.

Artificial intelligence and machine learning methods build investment routes to balance models between private and public sources of financing. In this respect, they are of national importance for import substitution and technological sovereignty. Decision support systems build business development scenarios based on marked-up data. They reduce the risks of projects connected with import substitution and national technological sovereignty. Early integrated planning and balancing of developer and investor capabilities can help other venture and high-tech projects by balancing various sources of private and government financing. This article introduces a new development method of machine learning and artificial intelligence based on an ultraprecise neural network. The method automates the task of navigating technological projects using investment financing tools. It builds a continuous multi-agent investment route to reduce the risks of technological projects in terms of private and government investments. In fact, the method offers an algorithm that connects the fundraising stage, the type of project, and the type of funding source. The research objective was to strategize the development, implementation, and scaling of artificial intelligence methods and scenario multi-agent modeling to solve economic coordination tasks of raising public and private funds by personal investment routes and integrated investment routes. The authors rationalized the development, implementation, and scaling of personal and integrated investment routes, defined the development principles, and designed a checklist. They also developed a methodology for using artificial intelligence algorithms. The practical part featured a case of strategizing regional economic potentials in terms of raising additional funds by multi-agent modeling of financial and economic interaction of individual investment projects and integrated investment projects. The authors assessed the long-term multiplicative effect of investment projects on sectoral and intersectoral cooperation, which increases the regional investment attractiveness. The study relied on the theory of strategy and methodology of strategizing developed by Professor Vladimir L. Kvint.

The work proposes a new strategic concept of Innovation Information Modelling based on digital technology, which allows for the creation of a digital twin of the innovation implementation process in a construction project and its use throughout the entire lifecycle of a construction object, from design to operation. The concept opens up new opportunities for construction organizations, including more effective strategic management of innovation implementation and utilization, meticulous process control, and prompt decision-making in the event of changes in external or internal project conditions.

The Russian tourism industry gets its current development impulse from reorientation to domestic tourism. Domestic tourism demand depends on the growth of prices for tourist transport services. In this regard, automobile tourism is a sensible solution for household and corporate budgets. The Vologda Region with its historical, cultural, and natural potential has good prospects for auto-tourism. The study identifies strategic priorities for the development of auto-tourism, which could increase the tourist traffic and tour service consumption in the region. The cartographic analysis of road infrastructure revealed the following obstacles to the development of auto-tourism: bad quality of roads, uneven distribution of roadside service facilities on the main tourist routes, and geographical remoteness of tourist attraction centers. The analysis of trends and factors of external and internal environment made it possible to identify the strategic priorities for the development of auto-tourism in the Vologda Region. The author formulated the concept of roadside service facilities development as a tool for the implementation of the priorities identified above.

Universal methodological standards for new innovative clusters are an issue of uttermost importance during the current emergency period. An effective methodology of cluster strategy development is crucial for stimulating innovative growth. This study proves that the methodology developed by Professor Vladimir L. Kvint is able to provide strategic success in developing the innovation clusters system in the current Russian realities. Strategic leaders and strategy developers are recommended to adhere to the fifteen key principles of strategic thinking described in this article.