V. S. Baraniuk, D. I. Fadiukhina, E. G. Muraveva, A. D. Khan, R. M. Frolov (Pirogov Russian National Research Medical University, Moscow)

Analysis of the influence of technological stamping parameters on the reliability and safety of medical instruments

This study conducts a comprehensive analysis of the influence of key stamping parameters on the strength characteristics and operational reliability of medical instruments. Based on an extensive empirical dataset, including laboratory testing and clinical practice data, optimal ranges of stamping parameter values have been identified to ensure maximum instrument reliability. It was established that critical factors include the precision of the shape and dimensions of the working parts of the instruments, the uniformity of the microstructure, and the level of residual stresses in the material. A set of technological solutions has been proposed to achieve the required quality parameters in mass production of medical instruments. The results obtained have high practical significance for optimizing instrument manufacturing processes and enhancing their safety in surgical practice. Future research should focus on the development of automated systems for real-time control of stamping parameters.
Keywords: stamping; medical instruments; reliability; safety; technological parameters; microstructure; residual stresses.

 

P. I. Chuvakhin (Financial University under the Government of the Russian Federation, Moscow)

Study of the application of Big Data technologies for optimizing stamping production processes

The article is devoted to the study of the application of Big Data technologies for optimizing processes in stamping production. The relevance of the topic is driven by the growing interest in the digital transformation of industry and the potential of Big Data in enhancing the efficiency of manufacturing operations. The objective of the work is to identify key directions and effects of implementing Big Data in stamping production based on the analysis of advanced practices and empirical data. The study employed a range of methods, including systematic literature analysis, case studies, expert interviews, and statistical modeling. The empirical base consisted of data from 120 stamping enterprises for the period 2018–2023. It was revealed that the use of Big Data technologies can increase the overall equipment effectiveness (OEE) by 12–17 %, reduce downtime by 20–25 %, and decrease defect rates by 35–40 %. It was demonstrated that the key success factors are data quality, information systems integration, and personnel competencies. Recommendations for the strategy of implementing Big Data in stamping production were formulated. The obtained results contribute to the development of the «Industry 4.0» concept and open prospects for further research in the field of manufacturing process digitalization.
Keywords: Big Data; stamping production; process optimization; digitalization; Industry 4.0; intelligent data analysis.

 

S. A. Tronin (Financial University under the Government of the Russian Federation, Moscow)

Modeling of intelligent production management systems based on artificial intelligence and big data technologies

The article is devoted to the problem of modeling intelligent production management systems (IPMS) based on artificial intelligence (AI) and big data technologies. A conceptual analysis of modern literature is presented, key trends in this area are highlighted. Based on the analysis of the terminology, the author's definition of IPMS is proposed. Gaps in existing studies are identified, the relevance of developing new approaches to modeling IPMS is argued. The research methodology is characterized, including methods of system analysis, simulation modeling, machine learning and data mining. The empirical base was formed by production data of three companies in the mechanical engineering sector. The results of testing the author's IPMS model are presented, demonstrating an increase in the efficiency of production management by key indicators by 10-15%. The theoretical and practical significance of the obtained results are discussed, prospects for further research in the mainstream of creating self-learning IPMS are outlined. The need for an interdisciplinary approach integrating the achievements of AI, data science and production systems management theory is emphasized.
Keywords: intelligent production management systems; artificial intelligence; big data; modeling; machine learning; digitalization of production.

 

V. B. Frolova (Financial University under the Government of the Russian Federation, Moscow)

Study of the influence of predictive analysis on models of innovative development of industrial enterprises under uncertainty

The article is devoted to the study of the influence of predictive analysis on models of innovative development of industrial enterprises under uncertainty. Theoretical and methodological provisions are substantiated and practical recommendations for the implementation of predictive analytics as a tool for innovative transformations in industry are developed. It has been established that the use of predictive analytics increases the accuracy of demand forecasting by an average of 17,4 %, accelerates the introduction of innovations to the market by 28,6 %, and reduces the risks of unsuccessful launches by 32,1 %. A matrix for selecting the optimal predictive analysis model depending on the type of innovation and uncertainty characteristics has been developed. An algorithm for implementing predictive analytics in a decision-making system based on the integration of Big Data, Machine Learning and Business Intelligence is proposed. The results of the study deepen the understanding of the relationship between analytical technologies and innovation dynamics, and open up prospects for creating digital platforms for the innovative development of industrial enterprises. The further direction of work is related to the industry specification of the proposed models and methods.
Keywords: predictive analytics; innovation; industry; uncertainty; modeling; digitalization.

 

Sun Che, Du Lei, Liu Zhuoxin (Saint Petersburg State University, Saint Petersburg)

Application of game theory methods for resource management and cost reduction in stamping production

This study is dedicated to the application of game theory methods for resource management optimization and cost reduction in stamping production. The relevance of the topic is due to the need to improve the efficiency and competitiveness of industrial enterprises in a dynamic market environment. An original method for the formalization of production-economic characteristics of stamping processes is developed (approximation accuracy 95 %). A series of game-theoretic models of cooperative and non-cooperative agent interactions in resource management is proposed (their stability and the existence of equilibria were proven). A complex of software tools is created for the implementation and parametric adjustment of the proposed models (with scalability capability for a wide range of productions). The developed methodology is tested, confirming a reduction in specific resource costs by 10–15 % and an increase in production rhythm coefficient by 8–12 %. The theoretical significance of the study lies in expanding the scientific toolkit for production system management through the synthesis of game-theoretic and optimization methods. The practical value is associated with the possibility of using the obtained models and algorithms to improve the efficiency of planning and organizing stamping production processes.
Keywords: game theory; resource management; stamping production; cost optimization; equilibrium stability; simulation modeling; parametric tuning.

 

P. I. Chuvakhin (Financial University under the Government of the Russian Federation, Moscow)

Methodological foundations for integrating digital models into quality management systems and innovation activities of industrial enterprises

The article considers the methodological foundations for integrating digital models into quality management systems and innovation activities of industrial enterprises. A conceptual framework and practical recommendations for integrating digital modeling technologies into the management decision loop at all stages of the innovative product life cycle have been developed. An analysis of the literature shows a shortage of system studies covering the full range of digital twin capabilities and going beyond narrow business processes. The theoretical significance of the work lies in the conceptualization of an integration approach that synthesizes methods of systems engineering, quality management and innovation. A multi-level maturity model is proposed that reflects the evolution of digitalization of production from isolated pilot projects to deep integration of cyber-physical systems. It has been proven that the transition to higher maturity levels is accompanied by an increase in the share of radical innovations (r = 0,74; p < 0,01) and a decrease in quality costs (r = –0,69; p < 0,01). The results are valuable for developing corporate digitalization strategies.
Keywords: digital model; digital twin; quality management; innovation; MBSE; industrial enterprise.

 

N. V. Kuchkovskaya (Financial University under the Government of the Russian Federation, Moscow)

Development of a methodology for using predictive analysis for strategic planning of industrial enterprises

A methodology for using predictive analysis for strategic planning of industrial enterprises has been developed. Taking into account modern digitalization trends and increasing turbulence in the business environment, the relevance of improving forecasting tools for making informed management decisions has been shown. Based on the analysis of research gaps in the field of predictive analytics application in industrial enterprises and a critical assessment of existing approaches, the authors propose an original algorithm for embedding predictive modeling tools into the strategic planning process. The developed methodology includes 5 stages, distinguished by a comprehensive combination of statistical methods, machine learning algorithms and expert assessments. Validation of the methodology on a sample of enterprises confirms an increase in the accuracy of key indicator forecasts and an increase in management satisfaction with the quality of plans. The results obtained not only contribute to the development of the theory of predictive business analytics, but also set a vector for the transformation of management practices. Further adaptation of the methodology to the conditions of specific enterprises will improve the validity and feasibility of their strategies in the face of uncertainty. 
Keywords: predictive analysis; strategic planning; industrial enterprises; machine learning; big data; business analytics; digital transformation.

 

S. G. Eremin (Finance University under the Government of the Russian Federation, Moscow); I. V. Babyna (Francisk Skarina Gomel State University, Belarus, Gomel)

Industrial policy and transnational corporations: impact on national economic interests

The article analyzes the impact of industrial policy and the activities of transnational corporations (TNCs) on national economic interests. Based on a systematic review of the literature and econometric modeling of panel data for a sample of 50 countries for the period 2000–2020, key trends and patterns were identified. It was found that the activity of TNCs in general positively correlates with the dynamics of GDP (β = 0,317; p < 0,01), but this effect is mediated by the quality of institutions and the consistency of industrial policy with the interests of national business. An integral index of policy consistency (CPI) is developed, the validity of which is confirmed by the Hansen test (J = 24,15; p > 0,1). The value of CPI > 0,65 is a necessary condition for the prevalence of the positive influence of TNCs. The results obtained develop the theory of strategic interaction between the state and TNCs and are of practical value for improving regulatory mechanisms in order to ensure national interests. Further research should focus on a more detailed analysis of country and industry specifics. 
Keywords: industrial policy; transnational corporations; national economic interests; panel regression; policy coherence index

 

A. I. Galkin (Financial University under the Government of the Russian Federation, Moscow)

Analysis of the role of innovation zones and technology parks in the implementation of industrial policy and stimulation of innovation

The article analyzes the role of innovation zones and technology parks in the implementation of industrial policy and stimulation of innovation. The study is based on a conceptual analysis of the literature, covering key publications of the last 5 years in highly rated journals. The author's terminology of key concepts is proposed, gaps in existing studies are identified. The relevance of the topic is substantiated, the non-triviality of the approach is argued. The methods of statistical and spatial analysis, comparative research, case studies are applied. The empirical base consists of data on 120 technology parks and innovation zones of Russia. It is revealed that technology parks contribute to the growth of innovative activity of companies by 18,4 %, increase the volume of attracted investments by 1,6 times. Innovation zones increase the innovative efficiency of the region by 11,3 %. The results have practical value for planning innovation infrastructure. Prospects for studying the role of the national innovation system are outlined. 
Keywords: innovation zone; technology park; industrial policy; stimulation of innovation; innovation infrastructure; spatial development; innovation potential.

 

M. P. Lazarev (Financial University under the Government of the Russian Federation, Moscow)

Study of the role of data centers and distributed data warehouses in forming industrial enterprise development strategies

The article considers the role of data centers and distributed data warehouses in forming industrial enterprise development strategies. An original approach to studying the relationship between the introduction of modern data storage and processing technologies and the strategic development of industrial companies is proposed. The empirical base includes data on 50 large industrial enterprises from various industries for the period from 2015 to 2023. Statistical and econometric analysis methods, as well as case studies, are used. The obtained results indicate a significant positive impact of investments in data centers and distributed storage on key performance indicators of enterprises (return on assets, labor productivity, revenue growth rates). Industry-specific features of this effect are revealed. Conclusions are made about the strategic role of data storage and processing technologies in ensuring the competitiveness of industrial companies in the context of digital transformation of the economy.
Keywords: data centers; distributed data storage; development strategies; industrial enterprises; digital transformation; investment efficiency; competitiveness.

 

N. V. Kuchkovskaya (Financial University under the Government of the Russian Federation, Moscow)

Application of predictive methods for forecasting and managing the development of new-generation industrial enterprises

The application of predictive methods for forecasting and managing the development of new-generation industrial enterprises is studied. The relevance of developing a new approach that integrates machine learning, simulation modeling and scenario planning methods is substantiated. The empirical base consists of data on 120 innovative industrial companies from various industries. Using ensemble machine learning methods (random forest, gradient boosting), forecast models of the dynamics of key performance indicators of enterprises were built. Based on them, alternative scenarios for the development of companies with probability assessment are generated using the Monte Carlo method. By means of multi-criteria optimization, optimal development trajectories for different scenarios are determined. Strategic maps of measures to achieve target indicators are developed. The accuracy of forecasts on test samples is 87–94 % for different indicators (R2 = 0,84–0,91; MAPE = 6,2–11,5 %). Sensitivity analysis confirms the robustness of the models. The obtained results lay the foundation for a dynamic approach to strategic management of enterprise development in conditions of uncertainty, opening up prospects for creating intelligent decision support systems of a new generation.
Keywords: industrial enterprises; predictive analytics; machine learning; simulation modeling; scenario planning; strategic management.

 

S. A. Tronin (Financial University under the Government of the Russian Federation, Moscow)

Study of the application of predictive analysis methods in models of strategic development of industrial enterprises in the digital economy

The article considers the application of predictive analysis methods in models of strategic development of industrial enterprises in the context of the digital economy. A comprehensive methodology for integrating predictive algorithms into strategic planning systems has been developed, aimed at increasing the adaptability and sustainability of enterprises in conditions of high uncertainty. Based on a critical analysis of the literature, key trends and gaps in research have been identified, and the author's terminology has been proposed. Original results have been obtained demonstrating a significant increase in the accuracy of strategic forecasts (up to 84 %) and an improvement in key performance indicators (ROA growth by 1,5–2,2 percentage points) when implementing predictive models. Methodological recommendations for adjusting algorithms taking into account industry specifics have been substantiated. The results have high theoretical and practical value and open up prospects for further research.
Keywords: predictive analysis; strategic development; industrial enterprises; digital economy; intelligent data analysis; machine learning.

 

An. B. Mottaeva (Financial University under the Government of the Russian Federation, Moscow)

Industrial and technological sovereignty of Russia as the basis for the formation of a competitive economy

The principle of sovereignty has always been the most basic principle of public international law. The article deals with industrial and technological sovereignty as an important component of economic sovereignty. Unjustified sanctions barriers from the United States and EU countries, the global global economic crisis, climate and environmental transformations have become motivators for ensuring industrial and technological sovereignty, the basis for the formation of a competitive economy. The authors of the study believe that the analysis will make it possible to substantiate Russia's industrial and technological sovereignty as the basis for the formation of a competitive economy. As a result of the research, conclusions were formulated that made it possible to update the understanding of the importance of industrial and technological sovereignty. The economic essence of industrial and technological sovereignty, which determines independence at the internal and external economic levels, is revealed. Increasing competitiveness and ensuring the industrial and technological status of the Russian economy is possible through the implementation of investment projects, the search for and access to new alternative foreign markets, strengthening leadership positions in the global industrial market, reaching a high level of innovative, intellectual and industrial development, and providing access to equal international technological cooperation.
Keywords: industrial and technological sovereignty; economic sovereignty; innovative activity; competitiveness; industrial and technological autonomy; national economy; scientific and technical potential.

 

O. V. Brizhak, V. E. Korolkov (Financial University under the Government of the Russian Federation, Moscow)

External and internal contours of the technological development of the Russian economy in modern conditions

The authors proceed from the objectively determined facts of finding the Russian economy in conditions of increased instability and the impact on the economy of a rather long-term and increasing factor of external sanctions restrictions, especially in matters of its technological development. The study of a qualitatively new practice of functioning and development of the Russian economy in these extraordinary conditions is an urgent scientific task solved by the economic system in the context of tightening external constraints. The events of recent years indicate that this context will persist in the medium term. At the same time, these events further actualize the development of the problem of economic development in these conditions, and also focus research in the field of economic theory on the study of external and internal contours of technological development in qualitatively new conditions of modern reality. In the course of the research, the authors use the methodology of political economic and system analysis.
Keywords: technological development; modern economy; external and internal contours; sanctions; instability; systemic approach.

 

M. P. Lazarev (Financial University under the Government of the Russian Federation, Moscow)

Study of the influence of digital models on environmental sustainability and energy efficiency of industrial enterprises in the context of sustainable development

The influence of digital models on environmental sustainability and energy efficiency of industrial enterprises in the context of sustainable development is studied. A comprehensive approach to assessing the potential of digital technologies in improving the eco-energy efficiency of production has been developed. The results show that the introduction of digital models helps to reduce specific energy consumption, reduce greenhouse gas emissions, and increase the environmental index. Factors mediating these effects have been identified. The findings contribute to the development of sustainable production and Industry 4.0 concepts. Prospects for further research in terms of developing predictive models and industry specification of the obtained patterns are outlined.
Keywords: digital models; environmental sustainability; energy efficiency; industrial enterprises; sustainable development; Industry 4.0.

 

T. U. Dzholdosheva (Kyrgyz Economic University named after M. Ryskulbekov, Bishkek, Kyrgyzstan); As. B.

Mottaeva (Financial University under the Government of the Russian Federation, Moscow)
The effectiveness of modelling the concept of a balanced structural maneuver in the field of residential real estate

Over the past hundred years, a new round of scientific and technological revolution and industrial transformations has provoked a historical intersection with the requirements of high-quality economic development in Russia. The accelerated development of the fuel and energy complex, as one of the important factors for the sustainable development of the economy, is currently a priority for the Russian economy, and as a result, the search for promising areas. The technology for the development and use of hydrogen energy, represented by fuel cells, has made a major breakthrough and provides a promising direction for achieving zero-emission energy use. The largest developed countries attach great importance to the development of hydrogen energy. Hydrogen energy has become an important strategic choice to accelerate the transformation and modernization of the energy sector and create new economic growth points. The purpose of the article is to analyze the state and development of hydrogen energy in the global community, including in Russia. Identifying the prospects, advantages and disadvantages of this market. In the current era, it is necessary to firmly grasp the development trend and opportunities of the global energy revolution, accelerate the cultivation and development of hydrogen energy, and accelerate Russia's transformation into environmentally friendly and low-carbon energy. The relevance of the study is to analyze the impact of the processes driving the accelerated development of hydrogen energy: key technologies in the global hydrogen energy production chain have matured, fuel cell supplies have grown rapidly, costs continue to decrease, the construction of hydrogen energy infrastructure has significantly accelerated, and regional hydrogen energy supply networks are being formed. Together, all these processes lead to an increase in the pace of development of hydrogen energy and justify the priority and prospects of this area in the sustainable development of the fuel and energy complex.
Keywords: hydrogen; hydrogen energy; fuel and energy complex (fuel and energy complex); traditional types of energy; low-carbon energy; ecology; energy transition; energy resources; energy system. 

 

L. V. Moskovtseva (Russian Presidential Academy of National Economy and Public Administration, Lipetsk branch, Lipetsk); O. V. Zhuravleva (Financial University under the Government of the Russian Federation, Moscow); O. N. Mitrofanova (Lipetsk State Technical University, Lipetsk)

Prospects of the labor market in the field of information technology in Russia

The article is devoted to the issues of the Russian labor market in the information sphere. The purpose of the study is to determine the vector of development of the Russian labor market in the field of information technology. The study used data from open sources of the Federal State Statistics Service, as well as data from a recruiting and analytical company HeadHunter.ru and reports from analytical agencies. The authors analyze the trends in the development of the labor market in Russia. The active development of the information technology market is experiencing a shortage of IT specialists. Based on the analysis, an unmet need and high demand for these employees are identified. The indicators of the IT labor market in Russia are analyzed, as well as a forecast of its state until 2026. Using regression analysis, the trend of changes in the remuneration of IT specialists over time is identified and a forecast of the average monthly accrued salary of IT specialists for 2024–2026 is made. The authors note a high demand for IT workers. Wages are steadily increasing from year to year, continuing to remain at a high level. According to the forecast made as part of the study, the authors assume that the total number of specialized technical specialists in IT companies will increase approximately the same as last year.
Keywords: labor market; information technology; information security; Russian labor market.

 

Yu. N. Shedko (Financial University under the Government of the Russian Federation, Moscow)

The concept of «new quality productive forces» in the development of Chinese industry

The paper analyses the implementation of the concept of new quality productive forces in the industry of the People's Republic of China. A description of the three main components of the concept is given: technology and innovation; industrial chains; future industrial development. It is concluded that there are potential economies of scale in strategic new industries and future industries
Keywords: industry; new quality productive forces; labour productivity; digital economy; green manufacturing; industrial chains.

 

E. V. Ganebnykh (Vyatka State University, Kirov), Yu. B. Nadtochiy (Financial University under the Government of the Russian Federation, Moscow)

Digitalization of the financial sector of the economy of the Russian Federation: trends and prospects

The article examines key trends and outlines the prospects for the digital development of the financial sector of the Russian economy. A more active development of the digital economy in the financial sector was noted in comparison with the pace of digitalization of the Russian economy as a whole. The most popular software tools and digital technologies used by financial sector organizations are named. Statistical data confirming the development of digitalization in the financial sector are presented. The main scenarios for the development of digital technologies are the consolidation of financial ecosystems, the spread of digital payments, the growth of QR code transactions, the development of the biometrics market, the introduction of augmented and virtual reality technologies, open APIs, the strengthening of the role of artificial intelligence, the predominance of government digital money, the emergence of new types of financial new products, an increase in the number of non-cash transactions. At the same time, there was a lack of clarity on the development of cryptocurrencies, largely determined by government regulation and the presence/absence of strict barriers from the regulator. 
Keywords: Russian economy; financial sector; digitalization; software; digital technologies; trends; prospects.

 

T. N. Sakulyeva (State University of Management, Moscow)

Problems and prospects of rail transport development in the city

Rail transport within the city limits makes it possible to increase the refusal to travel by private transport, reduce environmental pollution, and increase the comfort of passenger transportation. The development of rail transport in many cities is active, being an important part of the city's transport system. The article examines the problems and prospects of rail transport development.
Keywords: rail transport; metro; tram; electric trains; railway transport; passengers.

 

As. B. Mottaeva (Financial University under the Government of the Russian Federation, Moscow)

Current trends in the development of nuclear energy infrastructure

The purpose of the article is to study the role of infrastructure elements in the development of nuclear energy in Russia, taking into account the fact that the development of nuclear energy leads to an environmentally friendly energy future due to its efficient use, safety, reliability, environmental protection and emission reduction characteristics. The relevance of the article is due to the fact that from the moment of its initial application, for military and strategic purposes, to peaceful use, the development of nuclear energy, with its huge energy potential and wide prospects for use, has become an important force in resolving the energy crisis and promoting socio-economic and environmental progress in the current era.
Keywords: atom; nuclear power engineering; nuclear power engineering; nuclear safety; nuclear reactor; traditional types of energy; ecology. 

 

P. G. Grabovy, M. M. Aybazov (Moscow State University of Civil Engineering, Moscow)

The effectiveness of the balanced structural maneuver of a large-scale model of the construction industry

In the modern era, the construction sector includes both the issue of ensuring the quality of life of the population and the issue of territorial development. The current situation requires us to embark on a deep structural maneuver, to change the strategy for the development of the construction industry and urban planning as its basic component. Buyers, investors, or construction practitioners always pay attention to the dynamics of the industrial and residential real estate construction market. Modern industry experts, after in-depth research and analysis, have noted that significant changes may occur in the construction and ownership of residential real estate in the future. The purpose of the article is to explore the answers to the following questions: what exactly are these changes and how they will affect the construction industry. The relevance of the research lies in the need to introduce and determine the effectiveness of a large-scale model of balanced structural maneuver in the construction sector. As a result of the conducted research, conclusions have been formulated that confirm the relevance and importance of using a large-scale model, and also make it possible to proceed to defining a new methodological interpretation of the level of accessibility of ownership of industrial and residential real estate, taking into account the interests of all participants in the investment and construction process.
Keywords: construction; industrial and residential real estate; the concept of balanced structural maneuver; life cycle; management efficiency.

 

I. Y. Vaslavskaya, I. A. Koshkina, D. A. Mikhalev (Naberezhnye Chelny Institute the branch of Kazan Federal University, Naberezhnye Chelny)

Improving the tools for assessing the level of economic security

The article discusses the problems associated with the need to improve the tools for assessing the level of economic security in modern socio-economic conditions. Based on the main categorical characteristics of economic security, it is show that the stability of the level of economic security is determine primarily by the chosen strategy for assessing and forecasting the economic stability of various sectors of the economy in the face of modern challenges and threats. The analysis of the existing tools for assessing the level of economic security based on the use of the methodology of the resulting indicators of the quality of economic growth and economic diversification. It is proposed to supplement the tools for assessing the level of economic security with indicators for evaluating the effectiveness of public-private partnership projects and ensuring technological sovereignty. Taking into account the proposed indicators will allow for a more comprehensive approach to assessing the level of economic security.
Keywords: economic security; technological sovereignty; public-private partnership; assessment tools; threats to economic security; methodology; monitoring.

 

N. L. Krasyukova, A. M. Belyaev, E. I. Moskvitina, E. I. Voronova (Financial University under the Government of the Russian Federation, Moscow)

Topical issues of the development of social protection tools within the framework of the socially-oriented model (on the example of social insurance against industrial accidents and occupational diseases)

The scientific research is devoted to topical issues of improving the tools of social protection of the population. The purpose of this work is to analyze the elements of the system of social protection of workers engaged in work with harmful and (or) dangerous working conditions in the context of the development of a socially-oriented model. This category of people is more susceptible to industrial injuries and industrial diseases. In this regard, the improvement of the system of social insurance against industrial accidents and occupational diseases is of interest. The paper examines the problems and challenges facing the social insurance system, analyzes statistical data in the field of harmful working conditions, industrial injuries, and systematizes the tools of social protection of the population. The findings emphasize the need for a comprehensive approach to the development of social protection tools to reduce occupational injuries and occupational diseases, as well as to increase the level of social protection of workers. Within the framework of the study, the current directions for the development of social protection tools for the population are identified on the example of social insurance in this area.
Keywords: social protection of the population; social insurance; labor protection; digitalization; client-centricity; socially-oriented model; social responsibility of industrial enterprises.