KSHP. OMD №10-2025 el.dop

V. M. Davydov, V. V. Zaev, A. V. Zaev (Pacific National University, Khabarovsk)

Nickel alloy machining methods: overview and prospects

Nickel alloys are used in industry due to their unique combination of properties, including high resistance to elevated temperatures, resistance to chemical degradation, and wear resistance. Methods for improving productivity in machining nickel-based alloys are discussed. Particular attention is paid to the influence of heat treatment, metallurgical properties, machinability testing, as well as the impact of various lubrication strategies on machining and their influence on cutting tool quality. Non-traditional machining methods are also considered, including water-jet and abrasive cutting, laser cutting, and ultrasonic machining.
Keywords: nickel; alloy; machining; heat treatment; productivity.

 

Yu. E. Petukhov, P. V. Domnin, A. A. Kapitonova (MSUT «STANKIN», Moscow)

Regrinding of cutting tools with back surface having a clearance angle and guide shape in the form of a circular arc

The article is devoted to the topic of sharpening and regrinding of special indexable cutting tools having a clearance angle and guide shape in the form of a circular arc. Special attention is paid to calculating the setup parameters for implementing a new sharpening method.
Keywords: regrinding method; special indexable cutting tool; clearance angle; guide.

 

O. V. Chudina, A. Yu. Malakhov, E. A. Postnova (State Technical University – MADI, Moscow)

Surface hardening of the universal joint cross member of the KAMAZ-5490 truck drivershaft

Investigations are conducted into the causes of fatigue failure of the original universal joint cross of the KAMAZ-5490 truck's driveshaft during operation. It was shown that its working surface fails due to spalling caused by high contact loads. To improve the operational properties of the universal joint cross, steels with a higher carbon content, 45 and 30CrMnSiA, followed by thermochemical treatment, are proposed. Studies are carried out on the processes of nitriding, carbonitriding, and boriding on the surface properties of samples made from these steels. Based on a comparative analysis of the obtained results, recommendations are given on the selection of material and the method of its surface hardening during the manufacture of the KAMAZ-5490 truck's driveshaft universal joint cross, with the aim of increasing the contact strength and wear resistance of its working surface, thereby increasing the service life of this component in operation.
Keywords: chemical-thermal treatment; cementation; nitriding; carbonitration; boriding; microstructure and microhardness of the hardened layer.

 

E. M. Bulyzhev, V. N. Klyachkin (UlSTU, Ulyanovsk); Yu. B. Alyakin (UlSU, Ulyanovsk); V. G. Shuvaev (Togliatti State University, Togliatti); A. M. Zolotov (Peter the Great St. Petersburg Polytechnic University, St. Petersburg)

Improving resource conservation in the operation of synthetic cutting fluids in centralized maintenance systems at mass-production machine-building enterprises under varying process situations

This study explores the potential for improving process efficiency and repeatedly extending the service life of synthetic cutting fluids, while reducing losses during replacement. This extension is achieved through process optimization using the synergy of two groups of factors that determine the ability of cutting fluids to withstand adverse effects, and the potential of subsystems that ensure the long-term operation of synthetic cutting fluids. The conducted research not only allows us to determine the distribution of cutting fluid service life between replacements but also to distinguish between two possible manifestations of synergy: latent and explicit. In both cases, not only positive results were obtained in repeatedly extending the service life of synthetic cutting fluids, but also a methodology was developed for calculating the magnitude of synergy and the range of its variation, presented in the paper as a flowchart for calculating latent and explicit synergies. 
Keywords: synergy; entropy of the 1st kind; entropy of the 2nd kind; explicit and implicit synergy; distributed inevitable losses; losses during replacement of the coolant volume.

 

E. M. Bulyzhev (UlSTU, Ulyanovsk); Yu. B. Alyakin (UlSU, Ulyanovsk); V. G. Shuvaev (Togliatti State University, Togliatti); A. M. Zolotov (Peter the Great St. Petersburg Polytechnic University, St. Petersburg)

Centralized operation of synthetic cutting fluids in mass production machining with varying process situations

A retrospective analysis of cutting fluid use in metalworking is being conducted. Applied research is being conducted to confirm the scientific hypothesis regarding the feasibility of organizing control, monitoring, and management of the metalworking production process based on current estimates of cutting fluid entropy over time. The study examines variations in cutting fluid entropy in a centralized process monitoring system (CMS). The research is based on systematization of results and their transformation into time series over the period between cutting fluid changes. Cutting fluid variations are examined using a probabilistic-deterministic approach. The study generates digital data on cutting fluid entropy rates across all CMS systems in the complex, varying process and operational parameters, and identifies the potential for developing an indicative method for assessing control and monitoring the performance of synthetic cutting fluids, etc.
Keywords: synthetic cutting fluid; centralized application system; inevitable distributed losses; entropy; control; monitoring.

 

I. V. Deryabin (Togliatti State University, Togliatti)

On the issue of reducing the noise of internal combustion engines of vehicles

Limiting the impact of transport noise, as one of the most dangerous consequences of the rapid growth of the car fleet and their concentration in cities, is an urgent task. One of the main sources of vehicle noise is the internal combustion engine and, in particular, its fuel-air mixture intake system into the working cylinders. This paper examines the possibility of reducing the noise level emitted by the walls of the intake module housing by filling the intercostal space with a heat-resistant viscoelastic polymer material with a high damping level and introducing rigid reinforcing elements into the specified zone, which makes it possible to reduce the noise level generated by the internal combustion engine. The article presents the results of experimental studies performed on an engine stand installed in an acoustic anechoic chamber. It is concluded that the proposed technical solution has a positive effect, consisting in reducing the energy of the sound field from the housing elements of the intake system of the internal combustion engine.
Keywords: internal combustion engine; intake system; intake module; noise.

 

A. S. Metel, S. N. Grigorev, E. S. Mustafaev, Yu. A. Melnik (MSUT «STANKIN», Moscow)

Increasing the abrasive resistance of a die using a beam of fast atoms

Removal of defective surface layers can significantly improve the quality of various products. This can be done using accelerated ion beams or fast argon atoms. However, processing the inner surface of narrow channels is difficult. In this paper, a narrow beam of fast argon atoms is used to sputter and polish the inner surface of dies with a working channel diameter of 5.7 mm. Due to the large angle of incidence on the channel walls, sputtering with fast argon atoms reduced their roughness to Ra ~ 0,001 μm.
Keywords: drawing dies; surface roughness; fast atoms; sputtering; polishing; angle of incidence.

 

M. A. Volosova, I. V. Suminov, A. S Metel, T. B. Tyurbeeva (MSUT «STANKIN», Moscow)

Influence of plasma-electrolytic oxidation process factors on the through porosity and corrosion resistance of aluminum-magnesium alloy

The article presents the results of experimental studies of the influence of various plasma electrolytic oxidation (PEO) factors, such as the Na₂SiO₃ concentration in the silicate-alkaline electrolyte and its temperature, current density, and process duration, on the through porosity of the Al-Mg alloy. The effect of varying electrical discharge severity on the through porosity of the surface layer of the structural alloy, its topography and microroughness parameters, and its resistance to corrosion is studied. The through porosity is assessed on a special stand based on the results of measuring the total resistance of measuring tubes filled with electrolyte, with Al-Mg alloy samples installed at the ends. The results of gravimetric evaluation of the corrosion resistance of the samples show a direct correlation between the corrosion rate and the through porosity of the coatings formed during PEO, which can be minimized by implementing the process under the identified rational conditions.
Keywords: plasma-electrolytic oxidation; processing factors; Al-Mg alloy; through porosity; test stand; corrosion resistance.

 

D. G. Levashkin, O. N. Brega, A. V. Tolsykh, R. D. Voronov (Togliatti State University, Togliatti)

Creating unforgeable 2D codes using precision laser marking and engraving systems

This paper examines and describes a new method for creating unforgeable 2D codes, specifically QR codes, based on the phenomenon of tarnishing colors in metals, particularly titanium. A method for marking 2D codes using laser marking devices with various laser radiation parameters is proposed, which causes an oxide film of a specific color (thickness) to appear on the titanium surface. Since a potential attacker cannot know the exact radiation parameter values in advance, counterfeiting the resulting code shade is impossible. Furthermore, if an attacker were to select the required parameter values, the imperfections of marking systems, both at the software and physical levels, would prevent the exact same thermal effect on the surface as on the original. The authors demonstrate that 2D code creation may not be limited to a single tempering color. It is possible to create composite codes consisting of two, three, or more colors. Carrying out such marking would require changing the laser radiation parameters a certain number of times during the marking process. Combinations of color zones on the code plane can be either highly distinguishable visually or intentionally subtle. Furthermore, controlling the laser radiation parameters allows for influencing the texture and roughness of the marked surface. It is possible to create roughness in the form of a 2D code or, conversely, to mark to a specific depth in the material. The marking depth is optionally selected depending on the operating conditions of the part. A number of samples marked using the proposed method are presented, displaying color QR codes.
Keywords: QR code; 2D code; laser marking; tempering colors; laser radiation; non-falsifiable.

 

I. V. Shatskaya, A. V. Shpak, E. R. Zhdanov, R. A. Yafizova (RTU MIREA, Moscow)

Standardization and quality assessment of semiconductor power amplifiers

The article is devoted to the issues of standardization and quality assessment of semiconductor power amplifiers. The key characteristics affecting the efficiency and durability of reinforcement components are considered, and methods for testing and controlling product parameters are proposed. Attention is paid to the requirements of international standards and certification methods that ensure stable operation of equipment in modern telecommunication systems. The findings highlight the importance of a comprehensive approach to assessing the quality of semiconductor amplification to improve the performance and durability of modern radio equipment.
Keywords: quality management; reliability of radio engineering elements; semiconductor power amplifiers; radio electronic equipment; standardization.

 

N. L. Udaltsova (Financial University under the Government of the Russian Federation, Moscow)

Analysis of modern approaches to integrating artificial intelligence technologies into the optimization of heavy industry production lines

The article presents a systematic analysis of the integration of artificial intelligence (AI) technologies into the optimization of production lines in heavy industry. Amid intensifying competition, volatility in commodity markets, and growing environmental requirements, AI is becoming an integral component of the sector’s digital transformation. The author highlights three key application areas: predictive maintenance, computer vision systems for quality control, and digital twins. The economic impact of these solutions is evidenced by high return on investment (ROI), reductions in unplanned downtime by more than 75 %, maintenance cost savings of up to 30 %, and increased labor productivity. Analysis of empirical data shows that the greatest effect is achieved in the energy and metallurgical sectors due to the high costs of downtime and defective products. The research methodology is based on a systematic review of academic literature, industry reports, and case studies from leading industrial companies, which made it possible to integrate theoretical and practical aspects. The author demonstrates that AI implementation is not only a matter of algorithms, but also a complex strategic management task that includes building data management infrastructure, retraining personnel, and reorganizing business processes. The identified barriers are primarily related to data quality, lack of digital maturity, and resistance to change within organizations. It is concluded that AI has already moved beyond experimental technologies and has become a mature tool that provides long-term competitive advantages. Its adoption is shaping the transition from Industry 4.0 to Industry 5.0, where the emphasis shifts to a human-centric approach and AI acts as a cognitive partner that augments specialists’ capabilities. This synthesis of technology and human capital opens up prospects for building sustainable intelligent ecosystems in heavy industry.
Keywords: artificial intelligence, predictive maintenance, computer vision, digital twins, Industry 5.0.

 

D. E. Morkovkin, Ya. O. Zubov, R. R. Chugumbaev, I. N. Chernykh, N. N. Gubskaya (Financial University under the Government of the Russian Federation, Moscow); E. V. Chernikina (Russian State University for the Humanities, Moscow); G. I. Shepelin (Academy of Water Transport, Moscow)

Forecasting and optimization of business processes of industrial enterprises in the context of digital transformation of the economy

The study reveals a comprehensive picture of the transformation of management approaches in the industrial sector under the influence of revolutionary digital technologies and automated solutions. The analysis demonstrates fundamental changes in the architecture of business processes, characterized by the transition from traditional management methods to intelligent systems based on predictive analytics and machine learning. The central achievement of the work is the development of an integrated methodology that combines modern technologies of artificial intelligence, the Internet of Things, digital twins and robotic process automation. Practical application of the proposed solutions provides a dramatic increase in operational efficiency: forecasting accuracy increases by 20–30 %, the speed of making management decisions increases by 10–50 times, and the level of process automation reaches 70–90 % against the traditional 20–30 %. Industry analysis reveals specific effects of digitalization in various industrial sectors. In mechanical engineering, a reduction in inventory by 30 % and an increase in equipment utilization by 15 % are achieved. The chemical industry demonstrates a 25 % reduction in production defects and a 20 % reduction in energy resources. The metallurgical sector shows an increase in the yield of good products by 12 % and a reduction in the production cycle by 18 %. The food industry records a 35 % reduction in losses and a 20 % improvement in the quality characteristics of products. The results of the study confirm the critical importance of a systems approach to digital transformation that takes into account the technological, organizational and human aspects of change. Successful implementation of predictive and optimization systems requires not only the introduction of advanced technologies, but also comprehensive personnel training, transformation of corporate culture and ensuring reliable cybersecurity of production complexes. The scientific novelty of the work lies in the creation of a multi-level business process management architecture that integrates time series methods, neural networks, deep learning algorithms and optimization approaches into a single information ecosystem of the enterprise. The practical significance is determined by the possibility of switching from reactive to proactive management of production operations, which ensures sustainable competitive advantages in a highly dynamic market environment. 
Keywords: business process forecasting; production optimization; digital transformation; predictive analytics; machine learning; digital twins; Internet of Things; process automation; production management systems; artificial intelligence; big data; production efficiency.

 

E. N. Ramazanova (Financial University under the Covernment of the Russian Federation; BMSTU, Moscow)

Application of advanced methods of digital transformation in the oil and gas industry using graph models for dynamic analysis of hydrocarbon production processes and optimization of production parameters

The article is devoted to the study of the use of graph models as a key tool for the digital transformation of the oil and gas industry. In the context of high volatility in the global hydrocarbons market and growing competition, improving operational efficiency becomes a strategic priority. One promising direction is the concept of the «digital oilfield», within which the integration of the Internet of Things, artificial intelligence, and digital twins makes it possible to form a unified management ecosystem. Central to this process are graph models, which provide a universal mathematical framework for analyzing complex production networks and optimizing raw material flows. The research methodology is based on an interdisciplinary approach that combines graph theory, machine learning for predictive analytics, and economic-mathematical modeling. The production infrastructure is represented as a weighted directed graph whose vertices describe physical assets (wells, pumps, separators, tanks), and whose edges represent technological connections. The weights of the elements are formed on the basis of both static parameters and dynamic data from IoT and predictive maintenance systems. The Dijkstra and Ford–Fulkerson algorithms were used for analysis, allowing optimal flow routes to be determined and production volume to be maximized. Simulation results using an offshore oil production complex as a case study showed that the introduction of graph optimization reduces incident response time from 12,5 to 0,25 hours, decreases revenue losses per incident by $ 2,35 million, and reduces unplanned downtime by 45 %. Integration with PdM systems additionally made it possible to cut maintenance costs by 30 % and increase annual revenue by $ 67,93 million. Long-term NPV calculations confirmed an increase in project value of $ 211,4 million when using the graph model as part of a digital twin. Thus, graph models are not an auxiliary but a backbone element of the digitalization of the oil and gas industry. Their implementation ensures a transition from reactive management to a proactive and predictive approach, opening up opportunities for sustainable improvements in the efficiency and competitiveness of capital-intensive projects.
Keywords: digital transformation; oil and gas industry; graph models; digital twins; optimization of production processes.

 

O. V. Fokina (Vyatka State University, Kirov); V. O. Kozhina, S. A. Ryabichenko (Moscow International University, Moscow); O. V. Suzeva (State University of Education, Moscow)

Designing 5.0 in the mining industry in the digital economy

The purpose of the study is to analyze the specifics of project activity in Industry 5.0 in the extractive industry and to prepare recommendations for improving the efficiency of project development and implementation in the digital economy. Studying the dynamics of the digitalization process in the extractive industry, comparing design concepts and analyzing the features of design solutions in Industry 4.0 and Industry 5.0, identifying the limitations of the introduction of digital technologies and developing a number of recommendations to overcome obstacles in improving the efficiency of design and implementation of digital technologies in the extractive industry allowed us to achieve this goal. The results of the work are of interest to representatives of science, education and practitioners.
Keywords: Industry 4.0; Industry 5.0; extractive industry; engineering; projects; digital economy; digitalization; innovation; barriers; efficiency.

 

M. R. Safiullin (Kazan (Volga Region) Federal University; Academy of Sciences of the Republic of Tatarstan; Center of Advanced Economic Research in the Academy of Sciences of the Republic of Tatarstan, Kazan); L. A. Elshin (Kazan (Volga Region) Federal University; Center of Advanced Economic Research in the Academy of Sciences of the Republic of Tatarstan; TISBI University of Management, Kazan); D. R. Abdrakhmanova (Volga Region State University of Physical Culture, Sports and Tourism, Kazan)

Characteristics and prospects for regional industrial development in the context of sanction turbulence

This article, using descriptive data analysis methods for 2021, assesses the established parameters of import dependence in one of Russia's most industrially developed regions – the Republic of Tatarstan. The resulting assessments form the basis for identifying potential threats and risks to the sustainable development of the region's industrial sector amid the blockade of external markets, and also predetermine the main areas for implementing import substitution policy at the regional level.
Keywords: industry; import dependence; sustainable economic development; region; external market transformation; international supply chains; industrial development prospects.

 

S. M. Doguchaeva (Financial University under the Government of the Russian Federation, Moscow)

Development of mathematical models for evaluating return on investment in cloud computing technologies for large corporate structures

The article is devoted to the development of multi-level mathematical models for evaluating return on investment in cloud computing technologies in large corporate structures. In the context of the rapid growth of the global cloud services market, projected to reach $ 2,29 trillion by 2032, moving to the cloud is becoming not just a technological but a strategic decision. For practical validation of the methodology, a case study is conducted for a hypothetical corporation, Omega, comparing scenarios of modernizing on-premises infrastructure, full migration to a public cloud, and the implementation of a hybrid model. The results show that the public cloud provides the best NPV ($ 21,85 million) and IRR (58,2 %), mainly due to accelerated innovation processes and revenue growth. However, the risk analysis identified significant threats, including vendor lock-in. The hybrid model, while having a negative NPV in classical analysis, demonstrates a near break-even valuation when the value of real options is taken into account (−$ 0,5 million), as well as higher resilience to risks. Thus, the comprehensive model allows the hybrid scenario to be considered strategically preferable for long-term business adaptability.
Keywords: cloud computing; return on investment; discounted cash flows; real options; corporate strategies.

 

E. A. Okuneva (Financial University under the Government of the Russian Federation, Moscow)

Developing a simulation environment for modeling the relationships between artificial intelligence development and structural changes in the market

This paper presents the development of a simulation environment for analyzing the relationships between the development of artificial intelligence (AI) and structural changes in markets. The relevance of the topic is driven by the exponential pace of AI adoption: its use in business functions rose from 55 % in 2023 to 72 % in 2024, with generative AI demonstrating the fastest growth. Despite significant corporate investments, many companies face a paradox: productivity gains do not always translate into improved financial performance, indicating hidden barriers and the need for deeper analysis. The study’s methodology is based on agent-based modeling (ABM), which views the economy as a complex adaptive system. The simulation implements three types of agents: firms, consumers, and labor market agents. Firms make decisions about the scale of AI investments, shaping competitive dynamics and market concentration. Consumers determine the distribution of market shares through their product choices, while labor market agents model processes of worker displacement and reskilling. The model is calibrated using empirical data: productivity gains of 25–40 % and cost reductions of 15–35 % with AI adoption; World Economic Forum forecasts on job creation and elimination; and market concentration metrics (HHI). The simulation results reveal three key effects. First, increasing AI investments lead to higher market concentration and a «winner-takes-all» effect: at investments of 15 % of revenue, the market transforms into an oligopoly with HHI above 5,000. Second, the speed of technology adoption directly affects the labor market: shortening the adaptation period from 20 to 5 years increases structural unemployment more than threefold and exacerbates inequality. Third, public policy has divergent effects: antitrust regulation reduces concentration but slows innovation, whereas investments in reskilling significantly reduce social costs without affecting productivity growth. Thus, the proposed simulation environment allows AI to be considered an endogenous factor in the evolution of the economy and serves as a tool for assessing trade-offs between efficiency, competition, and social equity.
Keywords: artificial intelligence; simulation modeling; agent-based models; market concentration; structural unemployment

 

M. M. Imamov, N. B. Semenikhina (Kazan Federal University, Kazan)

Innovative methods for assessing and managing risks in enterprise digital transformation projects

The article examines the impact of digital transformation on the development of innovative approaches to strategic management in a global economy characterized by high turbulence and uncertainty. Traditional models of long-term planning are losing effectiveness, giving way to adaptive strategies in which digital technologies play a key role. The authors hypothesize that investments in digitalization affect organizations’ competitiveness not directly, but through the development of dynamic capabilities (organizational agility, responsiveness, and the ability to reconfigure resources). The results show moderate correlations between digital investments and financial metrics (r = 0,149–0,284); however, the most significant effects were operational improvements: a 43,5 % reduction in order cycle time, a 62,54 % increase in inventory turnover and a 74,3 % reduction in supply chain recovery time. 
Keywords: digital transformation; strategic management; dynamic capabilities; innovation; global economy.

 

N. E. Egorov (North-Eastern Federal University, Yakutsk); T. V. Pospelova (HSE University, Moscow)

Application of the Triple Helix model in the development of innovative economies in Russian regions

Currently, the Triple Helix concept has emerged as a viable framework capable of not only interpreting but also providing concrete measures to enhance innovation potential. A Python software product based on the Triple Helix econometric model is being developed to address a variety of practical issues in regional innovation economics. An approach to conducting computational experiments in Python, using the Triple Helix model in economic theory, is proposed. This approach is aimed at addressing a variety of practical issues in regional innovation economics. The proposed software product enables a detailed study and assessment of the current state of the innovation sector of various entities of varying scales and can be used by specialists in science management, innovation, and economic development, as well as regional analytical institutions and research organizations.
Keywords: innovation economy; Triple Helix model; Python software product; correlation and regression analysis; regional rankings.

 

S. R. Muminova (Financial University under the Government of the Russian Federation, Moscow)

Mathematical modeling of risks and benefits in the digital transformation of traditional business platforms using big data

The article is devoted to the mathematical modeling of the risks and benefits of the digital transformation of traditional business platforms using big data technologies. Modeling results using the example of the hypothetical company ManuCorp, which is transforming its business model to a platform-as-a-service format, show that the project’s mean NPV is $ 3,15 million with a 68,9 % probability of success. However, accounting for the value of embedded real options increases this figure to $ 9,04 million, which is three times the result of traditional analysis. The largest contribution comes from the expansion option ($ 4,71 million), confirming the importance of organizational ambidexterity. A comparative analysis of investment strategies shows that phased implementation with a pilot project delivers the highest expected monetary value ($ 9,04 million), whereas immediate investment has the minimal effect ($ 3,15 million). Sensitivity analysis identified critical success factors: customer retention rate, market adoption speed, and the cost of cloud infrastructure. Thus, the proposed approach demonstrates that enhanced models combining probabilistic methods and analysis of strategic flexibility provide a more realistic and strategically grounded evaluation of digital projects. This underscores the need to move from static models to dynamic tools for managing risks and benefits in the digital economy.
Keywords: digital transformation, big data, real option, risk modeling, business platforms.

 

G. S. Kovrov (North-Eastern Federal University, Yakutsk)

Assessment of the impact of scientific and innovative potential on the development of the economy of the Republic of Sakha (Yakutia)

The article is devoted to assessing the impact of scientific and innovative potential (NIP) on the development of the economy of the Republic of Sakha (Yakutia) (RS (Ya)). A research algorithm consisting of 4 stages is proposed, according to which, at stage 1, a review of literature and research is performed, based on the analysis of which a method for assessing the NIP of the region is selected and a system is compiled. NIP indicators (10 indicators) and the indicator of the region's economic development (GRP per capita). In the second stage, based on a comparative analysis of the results of the ratings of innovative development of the subjects of the Russian Federation according to the index of innovative development of the regions of Russia (IIRR), an assessment of the positions of innovative development of the RS (Ya) was carried out. At stage 3, statistical data were collected on selected indicators and model calculations of NIP and GRP per capita (GRP per rural area) of the Republic of Sakha (Yakutia) for the period 2010, 2015, 2020-2023 were carried out. At the 4th stage, the correlation and regression analysis method determined the relationship between the indicators of NIP and GRP in rural areas. A positive correlation was revealed (R=0.89). The research uses methods of assessing the innovative development of the region, rating, analysis and synthesis, tabular and graphical visualization methods, and the method of correlation and regression analysis. The results of the study confirm the hypothesis that there is a significant impact of the innovation factor on the development of the region's economy. In the future, it is of interest to study the impact of innovation potential on the economic development of municipalities in the region.
Keywords: scientific and innovative potential; GRP per capita; methods; calculations; interrelation; correlation and regression analysis.

 

M. I. Prygunova, I. K. Tumakov (Center of Advanced Economic Research in the Academy of Sciences of the Republic of Tatarstan, Kazan); E. G. Nikiforova (Kazan (Volga Region) Federal University, Kazan)

Characteristics of the development of small innovative and technological companies in the sector of small and medium-sized entrepreneurship in Russia

This article examines the functioning and development of two key forms of small and medium-sized businesses: small innovative companies (SICs) and small technology companies (STCs). The differences between these business models are analyzed, identifying the advantages and limitations of each model in the modern Russian economy. Particular attention is paid to financing, government support, and the prospects for these enterprises. This study helps identify the most effective management strategies and ways to improve the competitiveness of small innovative and technological companies in the Russian entrepreneurial landscape. 
Keywords: small and medium-sized businesses; small innovative companies; small technology companies.

 

M. R. Safiullin (Kazan (Volga Region) Federal University; Academy of Sciences of the Republic of Tatarstan; Center of Advanced Economic Research in the Academy of Sciences of the Republic of Tatarstan, Kazan); L. A. Elshin (Kazan (Volga Region) Federal University; Center of Advanced Economic Research in the Academy of Sciences of the Republic of Tatarstan; TISBI University of Management, Kazan); D. R. Abdrakhmanova (Volga Region State University of Physical Culture, Sports and Tourism, Kazan)

Assessing the vulnerability of regional economies in the context of systemic transformations in foreign markets

This article examines the chronological aspects and promising areas for ensuring sustainable economic development in Russia's regions (using the Republic of Tatarstan as an example) amidst contemporary historical transformations reflected in the transformation of the foreign economic landscape. Specifically, it addresses the vulnerability of regional economic systems and their strategic adaptability to restrictions on critical imports under the sanctions imposed in 2022–2025.
Keywords: sanctions; Russia; regions; sustainable economic development; transformation of foreign markets.

 

A. M. Delakhova, P. V. Gulyaev (North-Eastern Federal University, Yakutsk)

The impact of renewable energy sources on the northern supply of fuel and energy resources in the Republic of Sakha (Yakutia) – a general statement of the modeling problem

This article examines the impact of renewable energy development in the Republic of Sakha (Yakutia) on the volume of northern fuel and energy resource deliveries. The relevance of this issue is assessed, and economic development prospects in the decentralized power supply zone are analyzed. A review of existing alternative energy facilities launched in the region's decentralized energy zone and plans for increasing renewable energy capacity are presented. The authors propose parameters for a general formulation of the problem of mathematical modeling the impact of innovative power plant modernization on reducing transportation costs for fuel and energy resource delivery as part of the northern delivery in the Republic of Sakha (Yakutia).
Keywords: northern fuel and energy resource deliveries; solar panels; renewable energy sources; transportation challenges; Arctic; decentralized energy supply.

 

S. N. Pozdeeva (Financial University under the Government of the Russian Federation, Moscow)

Economic-statistical modeling of the impact of blockchain technologies on the efficiency of financial operations in the information technology sector

The central hypothesis of the study is that blockchain integration provides disintermediation, automation via smart contracts, and data immutability, which leads to a statistically significant reduction in transaction costs and settlement times. The methodological foundation of the study is a longitudinal analysis using econometric modeling of panel data. Given the limited availability of microeconomic data, a synthetic dataset was constructed, calibrated to industry statistics and reports from leading agencies. The sample includes 150 hypothetical IT companies of varying sizes with a time horizon of 10 years. The dependent variables considered are: average transaction cost (USD), time to complete a transaction (hours), and the operating expense ratio for data reconciliation. The key predictor is the Blockchain Integration Index (BII), which makes it possible to assess the marginal effect of the depth of technology adoption. The results of correlation analysis revealed a strong inverse relationship between the BII and all efficiency indicators (r = −0,854…−0,932). Fixed-effects regression models confirmed the hypothesis: full blockchain integration reduces the average transaction cost by USD 25,75 and shortens settlement time by 95,5 hours, which is equivalent to 4 days. These changes have a significant economic effect − accelerating capital turnover, reducing fees, and increasing data transparency. It was additionally found that the greatest benefit is achieved with deep blockchain integration into ERP systems, where automation covers reconciliation and accounting processes. Thus, the study demonstrated that blockchain is not a point solution, but a foundational technology for transforming the finance function in the IT sector. Its adoption delivers not only direct savings but also creates long-term competitive advantages by accelerating business cycles, enhancing financial resilience, and building a transparent digital infrastructure.
Keywords: blockchain; financial operations; transaction costs; disintermediation; economic-statistical modeling.

 

M. A. Troyanskaya (Orenburg State University, Orenburg); V. V. Varzin (Russian State University named after A. N. Kosygin (Technologies. Design. Art), Moscow); G. I. Shepelin (Academy of Water Transport, Russian university of transport (MIIT), Moscow); A. V. Semenov, Sh. U. Niyazbekova (Moscow Witte University, Moscow); E. M. Torbik, E. P. Petukhova, I. A. Zborovsky (Financial University under the Government of the Russian Federation, Moscow)

Digitalization and software in the context of technological sovereignty: public administration and the current state

Under the pressure of international sanctions and the withdrawal of foreign software providers, the Russian Federation launched a large-scale import substitution program in the field of digital public administration. This article presents a comprehensive assessment of the effectiveness of this process, focusing on institutional, technological, and human resource aspects. Particular attention is paid to the resilience of digital infrastructure, cybersecurity risks, and the maturity of domestic IT solutions. Based on empirical data and expert analysis, key barriers are identified, including system incompatibility, shortage of qualified personnel, and technological immaturity. The study offers practical recommendations aimed at improving the quality of import substitution and achieving digital sovereignty. The findings have practical relevance for policy development in the area of governmental digital transformation.
Keywords: digitalization; public administration; import substitution; sanctions; software; digital sovereignty; domestic IT solutions; cybersecurity; technological independence; digital transformation.

 

R. A. Polonchuk (MGIMO University, Moscow)

Theoretical approaches of the Chinese leadership to the implementation of innovations in the national defense industrial complex

This article examines the Chinese leadership's policy on implementing innovations in the national defense industrial complex. Particular attention is paid to the development of the fundamental principles and the creation of the material and technical base for implementing innovations.
Keywords: China; production; materials; dual technologies; standards; industry.

 

M. E. Kosov, T. K. Chernysheva (Financial University under the Government of the Russian Federation, Plekhanov Russian University of Economics, Moscow); S. N. Silvestrov, V. V. Eremin (Financial University under the Government of the Russian Federation, Moscow)

Industrial mortgages as a tool of state support in the face of sanctions pressure

The article discusses the mechanism of industrial mortgage application, which was introduced in Russia in 2022 as an instrument for state support for industrial enterprises. The authors analyze key conditions for preferential loan granting, its benefits and limitations, as well as the influence of individual factors on the attractiveness of this tool. Based on statistical data, main trends in industrial mortgage use have been identified, and ways to further develop this instrument in modern conditions have been suggested. The paper proposes a system of tax incentives, including preferential tax periods, specific deduction coefficients for capital expenses, and differentiated income tax rates, that could increase the attractiveness of the mechanism for businesses. The study combines a theoretical approach with an analysis of empirical data, allowing for the evaluation of not only the legal aspects of industrial mortgage lending, but also the practical outcomes of its implementation.
Keywords: industrial mortgage; preferential loan; government support for industry; interest rate subsidy; tax incentive; import substitution; industrial modernization.

 

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

New trends in the concept of expanding the export potential of Russia's nuclear energy sector

This article is devoted to the analysis of new trends in expanding the export potential of the Russian nuclear energy industry. Special attention is paid to the formation of institutional and technological conditions for entering new markets, the role of «green diplomacy», as well as the synergy between technological sovereignty and international cooperation. The article also discusses priority export destinations (Asia, the Middle East, Africa, and Latin America), the development of small-scale nuclear solutions (including floating nuclear power plants), and localization mechanisms. The conclusion is formulated about the need to adapt strategic planning to new geopolitical and environmental challenges.
Keywords: nuclear energy; export potential; Rosatom; energy diplomacy; climate agenda; carbon neutrality; low-carbon energy; digitalization; sustainable development; sanctions; international cooperation.

 

M. M. Imamov, N. B. Semenikhina (Kazan Federal University, Kazan)

The role of creative thinking and design thinking in developing innovative management strategies for small and medium-sized businesses

The article explores the role of creative thinking and design thinking in developing innovative management strategies for small and medium-sized enterprises (SMEs) in Russia. Despite the significant contribution of the SME sector to the economy its innovation potential remains largely untapped due to administrative barriers, limited access to financing, and talent shortages. To adapt the findings to the specifics of SMEs, quantitative modeling was employed to simulate the effect of implementing design thinking. The assessment is performed using a set of KPIs, including financial (revenue growth, profitability), operational (Time-to-Market, idea conversion rate), and strategic (customer lifetime value, return on innovation) indicators. The modeling results show that the implementation of design thinking leads to revenue growth 2,5 times higher than the control group, an increase in profit margin by 2,55 percentage points, and a 21,1 % reduction in customer acquisition cost. At the operational level, a 40,2 % reduction in Time-to-Market is observed, and the idea-to-project conversion rate rises from 12,4 to 29,6 %. Correlation analysis confirm a strong relationship between the maturity of design thinking and the strategic resilience of a business.
Keywords: creative thinking; design thinking; small and medium-sized enterprises; innovative strategies; management models.

 

Sh. A. Osmanov, V. V. Klyuy, D. E. Zavyalov (Saint-Petersburg State Fire Service University of EMERCOM of Russia, Saint-Petersburg)

Optimization of search and detection of victims in accidents in metallurgical industries related to the collapse of buildings

The rapid growth of the metallurgical industry, coupled with the current geopolitical situation and enormous mineral reserves, entails an increase in industrial capacity and an increase in production volumes. However, the man-made load also increases and the likelihood of various types of accidents and incidents at metallurgical enterprises increases. In turn, they are characterized by such distinctive features as the collapse of buildings, the threat of release of hazardous substances and elevated temperatures. All this entails a large amount of material and social damage in the event of accidents at such enterprises. The faster the victims are found, the higher the likelihood that they will be saved. An analysis of studies devoted to the issues of optimizing the search and detection of victims in accidents at metallurgical plants associated with the collapse of buildings showed that most of them are devoted to the analysis of the causes of emergency situations and the causes of industrial injuries. Some of the works propose the use of radar systems to search for victims under rubble. However, there are no works that take into account the specifics of metallurgical production, in connection with this there is a need to develop appropriate scientific and methodological tools. In the article, based on existing studies, optimization of the search and detection of victims in accidents at metallurgical production facilities associated with the collapse of buildings was carried out using the method of branches and boundaries, as well as the Hungarian method. The use of which made it possible to reduce the route covered by the search group by 32 and 42 %, respectively.
Keywords: optimization; search; detection; victims; metallurgical production; accident; collapse; building collapse.

 

Sh. A. Osmanov, A. G. Nesterenko, D. E. Zavyalov (Saint-Petersburg State Fire Service University of EMERCOM of Russia, Saint-Petersburg)

An approach to assessing the maturity level of the safety culture of employees of a mining and processing plant using questionnaires

Ensuring the safety of employees of mining and processing plants is the basis for their smooth and effective operation. However, at present, there are no scientific and methodological tools for assessing the maturity level of safety culture among employees of mining and processing plants. In this regard, the article develops a corresponding questionnaire consisting of 27 questions and possible answers. Its application will determine the level of knowledge of employees about safety rules and requirements at work and the level of responsibility for their actions and the actions of their colleagues, study the attitude of employees to safety issues and their willingness to comply with them, and assess the effectiveness of the system for training and informing employees about safety issues. As part of further research directions, the developed approach will be used to assess the maturity level of safety culture among employees of the mining and processing plant using a specific example and for further development of recommendations for the formation of a safety culture among employees of the mining and processing plant. The practical value of the article lies in the development of scientific and methodological tools for assessing the maturity and continuous monitoring of safety culture. This allows timely identification of problem areas in this area, assessment of the effectiveness of the technologies being implemented and increase the involvement of personnel in this process.
Keywords: approach; assessment; maturity level; safety culture; mining and processing plant; questionnaire method.

 

M. V. Polevaya, E. V. Kamneva, N. N. Shurakova (Financial University under the Government of the Russian Federation, Moscow)

Factors affecting the attitudes of different age groups to retirement age changes in Russia

This study analyzes the key factors determining the attitudes of Russian citizens of various age groups toward raising the retirement age in the context of the pension reform implemented in 2019. It examines the socioeconomic, demographic, psychological, and informational determinants of the formation of value judgments regarding the pension system transformation among different age groups. Based on representative sociological data and statistical analysis, significant differences in perceptions of the pension reform were identified between representatives of the younger (18-35), middle (36-54/59), and older (55/60+) generations. A correlation was established between age, employment status, level of awareness, and attitude toward the retirement age change. The study demonstrates that the most negative perceptions are characteristic of the pre-retirement age group, which found itself in the most vulnerable position during the pension system reform. The younger generation exhibits a more indifferent attitude, due to the temporal distance of the retirement age and a focus on alternative strategies for financial security in old age. The obtained results allow us to formulate recommendations for adjusting state pension policy, taking into account a differentiated approach to different age cohorts. This has significant practical value for reducing social tensions and ensuring the sustainability of the pension system in the context of demographic aging in Russia.
Keywords: pension reform; age groups; retirement age; demographic aging; social adaptation; pre-retirement population; generational analysis.

 

V. V. Perskaya, D. E. Morkovkin (Financial University under the Government of the Russian Federation, Moscow); Ya. Wang ((Shenzhen University, Shenzhen, China)

Technological factors of transformation of world economic processes in the context of the Fourth Industrial Revolution

The Fourth Industrial Revolution represents a qualitatively new stage in the development of the global economic system, characterized by the convergence of digital, physical, and biological technologies within the neo-Schumpeterian paradigm of endogenous technological development. This phenomenon requires a rethinking of the classical Heckscher-Ohlin-Samuelson theories of international trade and Michael Porter's neotechnological concepts in the context of the formation of global innovation ecosystems. The research is aimed at a comprehensive analysis of the technological determinants of the transformation of world economic processes through the prism of Kondratiev's theory of long waves, Glazyev-Lvov's concept of technological structures and the Nelson-Winter evolutionary economic theory. The methodological basis is based on the Haken-Prigozhin system-synergetic approach, the North-Williamson institutional theory of technological change, as well as the Christensen concept of destructive innovation, which makes it possible to consider technological innovations as endogenous factors of structural shifts in the architecture of the global economy. Methods of economic and mathematical modeling of technological diffusion within the framework of the Fischer-Prye logistic model, comparative institutional analysis of national innovation systems using the Lundwall-Johnson methodology, as well as econometric panel analysis methods were used to assess the impact of digitalization on international trade parameters. The empirical base consists of statistical data from UNCTAD on the development of the digital economy, WEF global competitiveness indices, OECD databases on science and technology, McKinsey Global Institute materials on the diffusion of digital technologies. The key patterns of technological transformation of global economic processes in the context of technological paradigm shifts have been identified. It is established that the technological revolution initiates the formation of the sixth technological order according to the Kondratiev-Glazyev classification, based on the convergence of NBIC technologies (nano-, bio-, info-, cognitive) and characterized by the network architecture of global value chains. A conceptual model of technologically deterministic transformation of world economic relations has been developed that integrates Haken's theory of self-organizing systems, Dossi-Orsenigo's concept of technological regimes, and Dunning's institutional theory of international trade, including four levels of impact with feedback loops and hysteresis loops. Promising areas of adaptation of national economies to technological challenges through the formation of adaptive innovation ecosystems and institutional mechanisms for regulating technological diffusion have been identified.
Keywords: the fourth industrial revolution; the neo-Schumpeterian paradigm; technological structures; evolutionary economics; digitalization of the world economy; cyberphysical systems; technological singularity; NBIC convergence; institutional theory; world economic processes.