KSHP. OMD №12-2025 el.dop
D. V. Tsukanov (Branch UEC NIID, Moscow); G. S. Sevalnev (All-Russian Scientific Research Institute of Aviation Materials, Moscow); N. N. Zubkov (Bauman Moscow State Technical University, Moscow)
Investigation of corrosion resistance of 12KH18N10T steel dies obtained by deforming cutting with embedded hard lubricants
The article examines the effect of deforming cutting on the overall corrosion resistance of austenitic steel 12X18H10T after exposure in a salt mist chamber for 170 and 900 hours. The results showed that deforming cutting leads to an increase in the rate of corrosion. The introduction of thermally expanded graphite into the intercostal gap contributes to the formation of an electroplating and leads to a significant increase in the rate of corrosion.
Keywords: austenitic steel; deforming cutting; corrosion rate; thermally expanded graphite
R. U. Kamenov, A. N. Popov (Togliatti State University, Togliatti); Yu. V. Titov (Togliatti State University, Togliatti; Omsk State Technical University, Omsk); P. N. Shenberger (Samara Federal Research Center of the Russian Academy of Sciences, Togliatti)
Atomistic modeling of the effect of diamond crystallographic orientation on strength behavior under surface plastic deformation
The study presents an atomistic investigation of the influence of crystallographic orientation of diamond single crystals on their mechanical response under conditions simulating surface plastic deformation (burnishing). Within the framework of molecular dynamics simulations (LAMMPS; Tersoff potential; a = 3.567 Å), three orientations with the loading axis along [100], [110], and [111] are analyzed. For each case, an identical geometric stress concentrator (a notch) was introduced, and the global stress–strain curves, the local «grip reaction», and maps of principal stresses near the crack tip are computed. It is shown that in the presence of the notch, the maximum stresses before fracture are close for [100] and [111] orientations, reaching approximately 138–140 GPa (at engineering strains of 0.033 and 0.017, respectively), whereas the [110] orientation exhibits a slightly lower strength (133 GPa, 0.015). The key difference lies in the crack trajectory: in the [111] crystal, an early deflection of the crack front into the {111} plane – corresponding to a lower surface energy – is observed, while in [100] and [110] the crack propagated linearly along the initial notch plane. The obtained results confirm the critical role of crystallographic anisotropy in fracture resistance and allow practical recommendations for diamond burnishing tools: it is preferable to orient working faces along {100}/{110} and avoid exposure of {111} planes on the contact surface, thereby reducing the risk of cleavage. The limitations of the MD scale and directions for further validation (quasi-static loading, phase-field and finite-element models, reactive potentials) are discussed.
Keywords: diamond; crystallographic orientation; surface plastic deformation; burnishing; molecular dynamics; fracture; crack deflection; surface energy; elastic anisotropy; Tersoff potential.
I. V. Deryabin (Togliatti State University, Togliatti)
On one approach to reducing the noise of a vehicle's internal combustion engine
Reducing noise pollution in residential areas is currently considered a pressing issue, so the issue of reducing transport noise is receiving increased attention. The most intense sources of noise are vehicles equipped with internal combustion engines. This study examines the possibility of reducing engine noise by using porous sound-absorbing elements in the crankshaft pulley design. The results of experimental studies conducted on an engine rig mounted in an anechoic chamber are presented. It is concluded that installing the pulley on the engine crankshaft is feasible to reduce the energy of the sound field in the engine compartment of a vehicle.
Keywords: internal combustion engine; crankshaft; pulley; torsional vibration damper; sound-absorbing material; noise.
V. A. Popov (NUST MISIS, Moscow)
Use of fullerenes as reinforcing particles in metal-matrix composites
The use of mechanical alloying made it possible to produce composites with aluminum and chromium matrices using fullerenes as reinforcing particles. Nanodiamond particles were first added to the chromium matrix composites. The aluminum composites contained 5–20 % fullerenes, while the chromium composite contained 10 % nanodiamonds and 10 % fullerenes. The chromium and nanodiamonds were first mixed, followed by the addition of fullerenes. The feasibility of producing metal matrix composites with fullerenes as reinforcing particles was demonstrated.
Keywords: nanoparticles; fullerenes; nanodiamonds; aluminum; chromium.
S. V. Kurovsky, D. A. Mishin (Higher School of Education LLC, Odintsovo)
Nanoscale corrosion-resistant coatings: mechanisms of barrier and passivation protection
This study analyzes the mechanisms of barrier and passivation protection of nanostructured coatings for pipelines subject to electrochemical corrosion in aggressive environments. The influence of nanoparticle size, morphology, and dispersion on the protective properties and adhesion of the coatings was determined, and the diffusion of aggressive agents was modeled. The obtained results have practical significance for Russian oil and gas companies in improving the efficiency and durability of pipeline systems.
Keywords: pipeline transport; nanoscale coatings; corrosion-resistant coatings; protection methods; barrier protection mechanisms; passivation protection mechanisms; nanostructured coatings.
S. V. Kurovsky, D. A. Mishin (Higher School of Education LLC, Odintsovo)
Nanomodified drag reducers and their impact on flow hydrodynamics
This study examines nanomodified drag reducers as a promising alternative to traditional polymer additives for reducing hydraulic resistance in pipelines. The effect of nanoparticles and polymers on near-wall turbulence is analyzed, which can reduce the energy consumption of pumping stations. The results of this study can be applied by oil and gas companies to improve the efficiency of energy transportation.
Keywords: pipeline transport; nanomodified drag reducers; nanosized polymers; hydraulic resistance; pipeline system flows; interaction mechanisms; pumping station energy consumption.
I. S. Maksimov, S. A. Galanskiy (Volga State University of Railway Transport, Samara)
Forming a repair profile of rails and switching elements by grinding with a circle periphery
A study is conducted on the method of profile grinding of the working face of the rail head using a special grinding wheel. The design and characteristics of the used grinding wheel, which is designed for MC-3 type machines and is made of 38AF36P6B B3 zirconium electrocorundum, were examined. The experimental studies are conducted on samples of R65 grade rails of the DT350 category made of E76HF steel using the method of volume hardening. It is established that the use of the periphery of a shaped wheel allows for an even distribution of the load between individual abrasive grains, minimizes stress concentration and extends the service life of the wheel. Technological analysis is shown that the destruction of the grain is predominantly mechanical in nature, which ensures uniform working conditions for each individual element of the wheel and prevents premature wear. Due to the uniform impact of all grains, high accuracy and quality of processing of rail surfaces are achieved, which significantly increases the durability of rails and reduces the cost of operating railway infrastructure. The proposed method is an effective solution for improving the reliability and durability of railway tracks.
Keywords: railway track; rail grinding; abrasive wheel; wheel periphery; grinding shaped wheel; grinding wheel destruction process; wheel wear; electrocorundum.
L. E. Shvartsburg, V. V. Avdonichev, A. O. Kiselev, A. D. Pakhomov (MSUT «Stankin», Moscow)
Improving air cleaning efficiency in metalworking shops based on automated air exchange control
The article discusses modern approaches to increasing the efficiency of air purification systems in industrial facilities through the implementation of automatic control of aspiration processes. The analysis of existing filtration and ventilation technologies presented in Russian and international research is provided, along with a description of engineering solutions enabling adaptive regulation of air exchange parameters during metal machining. Particular attention is paid to energy efficiency, fire safety, and the integration of intelligent control algorithms. As an author’s proposal, a design of a local aspiration system equipped with pressure and dust concentration sensors is presented, providing dynamic control of suction power depending on machining allowance.
Keywords: aspiration; automation; air filtration; energy efficiency; machining; ventilation; intelligent systems.
G. G. Kiselev (Volga State Transport University, Samara)
Automated system for monitoring the stocking rate of spare parts in technological racks
This article explores the use of automated racks as an effective tool for improving inventory management efficiency at railway companies. Automated racks leverage digital technologies that effectively optimize component retrieval and retrieval processes, reducing the time required to complete these operations and eliminating human error in warehouse management.
Keywords: monitoring; automated control system; racks; optimization; spare parts; maintenance center.
O. Yu. Gorodetskaya, Ya. L. Gobareva, V. E. Kosarev, M. E. Rychago (Financial University under the Government of the Russian Federation, Moscow)
Design of an intelligent platform for managing financial flows based on blockchain technologies for small and medium-sized enterprises
The study focuses on the design of an intelligent financial flow management platform for small and medium-sized enterprises based on blockchain technologies and smart contracts, aimed at overcoming chronic barriers to access to capital, reducing transaction costs, and increasing operational transparency under conditions of high interest rates and significant operational risks; the aim of the research is to substantiate the architecture of such a system and to quantify its impact on key financial metrics of SMEs, including operating expenses, settlement speed, working capital turnover, cost of capital, and return on investment. The results show that eliminating intermediaries and automating verification reduce average fees for domestic and cross-border payments, shorten settlement time, decrease the operating expense ratio, cut verification costs of turnover, and accelerate the accounts receivable turnover period. Integration of DeFi protocols increases the approval rate of loan applications, lowers the weighted average rate, reduces collateral requirements and accelerates funding acquisition. At the same time, significant barriers are identified which can be overcome through phased pilots and consortium cost-sharing models; an end-to-end economic calculation demonstrates the achievement of a positive net cash flow from the second year and a cumulative ROI of about 157 % over a three-year horizon, confirming the economic feasibility and strategic significance of implementing the platform as a catalyst for digital transformation and enhanced competitiveness of SMEs.
Keywords: Information systems, financial technologies, blockchain, smart contracts, financial flows, DeFi, SME.
V. Yu. Pauls (Northern Trans-Ural State Agricultural University, Tyumen)
Steels and hard alloys for cutting tools of woodworking equipment
This paper examines steels and hard alloys used to manufacture cutting tools for woodworking equipment. The information presented can be used in the development of new structural materials, wear-resistant coatings, and manufacturing and hardening technologies for woodworking tools to improve their durability, strength, and cost reduction.
Keywords: woodworking equipment; cutting tool; steel; hard alloys; forestry complex.
Shinkaryov A. S., Gridnev M. A. (MISIS National University of Science and Technology, Moscow)
Application of recycled plastic in 3D printing: a review
The review examines the current state and prospects of using recycled plastics in additive manufacturing technologies, with a focus on fused deposition modeling (FDM) and fused particle fabrication (FPF). The paper summarizes data on the main types of secondary polymers used in 3D printing, including PET, PLA, PP, and PE, analyzing their sources, recycling processes, and properties after multiple processing cycles. The study highlights the technological stages of waste transformation into filament and pellets, the influence of raw material purity, extrusion parameters, and moisture content on the mechanical characteristics of printed parts. Attention is given to the degradation mechanisms of polymers and methods for restoring their properties through additives, chain extenders, annealing, and fiber reinforcement. The review also outlines advances in automated sorting, artificial intelligence–based process control, and quality monitoring during printing. Despite the observed decrease in strength compared to virgin materials, recycled plastics can maintain up to 80–90 % of their mechanical performance while significantly reducing costs and environmental impact. The study emphasizes the importance of standardizing secondary materials and developing composite solutions to enhance circular economy implementation.
Keywords: Additive Manufacturing, Fused Deposition Modeling, recycling, secondary polymers, polymer waste.
A. S. Zueva (Lomonosov Moscow State University, Moscow); I. V. Lipatova (Financial University under the Government of the Russian Federation, Moscow)
Building models of public financial control in countries around the world
State influence on the economy in market conditions presupposes a system of legislative, executive and supervisory measures implemented by competent state institutions and public organizations in order to adapt the socio-economic system to existing conditions. State financial control is one of the main means of implementing the financial and legal policies of countries, as well as the most important lever of the financial mechanism. Its purpose is to facilitate the successful implementation of financial strategy and tactics, as well as the expedient and effective allocation and use of financial resources. A high level of legality and discipline in the sphere of formation, distribution and use of public funds is one of the criteria of a rule-of-law state. The issues of the construction and functioning of state financial control in the Russian Federation, as well as its further development within the framework of a unified model of state financial control, taking into account foreign experience, are a very relevant object of scientific research.
Keywords: model, finance, financial control, state, society, economy, macroeconomics, macroeconomic activity.
A. G. Batukhtin, V. I. Rudoy, A. E. Noskova (Transbaikal State University, Chita)
Comparative analysis of aerodynamic drag of plasma ignition systems with a straight-through and swirl nozzle
This paper presents a comparative analysis of the aerodynamic resistance of plasma ignition systems equipped with straight-through and swirl nozzles. The study combines numerical simulation and bench-scale experiments on a unified mixing rig (air mixture–plasma-forming gas) while accounting for the kinematics of pulverized-coal particles. Based on designed experiments, linear and quadratic regression models of the local loss coefficient were identified. The quadratic models substantially improve approximation accuracy and reveal nonlinear sensitivity of the pressure drop to the fraction of air injected through the nozzle, the solids loading, and the particle-size factor. The straight-through and swirl configurations differ in the signs and magnitudes of interaction terms, indicating the roles of centrifugal effects and particle redistribution in the mixing zone. Engineering guidelines are formulated to reduce pressure losses and to select the operating regimes.
Keywords: plasma ignition; plasma torches; swirl nozzle; straight-through nozzle; aerodynamic resistance (pressure drop); pulverized coal; gas–solid two-phase flow; regression modeling; mixing of streams.
S. K. Toigambaev, S. S. Gusev (Russian State Agrarian University-Moscow Timiryazev Agricultural Academy, Moscow); M. A. Tleuzhanova (International University of Engineering and Technology, Almaty, Republic of Kazakhstan); A. V. Semenov, Sh. U. Niyazbekova (Moscow Witte University; Research and Education Center «Sustainable development», Moscow); V. V. Varzin (Russian State University named after A. N. Kosygin (Technologies. Design. Art), Moscow); A. Z. Namitullina, E. P. Petukhova, I. A. Zborovsky (Financial University under the Government of the Russian Federation, Moscow); I. O. Ryzhova (Russian University of Cooperation, Mytishchi)
Development of the forging industry: state support, tax benefits, financial initiatives, global trends, and innovative technologies
The relevance of the chosen research topic. The development of blacksmithing in modern countries remains highly relevant due to the combination of craft traditions and industrial innovations. The article examines financial initiatives, tax incentives, government support, and taxation practices in the global market. The article presents global statistics on income in the blacksmithing industry, which varies by region and segment, as well as ZIPPIA statistics on the differences in blacksmith salaries based on education levels.
Keywords: competitiveness of blacksmithing; government support; craft blacksmiths; industrial forging enterprises; tax holidays; industrial blacksmithing enterprises; financial initiatives; innovative production technologies.
T. G. Popadyuk, E. N. Gavrilova (Financial University under the Government of the Russian Federation, Moscow)
Mechanisms for forming and balancing an innovation project portfolio in capital-intensive industries using real options and machine learning methods
The article substantiates the need to move from traditional DCF/NPV approaches to a hybrid model for forming and balancing portfolios of innovation projects in capital-intensive industries that accounts for managerial flexibility and high external uncertainty; the aim is to develop and trial a methodology integrating real options analysis (ROA) and machine learning methods for strategically sound project selection and enhanced portfolio resilience. The methodology comprises K-means clustering for strategic segmentation of the project pool by risk, maturity (TRL), investment scale, and volatility; predictive modelling based on a neural network to extract objective inputs for option schemes (probability of technological success and expected cash-flow volatility); valuation of embedded options (deferral, expansion, abandonment) via binomial lattices; and the combination of NPV with ROV into an expanded metric, ENPV; portfolio optimisation with budgetary and diversification constraints and scenario stress testing then follows. The discussion highlights managerial effects: a shift to data-driven processes, the creation of an analytical framework (project data, ML models, integration into the budget cycle), and a reorientation from single «best» projects to a strategically balanced combination of clusters; limitations relate to the hypothetical nature of the case, algorithm selection, and the need for validation on real data, with directions for development outlined (portfolio options, RL for decision dynamics).
Keywords: innovation portfolio; real options; machine learning; TRL; ENPV.
N. L. Udaltsova (Financial University under the Government of the Russian Federation, Moscow)
Evolution of corporate innovation management models in Russia’s industrial sector under the impact of digital transformation and global technological shifts
The article analyses the evolution of corporate innovation management models in Russia’s industrial sector against the backdrop of accelerating digital transformation and global technological shifts, with the aim of identifying which organisational and investment configurations convert rising outlays into technological breakthroughs and productivity growth; the empirical base covers 2018–2024 and combines quantitative analysis of statistics (dynamics of innovation and digital activity, cross-industry comparisons, correlation-regression estimates) with structural and substantive interpretation within the frameworks of open innovation, dynamic capabilities, and business digital transformation. It is shown that, despite overall growth in innovation activity and spending on digitalisation, an «investment–productivity paradox» persists – a significant labour-productivity gap with global leaders indicating the primacy of the managerial model over the volume of investment; an effect of «digital absorption» is identified as the time lag between the deployment of digital technologies and subsequent outcomes in the form of innovative products and efficiency. A sectoral breakdown records a «two-speed» structure: high-technology industries with a higher share of R&D expenditure exhibit more substantial productivity gains, empirically corroborating the shift from «catch-up modernization» based on imported technologies to endogenous technological development grounded in in-house research and ecosystem interaction with science and universities. Correlation analysis indicates a tighter association of return on assets with investment in software, platform solutions, and internal R&D compared with the acquisition of machinery and equipment, characterising a shift towards an asset-light model oriented to intangible assets and data. Practical implications include a rebalance of corporate budgets in favour of R&D, digital platforms, and human capital; a reconfiguration of organisational capabilities (research portfolio management, data analytics, ecosystem management); and policy measures that stimulate the diffusion of advanced practices (industry-science interfaces, knowledge-sharing platforms, managerial training), subject to constraints related to sectoral heterogeneity, time lags, and the need for longitudinal monitoring.
Keywords: innovation management; digital transformation; R&D; intangible assets; labour productivity.
D. V. Semikin (Volgograd Institute of Management, branch of RANEPA, Volgograd); S. N. Polenova, M. V. Kosolapova (Financial University under the Government of the Russian Federation, Moscow)
Distribution process management in an industrial enterprise
This article presents the results of a study on distribution process management at an industrial enterprise. It examines the nature and functions of distribution. The importance of choosing distribution channels and their functions within an industrial enterprise is analyzed. Various distribution strategies for an industrial enterprise are presented.
Keywords: industrial enterprise; distribution; distribution channels; distribution strategies.
N. L. Udaltsova (Financial University under the Government of the Russian Federation, Moscow)
Integration of lean manufacturing and agile development methodologies into the process of industrial innovation management and its impact on time to market and quality
The article examines the synergistic effect of integrating lean manufacturing and agile development methodologies in the context of industrial innovation management, addressing the challenge of simultaneously accelerating innovation cycles and enhancing operational quality. The aim of the study is to empirically test the hypothesis that a purposive combined Lean–Agile model shortens time to market and reduces defect rates without compromising economic outcomes. Practical implications include tuning the position of the decoupling point, creating cross-functional teams, and investing in training and a culture of continuous improvement. Limitations are associated with the use of simulated data; further work is planned on case studies and the development of a Leagile maturity model. The contribution of the study lies in quantitatively calibrating the relationships between value-stream practices and business outcomes, forming the basis for a managerial roadmap: selection of metrics, planning cadences, and portfolio governance mechanisms for innovation. Future research avenues include adapting the model to multi-tier supply chains and integrating digital twins for end-to-end validation and monitoring.
Keywords: lean manufacturing; Agile; Leagile; Time-to-Market; quality.
T. V. Aleksashina, I. V. Razinkina, N. Yu. Barkova (Financial University under the Government of the Russian Federation, Moscow); A. B. Veshkurova (Financial University under the Government of the Russian Federation, Russian University of Transport, Moscow)
Strategies for managing intellectual capital in high-tech industry to achieve sustainable development goals and enhance corporate competitiveness
The article examines strategies for managing intellectual capital in high-tech industry as a tool for simultaneously enhancing corporate competitiveness and achieving sustainable development goals, setting the objective of empirically assessing the contribution of human, structural, and relational capital to financial and ESG outcomes and identifying best managerial practices for their integration. The discussion underscores the need for portfolio management of the three IC components, the recalibration of success metrics beyond R&D/patent counts, and the development of «green human» and «green relational» capital; limitations stem from the use of proxies and a bias toward codifiable assets, while prospects include standardising the measurement of «green IC», longitudinal case studies, and industry benchmarks.
Keywords: intellectual capital; high-tech industry; sustainable development; human capital; competitiveness.
Yu. G. Semikina (Volgograd Institute of Management, branch of RANEPA, Volgograd); S. N. Polenova, R. I. Amirova (Financial University under the Government of the Russian Federation, Moscow)
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Using Big Data technologies to improve the efficiency of operational management of industrial enterprises
This article examines the application of Big Data concepts to support operational management at industrial enterprises. It outlines the key objectives of operations management, including in the context of implementing Industry 4.0. It also examines the concept of Big Data and the need to enhance enterprise competencies in this area. It also presents a six-stage model for the sequential implementation of Big Data in operational management, according to which the scope of data integration gradually expands at each stage, thereby determining the capabilities for supporting decision-making at subsequent management levels.
Keywords: Big Data; operations management; operational management; Industry 4.0; Industrial Internet; cyber-physical systems.
I. N. Makarov, T. V. Shchukina (Lipetsk branch of RANEPA, Lipetsk)
Strategies for integrating life-cycle contract management and asset management in the municipal infrastructure of large cities using digital twins and end-to-end analytics of performance indicators
The study aims to develop a strategy for integrating asset management and life-cycle contract management in the municipal infrastructure of large cities on the basis of digital twins and end-to-end analytics of performance indicators, designed to overcome the systemic crisis of network deterioration and to eliminate the «owner–operator» interest antagonism within life-cycle contracts. Methodologically, the work is conducted as desk research using a systematic literature review and a meta-synthesis of quantitative data across industry cases; a multi-level integration architecture is proposed that brings together IoT/SCADA, BIM, and the digital twin into a «single source of truth» feeding two loops: predictive maintenance in asset management (PdM) and automated monitoring of SLA compliance within life-cycle contracts. The results demonstrate measurable economic and managerial effects. The discussion shows that CAPEX savings due to modeling effectively finance the deployment of the digital-twin platform, while subsequent OPEX reductions create a stable cash flow, forming a self-sustaining efficiency loop; at the same time, information asymmetry between the client and the operator is eliminated, and risks are reallocated on the basis of objective data. It is concluded that a shift from a reactive to a predictive model is warranted, in which the integration of asset management and life-cycle contracts grounded in digital twins and end-to-end analytics becomes the core of resilience, tariff predictability, and improved service quality; conditions for scaling (data-exchange standardization, open platforms, deepening of AI models) are identified, and practical KPIs are proposed for monitoring the clustering of effects and compliance with SLAs.
Keywords: digital twin; asset management; life-cycle contract; municipal infrastructure; end-to-end analytics.
I. N. Makarov, T. V. Shchukina (Lipetsk branch of RANEPA, Lipetsk)
Risk allocation for cost, schedule, and quality in life-cycle contracts in district heating and water utilities under tariff regulation and sustainability requirements
The paper examines how, under tariff regulation and sustainability requirements, to structure a risk allocation matrix for cost, schedule, and quality when concluding full life-cycle contracts (LCCs) in district heating and water utilities. The relevance stems from critical wear of network infrastructure (up to 75 %) and a shortage of investment resources amid a need for modernization of at least 4,5 trillion rubles with limited budgetary support; the spread of LCCs faces a regulatory conflict between the logic of PPP and cost-plus pricing. Materials include the regulatory framework (concessions, heat and water supply), regulatory practice, and a corpus of academic and industry publications; methodologically, economic–statistical and comparative-legal analysis are applied, as well as simulation-based financial–economic modeling of a typical 25-year water-utility modernization project (CAPEX 8,5 billion rubles) with calculation of NPV, IRR, and DPP under three tariff models: «cost plus», RAB, and “inflation minus.” The discussion interprets «regulatory risk» as key and derives a practical rule of thumb: transferring operational schedule and quality risks to the concessionaire is efficient only with an institutionally protected tariff mechanism (RAB or a contractually fixed «inflation minus») and automatic budgetary compensators for political decisions. It is concluded that a shift is needed from a compensatory, cost-based model to an incentive-based one that ensures bankability without an unacceptable tariff burden.
Keywords: life-cycle contracts; tariff regulation; RAB regulation; risk allocation; district heating and water supply.
M. V. Kosolapova, S. M. Doguchaeva, S. V. Savina, R. I. Amirova (Financial University under the Government of the Russian Federation, Moscow); T. B. Turishcheva (Plekhanov Russian University of Economics; Financial University under the Government of the Russian Federation, Moscow)
Risks and barriers to industrial enterprise management in the process of digital transformation
This article provides a comprehensive analysis of the managerial and economic risks and barriers arising during the digital transformation of industrial enterprises. It is demonstrated that the key challenges are not technological but organizational and managerial in nature. Key risk groups are identified and systematized: strategic and leadership, organizational and cultural, process-related, competency-related, and communication-related. The need for an integrated approach that synchronizes changes in strategy, organizational structure, and corporate culture for the successful implementation of digital transformation is emphasized.
Keywords: digital transformation; industrial enterprises; managerial risks; economic risks; implementation barriers; organizational structure; risk assessment; risk management methods.
T. N. Sakulyeva (State University of Management, Moscow)
Supply chain management: methodology for efficiency assessment in modern conditions
The assessment of economic efficiency in modern conditions is no longer based solely on the cost-benefit ratio. In the context of rapidly changing technological paradigms, the effectiveness of economic activity is increasingly determined by the organization's ability to adapt strategically and develop ahead of schedule. The article proposes a methodology for evaluating the effectiveness of supply chains in modern conditions. The article analyzes the current state and prospects for further development of the Russian economy in the context of the creation of flexible adaptive mechanisms capable of responding to changing external conditions.
Keywords: supply chains, efficiency, economic development, imports, exports, and import substitution.
L. A. Ezhova (Financial University under the Government of the Russian Federation, Moscow)
Intelligent decision support system based on semantic data analysis
The objective of this study is to develop a conceptual and methodological model of an intelligent decision support system (DSS) based on semantic data analysis and ontological knowledge modeling. The relevance of this topic is determined by the need to improve the quality of management decisions in the face of information overload and the growing share of unstructured data in corporate and government systems. A theoretical model for integrating natural language processing (NLP), semantic search and contextual analysis into a unified architecture of an intelligent DSS is shown. A structure for an intelligent DSS is proposed, including modules for data collection, semantic normalization, contextual interpretation, and machine reasoning. A formula for an integrated assessment of decision relevance bases on semantic similarity weighting coefficients is developed, enabling intelligent selection of alternatives.
Keywords: intelligent system; decision support; semantic data analysis; ontological modeling; natural language processing; cognitive analytics; artificial intelligence.
Ya. O. Zubov, S. A. Sergeev (Financial University under the Government of the Russian Federation, Moscow)
Data monetization mechanisms and the effectiveness of digital platforms for industrial production
The purpose of this study is to identify and systematize data monetization mechanisms within digital platforms and assess their impact on the effectiveness of digital solutions for industrial manufacturing. This topic is relevant because data is becoming a strategic asset, shaping the competitive advantages of companies and new participants in industrial digital ecosystems. With growing data volumes, the spread of the Industrial Internet of Things, and the expansion of commercial circulation of industrial information, there is a need for a scientific understanding of models and tools for extracting economic value from information flows, as well as the performance indicators of digital platforms in industry.
Keywords: data monetization; digital platforms; industrial manufacturing; data economy; digital ecosystem; business model; data analytics; information flow management; digital transformation; digital platform efficiency; Industrial Internet of Things.
D. S. Shikhalieva (MIREA – Russian Technological University, Moscow); S. V. Bryukhovetskaya, I. V. Okhrimenko, O. V. Ryabova, S. A. Sergeev, A. A. Mkhitaryan (Financial University under the Government of the Russian Federation, Moscow); R. T. Dulambayeva (Academy of Public Administration under the President of the Republic of Kazakhstan, Astana)
Methodology of organization data management based on integration of artificial intelligence and big data technologies
The work is devoted to comprehensive research of methodological approaches to organization data management based on synergetic integration of artificial intelligence and big data technologies in the context of data economy formation. Classical data management theories are examined, including Data Governance concept according to DAMA-DMBOK methodology, Data Management principles, approaches to ensuring quality and security of information assets in conditions of artificial intelligence algorithms application. The evolution of scientific approaches to data management from traditional database management systems to modern big data processing platforms with intelligent analysis elements is analyzed. Key components of integrative data management methodology are identified, including technological infrastructure for processing large volumes of unstructured information, organizational and managerial mechanisms for data cataloging and lineage, machine learning algorithms for predictive analytics and information quality assurance, as well as metadata management systems using artificial intelligence for automating categorization and data enrichment processes. A conceptual methodology for integrating artificial intelligence technologies into data management lifecycle is developed, demonstrating the relationship between collection, processing, storage, analysis and use of information processes with application of intelligent analysis algorithms at each stage.
Keywords: data management; artificial intelligence; big data; Data Governance; DAMA-DMBOK methodology; machine learning; predictive analytics; data economy; technology integration; digital transformation; data quality; information assets.
I. A. Volkova, T. A. Galynchik, S. V. Danilova (Nizhnevartovsk State University, Nizhnevartovsk)
The labor market in managing population reproduction and aging (based on materials from the Urals Federal District)
The Urals Federal District lacks a unified mechanism for developing and regulating the labor market within the framework of demographic policy, but the development of this market can have a significant impact on demographic processes, both natural and mechanical. Therefore, studying individual labor market indicators that influence demographic processes in the Urals Federal District is a pressing issue.
Keywords: unemployed; demography; income; population; labor force; labor market.
P. V. Konyukhovsky, O. V. Kosteychuk, A. V. Sarzhe (Herzen University, Saint Petersburg)
Conceptual approaches to incorporating regional socioeconomic, scientific, and technological development analysis into schoolchildren's technology education
This article examines methods and approaches to improving the quality of labor (technology) instruction in educational institutions in a modern society largely determined by the consequences of global digital transformation. It argues that a necessary condition for successfully addressing these challenges is their systematic integration with regional socioeconomic, scientific, and technological development objectives, regional growth models, and national regional policy. The findings can be applied in the implementation of the regional component of the «Labor (Technology)» curriculum in comprehensive schools.
Keywords: labor (technology); education; regional economy; regional development strategy; regional development model.
Z. M. Kazova, E. V. Trubacheev (Russian State University of Social Technologies, Moscow)
The concept of inclusive mentoring in the organization of work activities of industrial enterprise personnel
The article discusses the concept of inclusive mentoring as a key tool for the effective integration of people with disabilities into the workforce at industrial enterprises. The authors identify systemic barriers that hinder employment, and also propose a structural and functional model for the implementation of inclusive mentoring, including regulatory, personnel and organizational support, details the step-by-step adaptation process and a comprehensive performance assessment system. It is concluded that the implementation of the proposed model makes it possible to move from the formal fulfillment of quotas to the creation of a sustainable inclusive environment that benefits both the company and employees with disabilities.
Keywords: persons with disabilities; employment of persons with disabilities; inclusive mentoring; industrial enterprises; structural and functional model of inclusive mentoring implementation.
L. A. Ezhova (Financial University under the Government of the Russian Federation, Moscow)
A mathematical model for assessing an organization's cyber resilience based on digital risk analysis
The purpose of this study is to develop a mathematical model for quantitatively assessing an organization's cyber resilience based on an analysis of digital risks and the probabilistic characteristics of incidents. The relevance of this topic is driven by the growing number of cyber threats and the increasing dependence of corporate processes on digital infrastructures, which necessitates a shift from reactive information security measures to a systemic assessment of resilience. The proposed model formalizes the relationship between the frequency and severity of cyber incidents, the mean time to restore critical services, and the economic losses resulting from failures. An integrated cyber resilience index is introduced, based on weighted coefficients of incident probability, recovery time, and damage, enabling a comparative analysis of organizations with different levels of digital maturity. The practical significance of the work lies in the potential application of the model for internal audit, IT risk monitoring, and the development of cyber resilience enhancement strategies. This developed tool can be used in the construction of corporate dashboards, automated information security management systems, and within the framework of state policy to ensure digital sovereignty.
Keywords: cyber resilience; mathematical model; resilience index; probability theory; information security; risk management; digital transformation.
S. A. Izmailova, V. O. Kozhina, I. V. Tolmacheva, A. A. Tolmachev (Moscow International University, Moscow)
Food security of countries in the aspect of achieving the goals of sustainable development and the index of resilience to shocks
This article examines a pressing issue related to achieving the necessary level of food security for countries to eliminate hunger. It also presents analytical data, which is used to formulate conclusions regarding the level of food security in Russia, the United States, and China. Finally, the authors propose a methodology for calculating a shock resilience index.
Keywords: hunger; food security; country; sustainable development; shock resilience index.
B. O. Gomboev, M. A. Motoshkina, V. S. Batomunkuev, A. S. Badmaeva (BIP SB RAS, Ulan-Ude); S. D. Shirapova (Buryat State University named after Dorzhi Banzarov, Ulan-Ude)
Economic and environmental assessment of the municipal solid waste management system in the mining region of Asian Russia (using the Republic of Tyva as a case study)
This paper provides a comprehensive assessment of the municipal solid waste (MSW) management system in the Republic of Tyva. Key issues are identified: environmentally hazardous disposal, a high proportion of unauthorized landfills, and a lack of recycling. Optimization strategies are proposed, based on the introduction of waste sorting, the development of recycling clusters, and the implementation of a regional territorial plan.
Keywords: municipal solid waste; landfill; recycling; environmental monitoring; closed-loop economy; Republic of Tyva; mining and industrial region.
E. M. Baichorova (Umar Aliev Karachai-Cherkess State University, Karachayevsk)
Modeling the dispersion of industrial pollutants in the atmospheric surface layer and their impact on the biodiversity of forest areas
The study aims to quantitatively assess the impact of industrial emissions on the biodiversity of adjacent forest ecosystems and to establish a causal link between emission source parameters, atmospheric transport, and observed biological effects at the local scale. Within an area of 500 km² around a metallurgical complex and a thermal power plant, a hypothesis was formulated of a dose-dependent decline in species richness and structural complexity of plant communities along the gradient of deposition of heavy metals and nitrogen-containing compounds, driven by prevailing winds and topography. The methodological framework includes a hybrid plume-in-grid atmospheric dispersion model that combines an exact Lagrangian description of plume rise and initial evolution with subsequent Eulerian computation of advection–diffusion, chemical transformations, and dry/wet deposition using ECMWF meteorological fields and emission inventory characteristics of sources. The integration of modeling, bioindication, and geobotany provides a robust basis for emission standard-setting, environmental impact assessment, and remediation prioritization, and also highlights the need to expand monitoring to faunal components and organic pollutants.
Keywords: atmospheric dispersion; heavy metals; forest biodiversity; bioindication; hybrid plume-in-grid model.
Ya. O. Zubov, S. A. Sergeev (Financial University under the Government of the Russian Federation, Moscow)
Visual ecosystem of digital marketplaces
This article examines the phenomenon of the visual ecosystem of digital marketplaces as a special type of communication environment, emerging at the intersection of marketing, interface design, and user analytics. The study aims to identify patterns in the formation of visual integrity and semantic continuity on digital platforms, where every element from icons to interface architecture becomes a carrier of branding code and part of a unified visual-semiotic structure. The authors analyzes how visual solutions are transformed into tools for retaining attention, stimulating emotional responses, and building loyalty, as well as how the visual ecosystem influences user economic behavior.
Keywords: visual ecosystem; marketplace; digital design; interface; UX aesthetics; brand identity; visual semiotics; user experience; digital environment; ecosystem marketing.
E. E. Grigoryeva, A. V. Grigorev, A. I. Egorova (North-Eastern Federal University, Yakutsk)
A neural network approach to forecasting diamond mining company stock prices
This study aims to identify modern methods for modeling economic processes in the diamond market that can account for volatility factors. This article examines the feasibility of using a neural network approach to forecasting diamond mining company stock prices. A comparative analysis of several methods and models for forecasting mining company stock prices, including an accuracy assessment, is provided. Using a neural network, a CNN model was built and trained on test data for ALROSA (PJSC) stock prices for the period June 1, 2020–May 6, 2024. The predictions obtained by the single-layer CNN model generally replicate the sign-oriented nature of the company's stock price trends. The test data set used covers a period of increased volatility in the diamond market, making neural network forecast errors of up to 40 % entirely predictable. To improve the accuracy of forecast values, the authors propose modifying the CNN model with input parameters characterizing the upward and downward trends of market conditions in the studied market. Neural network models expand the toolset for time series forecasting and automate numerical calculations. When a deep approach to knowledge is required during periods of uncertainty, expert opinions are proposed to be taken into account through a certain action coefficient. The authors believe that using the recommended input parameters, it is possible to construct various decompositions of the model architecture depending on the studied market process in the diamond value chain. The article identifies fundamental trends in the diamond market that can shape various scenarios in the long term. A detailed analysis of the patterns of ALROSA share price behavior in response to significant market events is conducted. The given example of the dynamics of export-import transactions of Indian diamonds demonstrates a significant correlation with the behavior of the company's share price.
Keywords: diamond mining company; diamond market; market conditions; neural network approach; correlation; action coefficient; uncertainty; influencing factors.
O. V. Kitova, L. P. Dyakonova, A. F. Konstantinov (Plekhanov Russian University of Economics, Moscow)
Forecasting credit risks of retail lending using the Horizon analytical system
The authors of this article are developing the Horizon information and analytical system, which enables forecasting socioeconomic indicators based on hybrid regression models. At the same time, a wide range of problems in economics, manufacturing, and business can be solved using AI classification models. The article describes the information and logical structure of the Horizon classification block. The results of a borrower default calculation are provided as an example of how this block of models can be used.
Keywords: financial risks; loan default forecasting; credit scoring; Horizon forecasting system.
N. A. Patutina, V. S. Kudryashov, S. P. Ivanova, S. A. Dzhendubaeva (Financial University under the Government of the Russian Federation, Moscow)
Analysis of the main approaches to assessing the marketing potential of creative clusters
The article is devoted to the study of the marketing potential of creative clusters as a key element of regional and urban development strategies. The authors analyze five methodological approaches to assessing potential: resource-functional (focus on tangible and intangible assets), image-communication (the role of digital media and branding), value-oriented (socio-cultural influence), institutional (external regulatory conditions) and integral (integrated model). Using the example of creative clusters, the strengths and limitations of each method are demonstrated. Special attention is paid to the need to synthesize approaches to overcome the fragmentation of assessments. An integral approach combining quantitative and qualitative metrics is presented as a tool for predicting cluster stability in a dynamic environment. The results of the study emphasize that the successful development of creative clusters requires a balance between internal resources, image management, adaptation to institutional changes and the translation of socio-cultural values. The work is aimed at researchers, managers and urbanists interested in turning creative spaces into points of economic growth and cultural identity.
Keywords: creative clusters; marketing potential; integrated approach; sustainable development; resource-functional analysis; image strategies; institutional factors; socio-cultural values.