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RAR RUS 7-34 Setiawati Pertiwi Priyanka Setyanto Padmanabha Adyaksa Muljono Wiryanta wiryantamuljono@gmail.com Setiyawati Sri AI-based technological transformation as a driver for development of oil refining market: case study of Indonesia This study investigates the multifaceted relationship between AI-driven technological transformation and the demand for downstream petroleum products in achieving Indonesia’s long- term economic growth goals, aligning with the “Golden Indonesia 2045” vision. Employing a mixed- methods approach, the research quantitatively assesses the immediate impact of AI on downstream petroleum operational efficiency (the first hypothesis) and its subsequent influence on critical macroeconomic indicators like GDP growth and the oil and gas trade balance (the second hypothesis). Concurrently, it qualitatively examines the strategic alignment of national AI policies, such as the National AI Strategy from 2020 to 2045 (Strategi Nasional Kecerdasan Artifisial, Stranas KA) and the “Making Indonesia 4.0” roadmap, with downstream energy development plans (the third hypothesis), while identifying associated implementation challenges. Findings reveal a significant positive correlation between AI adoption and improved operational efficiency within the downstream sector (supporting the first hypothesis). This is substantiated by evidence of sophisticated AI applications, including predictive maintenance (PdM) powered by advanced computational methods, which ensures continuous operation and extends the life of critical hydrocarbon assets. Furthermore, AI-integrated fuel blending systems demonstrate high precision, achieving a coefficient of determination (R2) of 0.99 during validation, which showcases robust real-time optimization capability that surpasses traditional modeling and reduces waste. However, the analysis of macroeconomic leverage provides only partial support for the second hypothesis. While AI-influenced efficiency – by maximizing domestic output and optimizing costs – shows a statistically significant, albeit moderate, positive impact on reducing the oil and gas trade deficit and boosting GDP growth, this effect is severely limited by persistent structural issues. Specifically, petroleum imports have a large and negative impact on Indonesia’s economic growth. The operational savings are currently dwarfed by the volume of necessary imports and the enormous fiscal burden imposed by incomplete fuel subsidy reforms, which peaked at 2.8% of GDP in 2022. The oil and gas trade balance persists in a deficit, recording –1.55 billion USD in May 2025 and –1.58 billion USD in July 2025, even amidst an overall national trade surplus. The study confirms a strong top-down strategic alignment between national AI and energy sector policies. Nevertheless, significant implementation hurdles highlight the necessity for targeted policy intervention (supporting the third hypothesis). These pervasive barriers include chronic infrastructure gaps, weak data governance frameworks, severe digital skills shortages requiring systematic improvement from foundational education, high initial investment costs and profound organizational inertia within large enterprises, leading to a “pilot trap”, where successful small-scale projects fail to scale up due to cultural and systems integration difficulties. Ultimately, these challenges temper the transformative potential of AI, shifting its current role primarily towards improving operational efficiency within the legacy system. For AI to become a driver of fundamental structural change – the necessary process of reallocating labor and resources toward higher-productivity modern industries – policy interventions must link AI investment to comprehensive energy subsidy reform and the acceleration of the new and renewable energy sector. This research bridges a critical gap in the literature by offering an integrated analysis of technology adoption in a resource-dependent emerging economy, providing evidence-based recommendations for policymakers and industry leaders to effectively leverage AI for sustainable and structural economic growth. 10.18721/JE.18601 658.5 artificial intelligence digital transformation oil refining market operational efficiency economic development Indonesia machine learning technological transformation https://economy.spbstu.ru/article/2025.116.1/ 01_mulono_setiyavati_setiyavati_setyanto.pdf

RAR RUS 35-53 Korokoshko Yulia Social drivers of business digital transformation of enterprises In modern conditions of digital transformation, enterprises should give priority to the study of social aspects of consumer behavior regarding their products and dynamically changing consumer values caused by the inevitable digitalization of society. Companies need to respond with utmost agility to the various challenges of the digital economy, since the subsequent stability of their operations depends on the speed of their response and adaptation to digitalization. In this regard, to operate successfully in today’s market, companies should identify and take into account the key drivers of business digital transformation, among which social drivers hold a special place today. However, such information has not yet been taken into account at the level of individual market entities, and enterprises remain unprepared for the various consequences of digitalization, which collectively creates preconditions for potential threats and the formation of weaknesses in initially successful companies. The aim of the study is to identify the features of consumer behavior and the values of modern consumers as the main social drivers caused by the digitalization of all sectors of the economy. The research is based on the application of empirical research methods, a systematic approach, comparative and expert analysis. The results of the study are to identify the current features of consumer behavior and consumer values, which are the most important social drivers of business digital transformation of enterprises. The novelty and practical value of the obtained results lie in the fact that the data obtained reflect not only specific regional characteristics of consumer behavior in the context of digitalization, but also systemic all-Russian trends in consumer choice, which make it possible to identify the most relevant areas for the digital transformation of modern companies’ businesses. In addition, the article introduces and explores the concept of “social drivers of digital transformation”, which has been poorly studied to date. It was found that in the context of the digitalization of the economy, a number of traditional emphases have shifted in consumer behavior regarding decision making, as well as the transformation of their values towards various digital trends. The conclusions obtained are prerequisites for the need for enterprises to take into account the social drivers of business digital transformation. 10.18721/JE.18602 65.011.56 digitalization digital economy digital transformation drivers of business digital transformation social drivers of digital transformation consumer purchasing behavior enterprise https://economy.spbstu.ru/article/2025.116.2/ 02_korokoshko.pdf

RAR RUS 54-70 Kozlova Evgeniya Evolution and classification of digital corporate platforms in the context of technological transformation Digital platforms have fundamentally transformed market structures, gradually permeating all sectors of the economy, including education and corporate management. Among the many digital solutions, digital corporate learning platforms have been selected as the relevant area of research. The article presents the results of a theoretical and methodological study of digital corporate learning platforms as a key instrument in the digital transformation of human capital management. The aim of the study is to systematize approaches to defining the essence of digital corporate learning platforms, to identify the stages of their evolution, to develop a classification of existing solutions and to determine levels of functional maturity. The methodological framework is based on systemic, typological and evolutionary-historical approaches, complemented by an interdisciplinary analysis integrating elements of knowledge management, educational technologies, HR analytics and strategic management. The study includes an analysis of Russian and international research, as well as practical cases from leading corporate platforms. It has been established that the development of digital learning systems has passed through three major stages: from LMS, performing administrative training functions, to LXP, focused on personalization and engagement, and finally to modern hybrid corporate ecosystems integrated into strategic competence management processes. Key maturity criteria for digital corporate learning platforms are defined as functional completeness, depth of integration into corporate processes, level of analytical sophistication, user coverage and the strategic role in human capital management. To quantify maturity, a set of metrics is proposed, including the share of individualized learning paths, user engagement levels, the economic effect of learning (ROI Learning) and the degree of integration of analytical tools. A classification of digital corporate learning platforms is developed based on six criteria: purpose orientation, learning objectives, target audience, applied technologies, architectural solution and source of development. The findings allow digital corporate learning platforms to be viewed as strategic infrastructure for human capital development, ensuring personalized learning, productivity growth and the formation of digital corporate culture. The scientific novelty of the research lies in refining the conceptual framework and proposing a maturity typology of digital corporate learning platforms, forming a basis for future empirical studies, effectiveness evaluation methods and strategies for corporate learning ecosystem development. 10.18721/JE.18603 005.336.5:378.1:004 corporate training digital corporate educational platforms digital educational platforms platform maturity assessment evolution of educational platforms https://economy.spbstu.ru/article/2025.116.3/ 03_kozlova.pdf

RAR RUS 71-83 Dinmukhametova Aliya Assessing the effectiveness of digital transformation of regional economic systems In the modern economic paradigm, digital transformation has established itself as a key driver of socio-economic development in territories. However, its outcomes demonstrate significant variability, driven by disparities in the availability of financial and technological resources, differences in the institutional environment, and the quality of human capital. This heterogeneity creates risks of increasing regional development disparities, necessitating the development of reliable tools for the comparative assessment of their effectiveness in the context of digital transformation. The study aims to develop and practically test a comprehensive methodological approach for the comparative assessment of the effectiveness of regional systems within the framework of digital transformation. The empirical basis for testing the methodology is data from the regions of the Volga Federal District (VFD). The methodology is based on a Data Envelopment Analysis (DEA) model, adapted to the specifics of regional systems. This allowed for a quantitative assessment of the relative efficiency of each region’s use of its digital potential. Another stage of the research involved the classification of regional systems using cluster analysis. Calculations based on data from 2016 and 2023 recorded positive dynamics, manifested in an increase in the average level of digital transformation efficiency in the VFD regions. Cluster analysis revealed a stable stratification, distributing all regions of the district into three distinct groups corresponding to high, medium, and low levels of digital transformation development. The developed methodological approach is of high practical value, as its results can be used by regional authorities to formulate targeted strategic decisions in the field of digital transformation, tailored to specific local conditions. A promising direction for subsequent scientific inquiry is the expansion of the analysis timeframe. This would allow for not only tracking long-term dynamics, but also analyzing the trajectories of regions transitioning between the identified clusters. 10.18721/JE.18604 332.1 technological leadership digital transformation Volga Federal District efficiency regions https://economy.spbstu.ru/article/2025.116.4/ 04_dinmuhametova.pdf

RAR RUS 84-107 Barybina Anna Digital divides: research review and challenges Digital divides, representing systemic inequality in access to, use of and the impact of digital technologies, have established themselves as one of the most significant and multifaceted challenges of modern globalized society. The relevance of this topic has sharply increased against the backdrop of accelerating digital transformation processes, the COVID-19 pandemic, which shifted many aspects of life into an online format, and a growing dependence on digital solutions, which together not only reveal but also exacerbate existing socio-economic inequality. The aim of this article is to conduct a comprehensive and multi-level analysis of the phenomenon of digital divides, combining theoretical economic and sociological approaches with relevant empirical data to identify key determinants of inequality and develop comprehensive pathways for its mitigation. The methodological framework of the research includes a systematic analysis of scientific literature, quantitative analysis of international and national statistics (including data from the UN, OECD, World Bank) and a comparative method, allowing for the comparison of digital inequality manifestations in different countries and regions. Such a comprehensive approach enables the examination of both macro-level (state policy, infrastructure development) and micro-level aspects of the problem (individual skills, socio-economic status of households). Particular attention in the analysis is paid to critically important factors such as physical access to broadband internet and devices, the level of digital and media literacy among the population, age, gender and socio-economic barriers, as well as the effectiveness of government regulatory measures. The results of the study clearly demonstrate that digital divides act not merely as a consequence but as a powerful catalyst for further social stratification, significantly limiting opportunities for marginalized population groups in education, employment, access to healthcare and full-fledged civic engagement. The scientific novelty and contribution of the work lie in the systematization and synthesis of various economic theories studying digital inequality, as well as in the development of specific practical recommendations for its reduction. The main conclusions emphasize the imperative need for coordinated investment in digital infrastructure, the implementation of large-scale educational programs aimed at all age groups and the strengthening of international cooperation to ensure inclusive and sustainable development. The scope for practical application of the results includes the formation of targeted state policy, the development of corporate social strategies and the creation of programs for international organizations aimed at reducing digital inequality. The study’s limitations are associated with the exceptional dynamism of technological development and the significant diversity of regional contexts, which necessitates further research to constantly adapt the proposed measures to rapidly changing conditions. Promising directions for future research include an in-depth study of the interaction and mutual influence of various levels of digital inequality (access, use, outcomes), as well as the development of more sophisticated and innovative methods for its quantitative and qualitative measurement. 10.18721/JE.18605 330.3 digital gaps digital inequality institutional environment socio-cultural factors digital economy digitalization regions innovative development innovation https://economy.spbstu.ru/article/2025.116.5/ 05_baribina.pdf

RAR RUS 108-126 56436586400 0000-0003-3042-7550 Penza State University Gamidullaeva Leyla Vasin Sergey Institutional mechanisms for the implementation of scientific and technological development in the regions of Russia The article is devoted to the analysis of institutional mechanisms for implementing scientific and technological policy in the constituent entities of the Russian Federation, identifying systemic constraints and substantiating possible trajectories for overcoming them based on existing national projects and programs. The authors used an institutional approach to identify limitations in supporting national projects in the regions, as well as a classification method for typologizing constituent entities of the Russian Federation by their level of institutional maturity. The analysis of national projects and the regulatory environment was carried out based on the content analysis of official documents (national project passports, methodological recommendations, the “New National Projects for the Period 2025–2030” Standard, etc.). A typology of regions by the degree of institutional readiness is presented, key risks and problems are identified. The analysis showed that the effectiveness of the implementation of national projects in the regions is largely determined not only by financial or human resources, but also by the level of institutional organization and the ability of the constituent entities to adapt federal initiatives to their own specifics. Insufficient institutionalization of coordination mechanisms, weak connectivity between participants in the innovation system and a lack of knowledge transfer infrastructure limit the scalability of project activities. The necessity of transition from a linear program-target model to an adaptive model of institutional support is substantiated. The authors discuss the advisability of forming new organizational links capable of acting as connecting mechanisms between scientific, industrial and managerial subsystems, performing functions of intermediary coordination and support of technology transfer processes within the framework of national projects. The concept of a regional consortium as a coordination platform ensuring interaction between government, business, science and society is introduced. The architecture of a regional consortium to support scientific and technological development is proposed. The advisability of developing a standard for regional support of national projects as a framework instrument for adapting the federal agenda to the conditions of specific regions is substantiated. Based on the analysis, the authors propose recommendations for improving regional scientific and technological policy in the context of national priorities and global trends. The proposed solutions are focused on reducing transaction costs, enhancing coordination, and ensuring the reproducibility of project practices in conditions of spatial asymmetry. 10.18721/JE.18606 332.12, 338.12 national projects institutional support regional policy project coordination technology brokers consortium technology transfer https://economy.spbstu.ru/article/2025.116.6/ 06_gamidullaevavasin.pdf

RAR RUS 127-141 57190260598 0000-0001-6888-1981 V.I. Vernadsky Crimean Federal University Kirilchuk Svetlana skir12@yandex.ru

Prospekt Vernadskogo 4 , Simferopol, Republic of Crimea, 295007

Nalivaychenko Ekaterina Innovative approach to assessing the multiplier effect of investments Research objective is to develop a methodological approach for assessing the multiplicative impact on the economic efficiency of investment processes, considering regional factors. Research methodology includes systems approach, neoclassical and evolutionary theories of investment, the concept of multipliers, methods of econometric modeling. These methods allow for a deeper understanding of the impact of innovations on the economic efficiency of investment processes at the macro and meso-levels and their interrelationships. This article examines the multiplicative impact of investments on economic efficiency in Russia, including in the Republic of Crimea in 2020–2024. A comparative analysis of the dynamics of investments in fixed assets and economic indicators of gross national income for Russia and gross regional product for the Republic of Crimea is carried out. The main focus is on calculating the multiplicative impact of investments. The results of the analysis show that investments in Crimea provide higher multiplicative return, which is associated with state support and infrastructure projects, while in Russia, investment efficiency is decreasing due to external shocks and institutional barriers, as well as significant challenges such as sanctions, inflation and geopolitical risks. The developed innovative approach to assessing the multiplicative impact of investments made it possible to identify regional imbalances in the investment processes efficiency. The use of VAR modeling for 2025–2027 confirmed the stability of forecast trends, despite external risks. To assess the multiplicative impact of investments in Russia and the Republic of Crimea, a combination of a VAR model with the Random Forest algorithm was used, in which the current values of these series depend on their past values, and regression analysis of panel data for 2020–2024. Implications for business and government involve using a variety of multiplication methods, including the presented one, which recommends taking into account geopolitical factors and inflationary risks in long-term planning. Specific recommendations include: for Russia: reducing bureaucratic barriers, stimulating private investment, diversifying the economy; for the region of Republic of Crimea: increasing investment with an emphasis on infrastructure and import-substitution projects. The results of the study show that optimizing investment policy, taking into account the identified patterns, can accelerate economic growth at both the federal and regional levels. The originality of the research and the author’s contribution: 1. Characteristics of modern methods for assessing multipliers. 2. An innovative model integrating national and regional approaches. The practical significance of the study lies in the potential application of its results to increase the validity of investment decisions at both the meso- and macroeconomic levels. The results of the work can be used by government bodies, corporations and investors to optimize development strategies and maximize the socio-economic impact of investments. 10.18721/JE.18607 330.341.1 investment activity innovative approach Russia Republic of Crimea multiplier gross national income gross regional product investments in fixed assets forecast efficiency https://economy.spbstu.ru/article/2025.116.7/ 07_kirilchuk_nalivaychenko.pdf

RAR RUS 142-158 Badykova Idelya idelia.badykova@gmail.com Differentiated governance of innovative development in Russian regions 10.18721/JE.18608 338 regional innovation systems regional differentiation typology innovation development management triple helix cluster analysis technological sovereignty regional policy https://economy.spbstu.ru/article/2025.116.8/ 08_badikova.pdf

RAR RUS 159-176 Chebotareva Galina Dvinayninov Artyom Сreation of local energy markets based on biogas technologies in Russian regions This work is the next authors’ publication devoted to the topic of scaling biogas technologies in the Russian energy market. The relevance of this study is determined by the need to address the problems of reliable energy supply to isolated and remote territories in Russian regions, combined with energy transition measures declared at the national level. The aim of the study is to develop a concept of local energy markets operating in these territories based on the use of biogas technologies. The methods used include a systematic approach to data collection and processing, comparison and generalization of initial information, as well as visualization of the results obtained. The study utilizes findings from previous research on assessing the economic feasibility of biogas plants in Russian practice, current regulatory legal acts governing domestic energy markets, and accumulated regional statistical data. The obtained research results showed that, under current conditions, the scaling of biogas technologies in Russian regions is realistic. It is possible due to the formation of a new category in the energy sector – local energy markets, that involve the construction and operation of biogas facilities by interested agricultural, fishery and forestry enterprises for their own energy supply and sustainable energy supply to isolated and remote territories. In particular, the architecture of such local markets is proposed, which includes a description of its specific elements and an algorithm of functioning. Based on the “traffic light” principle, a map of potential local energy markets in Russian regions was developed, taking into account a set of geographical, natural, climatic and economic criteria. Programs for state financial, economic and regulatory support for the national biogas sector were proposed, aimed at producers and owners of large biogas facilities, as well as indirectly aimed at stimulating local energy markets. All of the above substantiates the novelty and practical value of the results obtained. Directions of further research include the comprehensive efficiency assessment of using large biogas facilities when agricultural, fishery and forestry enterprises enter retail electricity markets to generate new sources of income; the feasibility study of modern biogas technologies and the creation of conditions for their reasonable use in conditions of low temperatures in specific Russian regions. 10.18721/JE.18609 332.12 alternative energy biogas technologies local energy market remote and isolated territories Russian region sustainable energy supply https://economy.spbstu.ru/article/2025.116.9/ 09_chebotareva_dvinyaninov.pdf

RAR RUS 177-203 Shchepetova Svetlana Critical problems of complex modeling of socio-economic systems for forecasting purposes As the organizational, economic, institutional, technical and other conditions of human life become more complex, and as a consequence of the increasing complexity of management objects and problems requiring solutions, the theory, methodology and tools of modeling (including mathematical) are developing. However, until now, in their development, insufficient attention has been paid to the issues of creating an integrated methodological basis for constructing a set of models that, taken together, allow achieving the effect of a “white (transparent) box” model of the studied cyber-socio-economic systems, understanding the interrelations of their structure, properties, processes, results and conditions of life, and investigating the long-term and indirect consequences of organizational and managerial decisions. The development of such a methodological basis, taking into account the cognitive and psychological characteristics of individuals, is the goal of the research being conducted. The stages of system modeling, systematizes the problems encountered during these stages, and reflects their impact on modeling results are presented in this article. It also proposes a methodological framework for constructing and evaluating a set of cyber-socio-economic system models. The results are based on general systems theory and epistemology, modeling methodology, and systems principles of thinking, organization, and management. The novelty of the proposals lies in the implementation of the principle of model integration based on a three-axis framework for the system description of the control object and in the systematization of critical modeling problems in the context of the steps of the basic methodology of systems research. This allows to give researchers to equip themselves with a methodological framework for the systemic description of controlled socio-economic systems through a set of models and to draw attention to critical issues that may negatively affect the adequacy, effectiveness, expediency, consistency and usefulness of the models of the set-complex. The implementation of the proposed approach to integrated modeling will improve the quality of substantiation of organizational and management decisions. The development of detailed methodological recommendations, taking into account the specifics of various socio-economic systems (depending on belonging to a certain level of the economy, on the types and scale of activities and other characteristics), should be a continuation of research in this direction. 10.18721/JE.18610 51-7, 001 controlled systems socio-economic systems cognitive-psychological characteristics of the researcher modeling systems modeling complex modeling adequacy of models of the system complex effectiveness of models of the system complex https://economy.spbstu.ru/article/2025.116.10/ 10_shchepetova.pdf

RAR RUS 204-229 Yatsenko Viktoriya Klanitsa Sofiya Adaptation of project maturity assessment methods for internal projects of an organization In the context of increased project activity, assessing the project maturity of organizations has become a critical aspect for ensuring their competitiveness and sustainability in the market. This article explores the relevance of assessing project maturity, with a focus on internal digital projects that often fall outside the scope of traditional assessment models. The authors analyze existing approaches, such as OPM3, P3M3 and CMMI, highlighting their limitations in application to internal initiatives, particularly in the context of digital transformation. Traditional models are typically focused on external projects, while internal projects require a more flexible and adaptive approach that takes into account the unique characteristics and goals of the organization. The article discusses modern models for assessing project maturity, such as the AI-Driven Maturity Framework, the Agile Maturity Model, IDEO Project Maturity Model and Digital Project Management Model, which combine technological innovations and anthropocentric approaches, but fail to account for organizational barriers during implementation in the context of misaligned digital infrastructure or corporate culture. Therefore, there is a need to develop new approaches that take into account the specific features of internal projects and their impact on the organization’s strategic goals. The article also includes a practical example of implementing a human resources management project at Company N, which illustrates the effectiveness of the proposed methodology for assessing project maturity. Internal projects, such as developing a feedback system for employees, require a deep understanding of organizational culture and interdepartmental collaboration, highlighting the importance of adapting internal project assessment approaches. In conclusion, the authors provide recommendations for implementing project maturity assessment methods, enabling organizations to optimize resources, enhance project management efficiency and minimize risks. This work will be useful for researchers and practitioners seeking to improve project management in the context of digital transformation and ensure the long-term success of their organizations. Implementing these approaches can significantly enhance the adaptability and innovation capacity of companies, which is a key factor in modern business. 10.18721/JE.18611 338.2 digital maturity project maturity internal initiatives project management innovative approaches https://economy.spbstu.ru/article/2025.116.11/ 11_yatsenko_klanitsa.pdf

RAR RUS 230-246 Alkin Kirill Blagoi Nikita Dmitriev Nikolay Modeling the digital maturity of national economy and verification of the macroeconomic effects of digital transformation The study presents an assessment of the digital maturity of national economy grounded in fuzzy set theory and objective feature weighting. From a harmonized panel of information and communication technology (ICT) indicators – after series normalization with 1st–99th percentile winsorization, monotonicity control and unit harmonization – a composite maturity index is constructed, followed by stratification of countries by maturity levels. The baseline set includes the prevalence of fixed broadband access for households and businesses, the number of active mobile subscriptions per capita, the share of Internet users, the density of secure Internet servers, the share of ICT goods in total merchandise imports and the share of ICT services in services exports. Where available, positions for software and telecommunications products are added with separate accounting logic for goods and service flows. Normalized indicators are transformed into linguistic variables; triangular and trapezoidal membership functions are specified for the “low”, “medium” and “high” gradations with openly parameterized vertices and plateaus suitable for scenario adjustments. The pipeline then performs fuzzification, weighted aggregation and defuzzification via the centroid method, with robustness checks against alternative membership shapes and aggregation schemes. Indicator weights are estimated using the entropy method and principal component analysis, reconciled and applied at aggregation to mitigate multicollinearity; principal component analysis loadings and component contributions are retained for interpretation. The resulting index supports ranking of economies, computation of probabilistic membership shares across maturity tiers, mapping, and clustering. External validation is carried out against the Human Development Index using correlation- regression analysis; robustness is confirmed by bootstrap estimates and heteroskedasticity-robust standard errors. The algorithm is implemented in Python with openly specified normalization settings and membership functions, which ensures reproducibility and scalability. The resulting estimates substantiate the prioritization of infrastructure, cybersecurity and digital-skills development for strategic planning, progress monitoring and international benchmarking. 10.18721/JE.18612 338.24:330.43 digital transformation digital maturity macroeconomic effects digital economy fuzzy sets entropy method principal component analysis https://economy.spbstu.ru/article/2025.116.12/ 12_blagoy_dmitriev_alkin.pdf