In the modern global economy, the government bond market performs a critically important function, acting simultaneously as a tool for financing budget expenditures, a mechanism for implementing monetary policy and an indicator of macroeconomic stability. However, in recent years, this market has faced unprecedented challenges due to the increasing frequency of external shocks of various nature. In this context, external shocks are understood as exogenous events that have a significant impact on the economy and financial markets: geopolitical conflicts (for example, sanction pressure on Russia from 2022), global pandemics (COVID-19), drastic changes in the monetary policy of leading central banks (the Fed tightening cycle in 2022–2023), as well as structural crises in the global financial system. These factors lead to increased volatility in financial markets, rising yields and, as a result, an increase in the cost of servicing government debt. The relevance of government bond market research in the context of external shocks is due to the increasing instability of the global economy caused by geopolitical conflicts, pandemics, changes in the monetary policy of leading central banks and climate crises. These factors have a significant impact on the profitability, liquidity and reliability of debt instruments, which is especially important for investors, regulators and issuers. Studying the reaction of the government bond market to external shocks makes it possible to develop effective risk management strategies, predict possible crises, and form a sustainable debt policy. Under conditions of sanction pressure and high volatility, the analysis for this topic becomes crucial for ensuring financial stability both at the national and international levels.

This paper examines the mechanisms of mutually beneficial partnership between a university and a technology startup, including fair terms for transferring to the startup intellectual property rights (IPR) created within the university. The current situation in Russia is analyzed using the terminology of new institutional economics. As a tool of institution-al modeling, the study employs a game-theoretic approach in which the interaction be-tween the university and the technology startup is represented as a finite dynamic non-zero-sum two-player game. The model takes into account such factors as the university’s participation in the startup’s authorized capital and the startup’s potential interest in «bypassing» the university’s intellectual property if the transaction price is overstated. It is proposed that the equitable value be assessed on the basis of market value, by analogy with the well-known and widely used collateral value assessment methodology, followed by an adjustment reflecting the specific terms of the transaction between the particular participants, namely the university and the startup. The developed approach to assessing the equitable value of intellectual property rights (IPR) can be interpreted as an institutional complement, that is, an instrument that enhances the effectiveness of the existing rules and norms governing interaction between universities and technology startups.

Amid escalating geo-economic fragmentation and diverging regulatory regimes, block-chain technology occupies a dual position. On one hand, it offers a technically neutral foundation for global finance. On the other, its implementation and regulation create new boundaries, contributing to the emergence of isolated fintech clusters. The aim of this study is to identify the dual role of blockchain as both a driver of fragmentation and a potential enabler of global financial integration. The methodological framework comprises a comparative analysis for regulatory frameworks (EU, US, China, BRICS), a tech-no-functional analysis for key blockchain projects (Ethereum, Solana, BSN, Hyperledger), and scenario-based forecasting. The results reveal that regulatory divergences create “soft” barriers, giving rise to distinct clusters with varying functional efficiency: decentralized systems demonstrate high throughput and low costs within clusters, yet cross-cluster interaction faces regulatory and technological constraints. Based on the findings, three future scenarios are proposed: dominance of a single model, consolidation of separate blocs, and the emergence of dominant technological bridges. The applicability of the results lies in informing digital finance regulation strategies and international cooperation in fintech. The limitations include the dynamic nature of regulatory changes and the absence of long-term empirical data on cluster performance. Future research directions include quantitative assessment of the economic effects of cross-cluster interaction.

This study investigated the relationship between entrepreneurial innovation and creativity on the performance of Small and Medium Enterprises (SMEs) in Nigeria. Specifically, the study aimed to evaluate the innovative ability in business sustainability, the influence of creative thinking on business expansion in SMEs. Descriptive survey research design was used. The population comprised SMEs of Lagos State, Nigeria. Using purposive random sampling and the Raosoft Sample Size Formula, a sample size of 372 respondents was obtained. Questionnaires were used to gather primary data and regression analysis used for data analysis. The results from the first hypothesis showed that innovative ability had a significant effect on the sustainability of businesses among SMEs. The coefficient of determination (R² = 0.275) was found that 27.5% of the variation in business sustainability could be explained by innovative ability and a moderate-to-strong relationship was found from the standardized coefficient (Beta = 0.525). The results of the second hypothesis indicate that creative thinking has a significant effect on business expansion of SMEs. The coefficient of determination (R² = 0.264) showed that the variance of SME expansion could be explained by creative thinking by 26.4%. The standardized coefficient (Beta = 0.514) showed that there was a moderate-to-strong positive relationship between creative thinking and SME expansion. The study found that innovation and creativity are significant factors influencing success of the SMEs in Lagos State. It suggested ongoing trainings and workshops in order to enhance the innovative and creative skills for sustainable growth and development.

Global economic development requires new approaches to regional management in the field of tourism. In the context of digitalization, smart tourism stands out, which relies on the implementation and grouping of advanced technologies such as artificial intelligence, the Internet of Things, digital platforms, big data, and virtual and augmented reality. This concept has gone beyond simple service automation, becoming a central element of regional innovation systems that significantly impact the development of territories and stimulate economic growth. The article explores how smart tourism technologies are being implemented in the tourism ecosystems of Russian regions, and how the level of digitalization in these regions is affecting this process. The study highlights the key components of this trend, including infrastructure, technology, social aspects, and institutional frameworks, and identifies key areas for strengthening smart tourism in the region. The proposed Smart Tourism Readiness Index (STRI) has been considered, which is designed to assess the region's readiness for implementing the concept of smart tourism. The comprehensive approach to creating tourist ecosystems focuses on both digital infra-structure and the development of attractive tourist areas.

The article discusses the key areas of ensuring the energy security of the Kaliningrad region, improving the energy efficiency of the economic complex of the region as an integral part of the entire energy security system of Russia. The importance of ensuring energy security for the socio-economic development of the region was emphasized. Based on the comprehensive analysis, the approaches to maintaining the stability of the regional energy system are proposed, taking into account the typology of threats to energy security and with an emphasis on foreign policy threats that can cause significant damage to energy facilities. The rhythmic functioning of the Kaliningrad Region's energy system and its dependence on electricity generation and consumption are demonstrated. The structural characteristics of the Kaliningrad Region's energy complex are given. The technological solutions implemented to minimize threats are being investigated: the construction of own generation, the introduction of automatic frequency control systems; special attention is paid to the issues of physical security of fuel and energy complex facilities. The analysis for the main factors influencing the level of energy consumption in the region, including the specifics of generation, transmission and use of resources, is carried out. A number of problem areas have been identified related to increased electricity losses in the grid, suboptimal use of production facilities and energy-saving potential in various sectors of the economy. Based on the analysis of open sources, the conclusion is drawn on the achieved level of autonomy of the regional energy sector and the remaining strategic challenges.

The article examines the processes of digital transformation of the agro-industrial complex in the regional context. The relevance of the work is due to the need to overcome the interregional digital gap in agriculture, as well as the challenges of achieving technological sovereignty of the agricultural sector in the face of external sanction pressure. The purpose of the work is a comprehensive assessment of the level of digitalization of agriculture in the subjects of the Russian Federation, identification of leaders and outsiders, analysis for factors hindering the introduction of digital technologies. The methodological base includes the author's methodology of the integrated index of the digital maturity of the agro-industrial complex based on three groups of indicators (infrastructure security, implementation of specific digital solutions, human resources and innovation potential). As a result of the study, three groups of regions were identified according to the level of digital maturity of the agro-industrial complex, key barriers (infrastructural, personnel, financial) were identified and directions of state policy to stimulate digitalization were proposed. It has been established that almost half of the subjects of the Russian Federation demonstrate extremely low digital activity, which threatens food security and increases territorial inequality. The paper also conducted a comparative analysis with the agricultural regions of India and Brazil, which demonstrated a similar problem of regional differentiation, but with different tools to overcome it. The scientific novelty lies in the development of the author's methodology for the integrated assessment of digitalization of the regional agro-industrial complex. The practical significance of the results lies in the possibility of their use in adjusting the development strategies of the agro-industrial complex of the subjects of the Russian Federation.

The urgency of the problem of the early integration of one of the new Russian regions, the Lugansk People's Republic, into the national economic space is due to the need to develop the economic level and quality of life for the citizens of the LPR to the all-Russian level in the shortest possible time. Federal Constitutional Law №. 6-FKZ dated 04.10.2022 and Decree of the Government of the Russian Federation dated 22.12.2023. №. 2255 provides for the solution of this priority economic task by 2030 with the development of a program for the socio-economic development of the region, approaches and mechanisms to ensure its implementation. The process of integrating the new region is based on previously developed general trends and scientific approaches, but is complicated by the continuation of hostilities in the surrounding territories. The purpose of the study is to develop and substantiate theoretically a strategy for integrating the region into the economic space of the Russian Federation under the current conditions. The methodological basis for the study includes: a systematic analysis and synthesis of accumulated scientific knowledge and experience; studying the methodology of strategic planning, methods and approaches of the integration process. As a result of the study, the main strategic directions, tools and ways of integrating the region and its socio-economic development in the coming years have been developed.

In the context of the current restructuring of global supply chains, the transformation of the Eurasian transport space is acquiring strategic significance for the global geoeconomic struggle. However, traditional economic models focused on assessing functioning infrastructure fail to explain the redistribution of geoeconomic influence occurring amid the rapid digitalization of international logistics. The purpose of this article is to identify patterns and specific features of the spatial and technological evolution of the logistics component of the Silk Road during the transition to a digital ecosystem. The methodological framework is based on the world-system approach and the concept of "technology – space – power". The study employs the methods of retrospective and comparative analysis, as well as the synthesis of empirical data. Three historical phases in the development of transcontinental transport routes in the Eurasian space are identified and characterized. It is demonstrated that in the context of digitalization, control over intelligent algorithms and data flows is becoming a more significant factor in determining dominance than political and economic power. It is argued that the implementation of end-to-end information technologies (smart hubs, distributed ledgers) in the international transportation management system will help bridge the gap between entities and ensure seamless transcontinental transport routes. The article substantiates the conclusion that the active participation of Eurasian Economic Union countries in the development of digital sovereignty and international data exchange standards is essential for successful integration with the Silk Road Economic Belt initiative.

This article explores the development of a promising model for youth policy management processes at a university. It emphasizes the need to update the methodological framework for youth policy at universities and the creation of a process model based on IDEF0 notation and SADT methodology, aimed at optimizing key processes in this area. The goal of the model is to increase the number of successful young people, thereby enhancing the performance of the university, employers, and other stakeholders. The model includes six first-level subprocesses that ensure the holistic functioning of the system. An important part of the study is the rationale for developing a comprehensive youth policy management model that includes mechanisms for interaction between various actors and an infrastructure for its implementation. The "SVOi Heroi" Museum and Educational Space project serves as a practical example, demonstrating the potential of the proposed model in achieving its goals. The study emphasizes the importance of reducing organizational change by implementing educational and information service frameworks that are flexible for integrating stakeholders and new processes. The developed model is a tool for increasing the effectiveness of youth policy, ensuring an increase in the number of successful young people and the success of the university, employers, and other stakeholders.

Nigeria set a target of ninety-five percent adult financial inclusion by 2024 under the Central Bank of Nigeria’s National Financial Inclusion Strategy 3.0; the target was not met, and the North-West zone retained 47% exclusion against 5% in the South-West zone [1]. Blockchain-based banking services have since entered Nigerian commercial banking at institutional scale through the Zone network and allied fintech platforms. Whether the service attributes of these systems move operational financial inclusion, customer satisfaction, or both remain unresolved, and the two outcomes imply different management priorities. This study examines data from 423 active commercial bank customers in Lagos (n = 250) and Kano (n = 173), collected in 2025. Multiple regression and multi-group Z-tests after Paternoster et al. [2] are applied, with five blockchain attributes (Security, Transparency, Decentralization operationalized as perceived accessibility without institutional gatekeeping, Transaction Speed, Cost Efficiency) modelled as formative composite predictors of operational Financial Inclusion and Customer Satisfaction separately. Results indicate that blockchain attributes explain 36.4% of variance in operational Financial Inclusion against 3.1% of variance in Customer Satisfaction, with Transparency (b = 0.349, p < 0.001) and Decentralization (b = 0.318, p < 0.001) as the dominant positive predictors in all subsamples. Z-tests find no significant coefficient differences between Lagos and Kano on any tested path, while descriptive baselines diverge sharply (operational Financial Inclusion mean 3.940 against 2.942). The study concludes that in this sample and pre-adoption environment, blockchain attributes behave as participation-oriented predictors more than satisfaction-oriented predictors, that the mechanism is structurally equivalent across Nigeria’s digital banking spectrum, and that closing the North-South gap requires lifting the institutional baseline alongside technology design.

In the context of the rapid growth in volume and complexity of financial data, classical credit scoring models face limitations in forecast accuracy and sustainability. At the same time, clustering and machine learning methods are evolving, enabling the identification of latent borrower segments and the integration of this additional information directly into predictive models. This paper addresses the methodological gap between data segmentation and machine learning in credit risk assessment. The goal of the study is to develop a concept of a hybrid model that combines clustering analysis and gradient boosting algorithms by incorporating cluster meta-features into the feature space of a scoring model. The methodological framework includes an analysis for existing approaches to credit scoring, the design of a sequential data-processing pipeline, and the construction of a feature set that reflects the borrower’s structural position in the data space. In addition, the study evaluates the stability of clustering results with respect to the choice of metric, the number of clusters, and sample characteristics, as well as compares different ways of encoding cluster information. The proposed approach is aimed at improving model discriminatory power by accounting for latent customer segmentation. The expected deliverable is enhanced default prediction quality and expanded model interpretability, which increases their practical value for credit risk management and decision support in financial institutions.

The objective of the article is to study and systematize the specific features of IT project management in commercial banks amidst the emergency substitution of infrastructure software and hardware in 2024–2025. The study is based on the systematic analysis for the regulatory landscape (Bank of Russia requirements for operational resilience and protection of critical information infrastructure) and the analysis for practical experience in migrating high-load transactional systems. The authors substantiate the methodological conflict between strict compliance requirements and the need for agile adaptation to a sovereign technology stack. The scientific novelty of the work lies in the development of a mathematical model for assessing cumulative migration risk 𝑅_{𝑖𝑛𝑓𝑟𝑎}, enabling the implementation of predictive control over migration "maintenance windows". It has been established that an effective solution to the management crisis in the banking sector is the implementation of an organizational ambidexterity model – a synthesis of cascade control of regulatory requirements and an iterative cycle of technological implementation. It is proven that the use of intelligent decision support systems (AI-layer) allows compensating personnel shortages and reducing the probability of critical failures during system switchovers from 18% to 4%. It is concluded that the transition to sovereign intelligent management models is a fundamental condition for ensuring the operational stability of the financial sector.

The relevance of the study is determined by the need to improve the management efficiency of regional innovation systems (RIS) in the context of the digital transformation of the economy and limited budgetary resources. The Samara region, having significant scientific and technical potential, demonstrates insufficient dynamics of innovative development, which requires the development of scientifically sound forecasting tools. The academic literature offers numerous attempts to describe how innovation evolves within territories, and forecasting is generally viewed as a necessary analytical instrument. However, methodological support remains limited: few models can adjust to changing regional conditions while simultaneously reflecting heterogeneous determinants, feedback effects, and nonlinear links among participants of innovation activity. The article provides a justification and testing of methodological approaches to predictive and scenario modeling of RIS (using the Samara Region as an example) using multiple regression tools and a scenario‑based approach. Multiple linear regression, correlation analysis, step-by-step variable inclusion, and scenario forecasting were used to build the model. The verification of the obtained results was carried out on the basis of a comparative analysis with gradient boosting (XGBoost). The constructed regression model (R² = 0,94) includes seven predictors. The key factors are the number of small innovative enterprises (β = 0,350) and inventive activity (β = 0,240). Four scenarios have been developed for 2026–2029: basic (20,4% of GRP innovations), optimistic (24,8%), innovative (29,5%) and pessimistic (9,2%). The model is suitable for strategic planning of innovative development of the region. The key driver of growth is the support of small innovative businesses and the promotion of patent activity. The model is adaptable to other industrialized regions.

The paper proposes and tests a forecast model based on the regional statistics, which reveals the mutual dependence of investment attractiveness and innovation activity in the Samara Region. The theoretical and methodological framework of the study is based on the neoclassical tradition, the Schumpeterian interpretation of innovation development, the triple helix model, and the institutional approach. The author's model includes four feedback loops through which the regional system can shift to cumulative growth or remain in a stagnant trajectory. The empirical validation was conducted using data from the Samara Region for 2019–2023, employing regression modeling. The calculated results demonstrate high accuracy, with a MAPE value of 1,8%. The study confirms the two-way nature of the relationship, where a 1% increase in investment is accompanied by a 0,6–0,7% increase in innovation activity, and a 0,5–0,6% increase in innovation output leads to an additional 0,5–0,6% increase in investment a year later. The forecast for 2024–2029 indicates a steady average annual growth rate of 8–8,5%. It was found out that the Samara region is moving from the "territory of increased attention" group to the "territory of confident development" group. The expediency of forming a specialized institute has been confirmed, the task of which will be the real unification of investment and innovation channels. The proposals have been prepared to launch a mechanism for early detection of threats and prompt adjustment of regional processes during the period of external fluctuations.