The study focuses on identifying episodes of transmission of financial shocks from Asian stock markets to the Russian stock market in 2008–2023. Particular emphasis is placed on systematising key crisis episodes, their impact on the economies of Russia and Asian countries, and analysing existing methodologies for testing market contagion. The paper outlines fundamental distinctions between joint shocks and the transmission of financial crises, as well as approaches to verifying periods of financial contagion using statistical tools. To identify financial contagion of the Russian stock market originating from the stock markets of Asian countries, a modified approach by K. Forbes and R. Rigobon was employed. Its application revealed the greatest intensity of contagion of the Russian stock market from Asian markets during the China’s 2014 economic recession and the 2020 COVID pandemic. Over the entire period, the Russian stock market showed the greatest susceptibility to shocks emanating from the stock markets of the Republic of Korea, Indonesia, and Hong Kong. The conducted research made it possible to clarify the mechanisms of crisis transmission phenomena amid global instability, identify the specific vulnerabilities of the Russian stock market to Asian shocks, and establish a methodological foundation for further applied analysis. The findings underscore the need for a comprehensive approach to detecting contagion and may assist regulators and market participants in developing preventive measures to mitigate the risks of cross-border financial contagion.
Amid accelerated digital transformation and mounting geo-economic turbulence, the challenges of safeguarding digital security in the real economy and achieving technological sovereignty have become critically important for international business. This article provides a comprehensive analysis of the key risks and strategic challenges faced by multinational corporations in the digitisation of global economic relations. The authors examine a broad spectrum of threats – from the rising frequency of large-scale cyberattacks targeting critical information infrastructure to the progressive fragmentation of digital space driven by protectionist barriers, technological sanctions, and policies of digital isolation. Particular attention is devoted to the methodological foundations of information security and conceptual approaches to establishing technological sovereignty, which serve as interconnected factors in ensuring long-term competitiveness and sustainable business development in an era of global instability. Drawing on an in-depth study of leading Russian companies successfully adapting to these new realities, the paper formulates concrete recommendations for building effective cyber defence systems, localising digital assets, and developing strategies for technological independence. The findings hold significant value both for academia – particularly researchers examining the evolution of international business models – and for corporate practitioners, including senior executives, cybersecurity specialists, and digital policy developers, who face the pressing need to rethink conventional approaches in light of profound shifts within the global digital ecosystem.
The article examines the prospects for establishing a new global monetary system within the expanded BRICS+ framework as an alternative to the existing dollar-centric financial architecture. The author conducts a comprehensive analysis of contemporary geopolitical and economic factors, including escalating sanctions pressure and the pursuit of financial sovereignty, which necessitate a transition towards a polycentric model of international economic relations. Central to the study is the concept of the BRICS UNIT – a collective settlement unit based on a basket of member states’ national currencies. The paper proposes a multi-stage implementation mechanism, ranging from the development of digital platforms for cross-border transactions to the establishment of a supranational BRICS+ Central Bank. Particular emphasis is placed on the institutional role of the New Development Bank (NDB) and other financial structures independent of the US-dominated financial system. A comparative analysis of historical precedents in international monetary integration is provided, including the experience of the transferable rouble within the Council for Mutual Economic Assistance (CMEA) and the European Currency Unit (ECU) in the European Union (EU), revealing key patterns in the formation of regional currency zones. The author argues that such zones reduce global reliance on the US dollar. The concluding section highlights that the project’s success hinges on achieving consensus among member states and overcoming institutional resistance.
In recent years, foreign trade operations involving Russian dairy products have been significantly complicated by sanctions imposed on the national economy. These measures have detrimental impacted both the logistics of finished product supply chains and producers’ access to essential raw materials – particularly milk. The supply of components for butter production has become especially challenging amid a raw milk shortage in the Russian consumer market. Consequently, contradictory trends have emerged for Russian butter, manifesting in an unexpected retail price during autumn 2024. Identifying key factors influencing butter production and distribution organisation in Russia represents a crucial scientific and practical objective. Addressing this issue would help balance raw material import portfolios. This study examines the fundamental aspects of butter imports in both volume and value terms. Based on international statistical analysis, the author provides scientific generalisations aimed at defining prospective policy directions for producing and distributing butter from imported dairy raw materials in the Russian Federation. The findings highlight the essential nature of state import for domestic dairy producers. Such measures should focus on stimulating their economic activity while reducing barriers to global food industry market entry.
The article examines the optimal trajectory for transforming economic relations, focusing on the development of machine-to-machine interaction while preserving human managerial control. Unlike the prevailing approach in the digital agenda, which prioritises the replacement of human labour with automation, the proposed model emphasises the importance of collective digital planning. This approach ensures active human participation in analytical and decision-making processes, thereby enhancing the quality, flexibility, and adaptability of managerial systems. In this context, the rationale behind the Concept of an Open Government Digital Platform (OGDP) gains particular significance, marking a shift from traditional digital economy ecosystems to a fundamentally new architecture of network interaction. The relevance of this research lies in the pivotal role of economic digitalisation through the implementation of OGDP, which holds strategic importance for Belarus and Russia. This technological platform facilitates the optimisation of macroeconomic conditions, modernises state-society interactions, streamlines technological and production processes, and fosters the evolution of business strategies and marketing tools for product promotion. The objective of this study is to develop a conceptual framework, a feasibility assessment, and practical implementation mechanisms for an innovative platform that aligns with the digital transformation goals of the Eurasian space, taking into account the significant role of the state in the economy. As a result of this research, practical recommendations have been formulated for the integration and utilisation of OGDP in administrative practices amid the digital transformation of the Union State (US) economy.
The study examines the impact of digitalisation on the management of multicultural teams and proposes strategies for their effective integration within the context of contemporary business transformations. The aim of this work is to identify factors that enhance collaboration among participants representing diverse cultural and national backgrounds – a matter of growing relevance in an increasingly multipolar world. The research framework encompasses a theoretical analysis of existing management approaches, a review of digital tools employed to support teamwork, and practical recommendations for organisations. Particular emphasis is placed on the need to foster an inclusive corporate culture that values diversity and respects cultural differences, as well as the importance of considering interaction dynamics when formulating team strategies. The analysis reveals that digital technologies – including collaborative platforms, video communication tools, and project management systems – enhance communication efficiency and improves mutual understanding among team members, thereby reducing the likelihood of conflicts and misunderstandings. The findings confirm that successful integration of multicultural teams requires a systemic approach that accounts not only participants’ professional competencies alongside their cultural nuances. In conclusion, the study outlines promising directions for future research, including the adaptation of management strategies to the rapidly evolving global market conditions, and фт assessment of digitalisation’s long-term effects of management processes within multinational teams.
The article examines contemporary practices of implementing machine learning methods within the insurance industry. It analyses key applications of machine learning, including risk assessment and forecasting, claims processing automation, fraud prevention, and the personalisation of insurance products and pricing. We focus particularly on the adoption of cluster analysis for customer segmentation. Drawing on case studies from leading Russian and international insurers, the study demonstrates that machine learning adoption reduces operational costs, enhances risk assessment accuracy, and minimises human-factor errors. The findings indicate that machine learning implementation has become a critical competitive differentiator in an increasingly digitalised market, where growing data volumes necessitate advanced analytical capabilities – delivering not only significant cost efficiencies but also improved employee productivity by automating routine tasks. Future integration of machine learning algorithms is expected to substantially reduce processing times for policyholders through automated claims submissions. However, successful deployment requires upskilling employees and access to large datasets, the latter often proving challenging for smaller insurers. The article also addresses data privacy concerns and regulatory considerations in this domain.
