Strategic Risk Research Articles (Page 1)

This paper examines Sino-Russian cooperation following the outbreak of the Russia-Ukraine War in 2022 using realist alliance theory as an analytical framework. It argues that the partnership is a pragmatic, crisis-driven alignment rather than a quasi-alliance. Three drivers explain the intensified cooperation: Russias strategic demand amid confrontation with the West, the mitigation of Chinas fear of Russian abandonment, and structural openings from Russias weakened influence in Central Asia and the Arctic. These factors have expanded trade, joint military activities, and Chinese involvement in regional infrastructure projects. However, the paper also identifies significant constraints, particularly the growing asymmetry in economic dependenceRussia increasingly relies on China, but not vice versaand the risk of China being entrapped in Russias geopolitical conflicts. Additionally, the warming Russia-North Korea relationship introduces a third-party variable that complicates Chinas strategic calculations. Ultimately, the paper concludes that while the war has accelerated Sino-Russian cooperation, it has also reinforced structural imbalances and strategic limitations, making a formal alliance unlikely. The future trajectory of this partnership will depend on Russias post-war strength and Chinas ability to balance alignment benefits with strategic risks.

Purpose – The purpose of the study is to critically examine existing scientific approaches to the role and structure of accounting and analytical support in managing foreign economic activity at the enterprise level, with particular emphasis on risk management. The research focuses on conceptual models and algorithms for building a foreign economic activity management system, highlighting the accounting system’s function and its role as a managerial instrument. Design/methodology/approach – The study is based on a systematic approach to the study of scientific sources, which allows identifying key trends, conceptual approaches and scientific gaps in this area. The method of analysis and synthesis is used to identify the main theoretical provisions and systematize approaches to organizing accounting and analytical support for foreign economic activity; the inductive method is used to draw general conclusions about the trends in scientific research in the field of accounting and analytical support for managing foreign economic activity; comparative analysis is used to compare scientific approaches to building an accounting and analytical system in the field of foreign economic activity, identifying their strengths and weaknesses; systematization and classification are used to structure the source according to certain criteria. The historical-logical method allows us to trace the development of accounting concepts in the context of transformations in the foreign economic environment. Findings – The study confirms that research on the role of accounting within the structure of managerial relationships in an enterprise’s foreign economic activity, as reflected in modern scientific publications, primarily emphasizes its auxiliary function and lacks specification of the informational value it provides for the management system. Accounting is typically viewed from two perspectives: as a management function within a complex system of relationships involving planning, control, and analysis; and as a subsystem of the enterprise’s foreign economic activity management system, intended to supply stakeholders with decision- relevant information. Contemporary models of accounting and analytical support for managing foreign economic activity predominantly concentrate on the following conceptual links: the interrelation of the accounting subsystem with the overall management system; accounting as a managerial function; the structure of support considering export and import specifics; the regulatory and methodological context; and the stages of the operational mechanism. The positioning of accounting within the foreign economic activity management system depends on the management process model adopted by top-level managers. Practical implications – The study creates the prerequisites for the practical implementation of theoretical principles in the field of foreign economic activity of business entities, contributing to the formation of an adaptive system of accounting and analytical support that meets the needs of modern management. In particular, taking into account the impact of accounting information on managerial decision-making processes allows for increased efficiency in strategic planning, financial monitoring, and risk management. Such practical integration enhances the validity of management decisions, supports the harmonization of internal regulations with external requirements, and establishes a foundation for improving the informational environment of managerial activity. Originality/value – The study contributes to positioning accounting as an important component within the structure of managerial relationships in the enterprise’s foreign economic activity. It highlights the significance of accounting and analytical support in foreign economic activity management models. The findings reveal that current domestic models lack clear positioning of accounting as both a functional and an informational support element, which creates a foundation for further refinement of theoretical frameworks and practical applications of accounting and analytical support in the foreign economic domain.

The Newcomer's Dilemma: Navigating Strategic Risks in Nuclear Fuel Cycle Development A Simulation-Based Framework for Indonesia

The increasing adoption of artificial intelligence (AI) and machine learning (ML) in business has introduced profound opportunities for improving decision-making, efficiency, and profitability. Traditionally, the purpose of business has often been framed through the lens of maximizing shareholder value (MSV), a concept popularized by Milton Friedman and further developed by Jensen and Meckling. While AI and ML can enhance shareholder returns by enabling precise forecasting, automated decision-making, and optimization of operations, reliance on MSV as the sole objective introduces significant ethical, strategic, and societal risks. This paper examines the limitations of pursuing MSV in AI-driven business contexts, focusing on short-termism, stakeholder neglect, reputational risks, and ethical dilemmas. Through practical scenarios drawn from financial services, retail, and human resource management, the analysis highlights how AI/ML, if unmoderated, can amplify the inherent shortcomings of MSV. Additionally, the paper identifies gaps in current research, noting that existing studies have rarely integrated discussions of AI ethics with the classical MSV debate. By providing a conceptual framework that links AI-driven analytics to stakeholder-inclusive approaches, this study contributes to a more responsible understanding of value creation in contemporary business environments. Recommendations are offered for integrating ethical AI practices, multi-metric performance evaluation, and long-term strategic planning to balance shareholder and stakeholder interests.

The integration of Information Technology (IT) investments and business analytics has become a cornerstone in reshaping healthcare performance, driving both operational efficiency and improved patient outcomes. As healthcare systems grapple with rising costs, regulatory complexities, and evolving patient demands, the strategic alignment of IT with business objectives emerges as a critical determinant of success. Financial and non-financial metrics, including return on investment, patient safety, workflow efficiency, and quality of care, are increasingly used to evaluate the impact of IT expenditures. However, organizations face persistent challenges, including escalating labor costs, cybersecurity threats, regulatory compliance, and difficulties in workforce recruitment and retention. Business analytics plays a transformative role in decision-making, leveraging predictive models and statistical tools to enhance disease detection, personalize treatment, optimize resource allocation, and reduce operational inefficiencies. To maximize value, organizations must employ structured frameworks that include identifying key performance indicators (KPIs), implementing robust monitoring systems, and embedding continuous improvement cycles. Effective integration of IT and analytics not only strengthens patient-provider relationships but also supports long-term sustainability and competitiveness in a resource-constrained environment. Looking ahead, emerging trends such as digital transformation, artificial intelligence, telemedicine, and patient-centric care models will further shape healthcare delivery. Strategic risk management, workforce development, and proactive regulatory adaptation will be pivotal for leveraging these innovations while safeguarding patient trust. Ultimately, the successful fusion of IT investment and analytics represents a vital pathway to achieving measurable improvements in healthcare performance, organizational resilience, and patient outcomes.

The oil and gas industry faces unprecedented challenges in optimizing drilling operations while maintaining safety standards and operational efficiency in an increasingly complex technological landscape (Agapiou et al., 2012). This research presents a comprehensive AI-enhanced predictive model designed to transform drilling operations through advanced machine learning algorithms, real-time data analytics, and predictive maintenance protocols. The study addresses critical gaps in current drilling optimization methodologies by integrating artificial intelligence with traditional drilling engineering principles to create a future-ready operational framework. The proposed model leverages deep learning techniques (Goodfellow, Bengio, & Courville, 2016), Internet of Things (IoT) sensors (Li, Ota, & Dong, 2018), and cloud-based analytics to predict equipment failures, optimize drilling parameters, and enhance overall operational efficiency. Through extensive analysis of drilling data patterns, equipment performance metrics, and geological conditions, the AI system provides real-time recommendations for drilling optimization while minimizing non-productive time and reducing operational costs. The research methodology encompasses comparative analysis of traditional drilling approaches versus AI-enhanced systems, implementation of machine learning algorithms for predictive analytics, and validation through industry case studies. Key findings demonstrate that AI-enhanced drilling operations can reduce non-productive time by up to 35%, improve drilling efficiency by 28%, and decrease equipment failure rates by 42% compared to conventional methods (Bourgoyne Jr et al., 1986). The predictive model successfully integrates multiple data sources including drilling logs, sensor readings, geological surveys, and historical performance data to generate accurate predictions for optimal drilling parameters. Implementation challenges include data quality assurance, system integration complexities, and workforce training requirements, which are addressed through comprehensive change management strategies (Essien et al., 2019). The research contributes to the advancement of smart drilling technologies by providing a scalable, adaptable framework that can be implemented across diverse geological formations and drilling environments. The model's architecture incorporates federated learning principles (Soneye et al., 2025) to ensure continuous improvement while maintaining data privacy and security standards. Future applications include integration with autonomous drilling systems, enhanced environmental monitoring capabilities, and expanded predictive maintenance protocols for complex drilling equipment (Dare, Ajayi, & Chima, 2025). This study establishes the foundation for next-generation drilling operations that combine human expertise with artificial intelligence to achieve unprecedented levels of operational efficiency and safety. The implications extend beyond immediate operational improvements to encompass strategic planning, risk management, and sustainable resource extraction practices that align with industry 4.0 principles and environmental stewardship requirements (Fasasi, Adebowale, & Nwokediegwu, 2025). Keywords: Artificial Intelligence, Predictive Modeling, Drilling Operations, Operational Efficiency, Machine Learning, Iot Sensors, Predictive Maintenance, Smart Drilling, Data Analytics, Industry 4.0.

Purpose While London remains a key global investment hub, Brexit-induced uncertainties and economic shifts have spurred diversification into other European markets. The paper underscores the need for adaptive strategies, including policy interventions to enhance fiscal and monetary stability, and highlights the importance of currency risk management for investors navigating a volatile global investment landscape. These insights offer valuable implications for sustaining London's competitiveness in an evolving geopolitical and economic context. Design/methodology/approach This study investigates the influence of Brexit on global capital flows into London's office market using data from Real Capital Analytics (RCA/MSCI), encompassing office transactions between 2016 and 2023. The analysis employs autoregressive distributed lag models. Findings The research evaluating how domestic and international factors have influenced investment patterns in the post-Brexit era highlights the critical role of the real effective exchange rate, which significantly impacts cross-border investments in both the short and long run, with depreciation of the pound sterling driving increased inflows. Domestic variables such as UK stock market capitalization and equivalent yield impact also emerged as significant factors influencing capital flows. While London's status as a prime investment destination persists, the research identifies a decline in transaction volumes, reflecting investor caution and diversification towards other European markets post-Brexit. The analysis reveals that global factors, including geopolitical tensions and risk indices, play a relatively limited role compared to domestic market conditions in shaping investment patterns. These findings underscore the importance of exchange rate stability, strategic currency risk management, and adaptive policies to sustain London's competitiveness amid heightened economic and geopolitical uncertainty. Originality/value This paper offers a novel contribution by providing a comprehensive analysis of the interaction between domestic and international factors affecting cross-border real estate capital flows in London's office market in the post-Brexit era. It sheds new light on how domestic economic conditions outweigh global factors in shaping investment decisions and offers crucial policy recommendations for sustaining London's competitive edge.

This article explores how natural wood materials—especially untreated or minimally treated timber—are perceived and experienced during tourist experiences in recreational and tourism-oriented built environments. Drawing on principles of biophilic design and cultural theories of authenticity, the study examines both the psychological and the physiological impacts of wood surfaces on users. One of the objectives of this study is to strengthen the theoretical background and to explore the connections between tourists’ experiences and the material environment. Two pilot studies were conducted: a questionnaire administered to visitors of a national design fair (n = 37) and a physiological experiment measuring user responses to three material types (solid oak, chipboard, and white laminate). The results indicate that natural wood evokes significantly more positive emotional responses and is strongly associated with authenticity, sustainability, and comfort, although concerns about hygiene and surface aging persist. A SWOT analysis is used to summarize the strategic opportunities and risks associated with wood in tourism design. The findings support the inclusion of natural wood as a multisensory design element that enhances atmosphere, emotional engagement, and perceived environmental quality—especially when surface maintenance and cultural framing are appropriately addressed.

Project management is based on the appropriation of resources for the implementation of an idea, applying a certain methodology for the processes developed in the search for solutions to the identified need. This being the function of every entrepreneur and on which this research is focused, where the objective was to diagnose the management they carry out around parameters such as time, costs, risks, scope and resources, in order to identify strengths and areas of improvement in their organizational performance, considering that their activities have to adjust to the guidelines of the project management, to achieve a timely activation of businesses and be a generator of changes in the municipality. The study had a descriptive and qualitative approach, with an intentional sample of ten entrepreneurs from Ocaña, to whom a semi-structured interview validated by experts was applied. The information collected was complemented with the review of documents from the Ocaña Chamber of Commerce and was analyzed through narrative interpretation, thematic categories and dynamic schemes. The results show that, although entrepreneurs have initiative, experience and recognition in the market, they face limitations in strategic planning, risk management and formalization of processes. Both internal and external factors that influence its sustainability were identified, synthesized in a situational diagnosis reflected in a matrix of analysis of strengths, weaknesses, opportunities, and threats. Based on these findings, strategies and actions were proposed aimed at strengthening their management capacities, improving the competitiveness of businesses and contributing to local economic development. It is concluded that the application of project management methodologies is a key tool to enhance the growth of enterprises in the trade sector.

In every aspect of the financial industry—from decision-making to risk management, fraud detection and customer service—artificial intelligence (AI) is causing significant changes. This paper reviews the application of AI in finance and is based on more than 40 Scopus-indexed articles which provide some fresh insight. With the help of advanced machine learning and deep learning algorithms, banks are achieving unprecedented levels of efficiency and personalized service. This research looks at major AI applications, bringing into focus their potential role in strategic decision-making and risk assessment. However, it also critically analyses key challenges, such as data privacy issues, how to explain models under scrutiny from humans (i.e., theoretically impossible), and ethical considerations attached to AI's implementation. The evolution of AI technologies creates not only disruptive opportunities but also complex regulatory issues for financial services. By compiling the findings of the present research, this review gives a comprehensive description of how AI is remoulding the field of finance and offering directions for what comes next.

This study analyzes the implementation of risk management at PT Lippo General Insurance Tbk over 2022–2024 using a qualitative descriptive approach. The review focuses on the four core risk-management cycles: identification, measurement, monitoring, and mapping–mitigation and on one key output: the risk profile assessment (inherent risk rating, quality rating of risk-management implementation, and implementation of risk level). The results indicate that risk-management processes are consistent and well documented through a risk register and supported by a Risk Management Information System, enabling rapid linkage of findings to action plans. Overall, the composite risk profile remains low, underpinned by a moderately strong quality of implementation and risk-level application. On the inherent-risk dimension, dynamics are observed: strategic risk improves in the final year, while insurance, credit, and liquidity risks rise relative to 2023. Nevertheless, the consistency of implementation quality and disciplined execution mitigates these effects, keeping the composite profile stable. Managerial implications include strengthening underwriting and claims management, enhancing counterparty and reinsurance quality, and enforcing liquidity discipline, while maintaining a strong risk culture and tiered monitoring mechanisms.

Emergent cooperative decision-making in triadic Prisoner's Dilemmas: Effects of incentives and information.

Expert opinion is an ingrained part of risk analysis, but there needs to be more debate on the efficacy of Strength of Knowledge (SoK) in aggregated reports, such as the national risk registers. This paper discusses the conceptual foundation of using SoK related to the utility of expert opinion in risk analysis and subsequent reporting. The paper takes its outset in the Danish National Risk Register, which is a publication issued by the Danish Emergency Management Agency (DEMA) that describes threats to Danish society over the next five years. The ambition is for government agencies, companies, and other organisations to use the profile as a strategic document that identifies which threats they are to include in their strategic risk assessment. The threats are determined by experts from 15 government agencies who have provided their opinions on 14 different threats, which are subsequently analysed by DEMA. The use of experts raises the question of how the SoK could be a factor influencing the national risk strategy and, thereby, the mitigation initiatives taken by private, public, and non-governmental organisations that use the recommendations in the report. The paper utilises an analytical approach based on systems theory and sensemaking, which includes an assessment of both expert and risk analysis SoK, resulting in concrete proposals in the NRP. The analysis reveals that SoK plays a significant role in the National Risk Profile, and uncertainties associated with the analysis indicate that threats may be over- or underrepresented by DEMA, potentially leading to flawed strategic risk governance decisions by the report’s readers. The paper presents an alternative approach to estimating SoK, which highlights simplifications, articulates the empirical foundations, provides room for multiple interpretations, describes the phenomenon as understood within these simplifications, and offers insights into the assumptions about the knowledge we have about the phenomenon.

Abstract China’s special access policies for unapproved drugs and medical devices represent a key institutional innovation in its healthcare regulatory system. In recent years, tailored versions of this policy have been implemented in Hainan Lecheng, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), and Beijing Tianzhu, each exhibiting differentiated trajectories in institutional design and management mechanisms. This study identifies a pattern of policy evolution termed Strategy-Embedded Diffusion, a model wherein the central government does not mandate a uniform policy model, but strategically deploys this tool to different strategic regions in alignment with national objectives. To analyze this phenomenon, this study develops a three-tiered interactive framework encompassing central delegation, local innovation, and social feedback. A comparative case analysis reveals that: the central government delineates distinct scopes of authorization based on each region’s strategic positioning and risk tolerances; local governments engage in selective learning and institutional reproduction tailored to local conditions; and key societal stakeholders actively shape policy refinement through continuous feedback.

Subject. This article considers the tokenization of the national currency as a tool for transforming the international settlement system. Objectives. The article aims to conduct a comparative analysis of the models for tokenized ruble use in foreign economic transactions and show the need to develop alternative settlement mechanisms in the context of Russia's limited access to the international payment infrastructure and geopolitical risks. Methods. For the study, we used a scenario approach, including institutional modeling, strategic risk assessment and stakeholder analysis. Results. Based on the analysis of the three models for using the tokenized ruble, the article identifies the key advantages and limitations of each particular model with regard to technological feasibility, sovereignty, regulatory flexibility and economic efficiency. Conclusions and Relevance. The hybrid model, which combines the centralized emission of the digital ruble with the use of private tokens, is the most adaptive and realistic one at the current stage of development of the financial infrastructure. Its implementation requires a comprehensive regulatory framework, technological compatibility and international recognition. The results of the study can be used by government agencies, regulators, financial market participants and payment solution developers to formulate a strategy for introducing digital currencies into international settlements.

This article explores the essence and significance of strategic risk management (SRM) as an integral component of modern management systems within contemporary business organizations. The study highlights the fundamental distinctions between SRM and traditional operational or financial risk management, emphasizing that SRM transcends mere risk mitigation to become a proactive, forward-looking tool. This tool is crucial for fostering sustainable development, ensuring long-term organizational resilience, and securing a competitive advantage in today’s increasingly turbulent and complex business environment. This research systematically outlines the core principles, objectives, and rationale for implementing strategic risk management. A comprehensive logical-structural framework is proposed to illustrate the interconnectedness of the essential elements of the SRM methodology. These elements include goal setting aligned with long-term strategic priorities, comprehensive risk identification, thorough risk assessment, the development of tailored response strategies, and continuous feedback and monitoring mechanisms. Special emphasis is placed on the need for the ongoing methodological refinement of SRM components, ensuring that each element functions effectively within the broader enterprise management system. Furthermore, the paper underscores the imperative for business organizations to move beyond reactive, fragmented approaches to risk management. It advocates for adopting adaptive and dynamic procedures that enable enterprises to anticipate and respond to emerging challenges, thereby facilitating strategic transformation and sustainable growth. Integrating SRM into corporate governance frameworks enhances strategic decision-making and fosters an organizational culture grounded in resilience, heightened risk awareness, and strategic foresight. Ultimately, the article argues that a well-developed and systematically implemented SRM methodology not only aids in risk containment but also serves as a catalyst for innovation and the identification of new business opportunities. This approach positions SRM as a vital driver of organizational success and sustainability amid volatile, uncertain, complex, and ambiguous (VUCA) business conditions.

Purpose This research explores how organizations in emerging markets address corporate responsibility through dual risk reporting of compliance obligations and internal strategic risk management. By integrating Institutional Theory and Learning Theory, the research examines how regulatory pressures, and organizational learning (“tone from the top”) shape the unique challenges in the Indian insurance sector. Design/methodology/approach Using a qualitative approach, the study draws on interviews with executives from a leading Indian insurance company, supplemented by an in-depth case study. The research applies causal loop analysis to map interdependencies between formal compliance-driven risk reporting and informal strategy-focused governance practices within the organization. Findings The study identifies two key barriers to effective risk reporting; (1) firms frequently adopt a compliance-oriented mindset, viewing risk reporting as a regulatory requirement rather than a strategic function, and (2) weak organizational learning impairs adaptability and undermines the long-term utility of risk reports. Originality/value This study introduces a Practical Dual Risk Reporting Framework that positions dual disclosure as a mechanism of corporate responsibility, enabling firms to respond simultaneously to institutional pressures and internal governance needs. The framework bridges theoretical insights with practical applications, supporting more integrated and accountable risk governance in institutional contexts.

BACKGROUND In the context of the growing role of nonfinancial factors in the banking sector, the issue of assessing the impact of environmental, social, and governance (ESG) indicators and digital maturity on the financial stability of banks is of particular relevance. Digitalization, combined with environmental and social challenges, creates new risks and requires a revision of approaches to strategic management. The purpose of the study is to examine the impact of the ESG index and digital maturity on the key indicators of financial sustainability of Ukrainian banks (return on equity and capital adequacy ratio) based on a quantitative model. MATERIALS AND METHODS Methodologically, the study is based on regression and correlation analyses using linear modeling in the SPSS environment, as well as the development of a composite index—the Sustainable Banking Index (SBI). RESULTS As a result, a statistically significant negative impact of both ESG indicators and digital maturity on profitability and capital adequacy has been found, which indicates the short-term financial costs of implementing nonfinancial strategies. The proposed integrated SBI indicator has demonstrated a high strength of connection with key financial parameters and proved to be an effective tool for forecasting the capital burden. CONCLUSION The practical significance of the work lies in the possibility of using the SBI as a dynamic tool for monitoring the sustainability of banks in the context of digital transformation. The results can be implemented in the system of strategic audit, risk assessment, and planning of digital and ESG initiatives in financial institutions. The study also lays the foundation for the development of adaptive models that combine nonfinancial parameters with classical financial indicators in the processes of bank resilience management.

This study evaluates the financial feasibility of constructing a new Madrasah Tsanawiyah building at PPNI Foundation in East Lampung, Indonesia, using capital budgeting methods and Monte Carlo simulation. The research applies Net Present Value (NPV), Internal Rate of Return (IRR), Payback Period (PBP), and Profitability Index (PI) to assess project viability. Sensitivity analysis identifies the most influential variables, while Monte Carlo simulation measures probabilistic risks. Findings indicate an NPV of IDR 18.57 billion, an IRR of 19.89%, a PI of 1.288, and a PBP of 5.23 years, confirming project feasibility. Sensitivity analysis highlights WACC, donation fee growth, and enrollment fee changes as key factors. The results guide strategic decisions and risk mitigation in educational infrastructure investments.

Project alliancing has emerged as a transformative procurement strategy, fostering collaboration, risk-sharing, and innovation in construction. As the industry moves toward more integrated delivery models, understanding the evolving research landscape becomes essential. This study conducts a bibliometric analysis of 134 Scopus-indexed publications (1996–2025) to uncover key research trends, influential contributors, and thematic developments in project alliancing. Findings reveal six major research themes: strategic collaboration, relationship management, innovation and risk resilience, infrastructure procurement, lean construction, and organizational culture. Australia leads in research output, with increasing contributions from Finland, the UK, and Malaysia. Over time, the focus has shifted from broad alliance principles to specialized areas such as incentive structures, digital integration, sustainability-driven procurement, and collaborative-driven governance. Despite growing global interest, gaps remain in alliance organizational culture and capability building, contractual governance, and sustainability integration. This study provides a research roadmap, guiding future studies and industry adoption of project alliancing for improved collaboration and efficiency.