ABSTRACT The concept of social resilience broadly refers to a community’s ability to deal with, adapt to, and transform in the face of crises. In this paper, we examine how co-design practices within the context of mandated forums can facilitate and reconfigure disaster risk governance in the Indian Sundarbans Delta. Using participatory mapping, design charrettes, and validation circles, we explore the dynamic relationship between traditional ecological knowledge and scientific knowledge to co-design solutions, such as climate-resilient betel vine (Piper betle) cultivation, the placement of afforestation interventions, as well as co-designing integrated water management systems. Three embedded co-design processes involved residents affected by floods and cyclones collaborating with government engineers, members of the Water User Association (WUA), and non-governmental organisations (NGOs) to refine the technical, procedural, and institutional framework for risk management. Throughout this examination of co-design as a methodology, we consider how these design interactions alter the nature of the relationship by transforming rules, routines, and material infrastructures. It contributes to codesign scholarship by demonstrating how facilitation, timing, and epistemic negotiation operate as situated design moves that embed plural knowledges and community claims within public-sector decision-making.

Risk management in healthcare organizations has emerged as a critical determinant of clinical safety outcomes. This literature review systematically examined peer-reviewed studies published between 2013 and 2024, focusing on the implementation of risk management frameworks, incident reporting systems, patient safety culture, and their measurable effects on clinical outcomes. A total of 45 articles were screened from databases including PubMed, Scopus, and CINAHL, with 28 studies meeting the inclusion criteria. Findings revealed that structured risk management programs, particularly those integrating the ISO 31000 framework and failure mode and effects analysis (FMEA), were consistently associated with significant reductions in adverse events, hospital-acquired infections, and medication errors. Leadership commitment, interprofessional communication, and organizational learning culture emerged as pivotal mediating factors. However, challenges including resource constraints, staff resistance, and inadequate reporting infrastructure persist across low- and middle-income healthcare settings. This review underscores the need for context-sensitive risk management strategies and robust policy frameworks to enhance clinical safety outcomes globally.

The implementation of the global IFRS S2 standard regarding climate-related disclosures presents new challenges for corporate reporting transparency in developing economies. This study aims to evaluate the readiness of climate-related disclosures of PT Telkom Indonesia (Persero) Tbk in its 2024 Sustainability Report based on IFRS S2 requirements. This research employs a qualitative approach using content analysis of public corporate documents, utilizing the IFRS S2 disclosure checklist instrument, which covers four main pillars: governance, strategy, risk management, and metrics and targets. The findings indicate that PT Telkom Indonesia demonstrates a partial level of readiness in adopting the standard. Mature readiness is identified in the governance and risk management pillars, where climate change issues have been effectively integrated into board oversight structures and enterprise risk management frameworks. However, material gaps are found in the strategy and metrics pillars, particularly regarding the absence of quantified financial effects of climate risks on the company’s financial position, the lack of quantitative climate scenario analysis, and the incomplete Scope 3 GHG emissions inventory. The study concludes that while institutional foundations are established, the company needs to prioritize the development of financial impact models and the expansion of supply chain data to achieve full compliance in the future.

ABSTRACT Xenophobic violence has become a persistent threat to human security in post-apartheid South Africa, disproportionately targeting African migrants. Despite its frequency and destabilising effects, this form of violence remains largely absent from national disaster risk management (DRM) frameworks, which continue to prioritise environmental hazards over socially driven risks. This article conceptualises xenophobia as a slow-onset, socially constructed disaster risk that undermines social cohesion and regional stability. Drawing on Integrated Threat Theory (ITT), the study explores the perceived drivers of xenophobic violence, including economic competition, cultural threat, and intergroup anxiety through survey data collected from 33 DRM practitioners and academics. The findings reveal a critical gap between current DRM practices and the need for inclusive, anticipatory approaches to identity-based violence. The article argues for the formal recognition of xenophobic violence within DRM systems, including its integration into risk assessments, early warning mechanisms, and public education strategies. By reframing xenophobia as a security and governance issue, the study contributes to a broader understanding of disaster risk in Africa and calls for more adaptive and socially responsive DRM frameworks that reflect the continent’s complex human security landscape.

This study provides a comprehensive bibliometric analysis of internal audit research within higher education institutions, mapping the intellectual structure, evolution, and emerging trends in this specialized field from 1994 to 2024. Using bibliometric analysis with the Bibliometrix R package and Biblioshiny interface, this study analyzed 162 documents from the Scopus database. The analysis employed multiple techniques including co-occurrence network analysis, thematic mapping, Bradford's Law application, and temporal evolution tracking to identify research patterns, influential works, and collaboration networks. The research reveals three distinct evolutionary phases: Foundation (1994-2010), focusing on compliance and financial controls; Growth (2011-2020), emphasizing risk management and governance frameworks; and Acceleration (2021-2024), integrating digital transformation and sustainability concerns. Analysis identified 441 contributing authors across 113 sources, with limited international collaboration (20.97%). Thematic analysis revealed four primary clusters: governance mechanisms, internal control systems, audit effectiveness, and emerging technologies. The field demonstrates a paradigm shift from traditional compliance-focused auditing to strategic governance partnership, with increasing emphasis on value creation, institutional resilience, and stakeholder accountability. Higher education institutions should reconceptualize internal audit functions as strategic governance partners rather than compliance monitors. The findings suggest the need for enhanced digital capabilities, sustainability integration, and cross-functional collaboration in audit practices. The study provides a comprehensive mapping of internal audit research specifically within higher education contexts, offering unique insights into the field's evolution and future trajectories. The multi-dimensional analysis framework contributes methodologically to bibliometric research while providing actionable intelligence for academic administrators, audit practitioners, and policy makers.

The rapid advancement of financial technology (fintech) has significantly disrupted the traditional banking sector by introducing innovative services and business models that enhance efficiency, reduce costs, and promote financial inclusion. However, these benefits also bring emerging operational risks, such as cybersecurity threats, data privacy concerns, and regulatory compliance challenges. This systematic literature review synthesizes findings from 13 peer-reviewed journal articles published in the last five years, selected through a rigorous PRISMA-based methodology. The analysis identifies key themes, including the transformative role of technologies like artificial intelligence, blockchain, and big data analytics; the reconfiguration of risk management frameworks; and the evolving relationship between digital innovation and operational resilience. The results indicate that while fintech adoption offers substantial opportunities for competitiveness and customer engagement, it also necessitates proactive governance, robust cybersecurity measures, and continuous workforce upskilling. The discussion emphasizes the need for collaborative efforts among regulators, financial institutions, and technology providers to develop adaptive strategies that can mitigate risks in an evolving digital landscape. By addressing both the opportunities and vulnerabilities presented by fintech disruption, this review enhances our understanding of its implications for operational risk in banking and provides directions for future research.

Risk management maturity models (RMMMs) have been increasingly integrated into public organizations to promote structured and proactive risk management. Several studies across different countries proposed frameworks to guide institutions in strengthening their practices. Despite these developments, a persistent imbalance between scientific rigor and practical applicability remains, leaving many public institutions with either complex models to implement or overly simplified frameworks that lack meaningful insights. This gap is particularly evident in the Georgian public sector, where adoption of a comprehensive risk management framework has been significantly delayed. The present study introduces Risk-MM-Georgia, a novel RMMM developed using the design science research (DSR) methodology. The model was applied to nine major public organizations and externally validated against Brazil’s PRisk-MM, a framework successfully implemented within the Brazilian public sector (de Lorena & Costa, 2023b). The analysis yielded consistent findings, with 77.78 percent of the organizations achieving the same maturity level under both models, thereby supporting the reliability of the proposed framework. Overall, Risk-MM-Georgia bridges theory and practice by providing step-by-step guidance for public institutions and demonstrating global relevance through cross-national benchmarking.

The swift evolution of artificial intelligence (AI) has enabled unprecedented capabilities across domains, while simultaneously introducing critical vulnerabilities that can be maliciously exploited or cause unintended harm. Although multiple initiatives aim to govern AI-related risks, a comprehensive and systematic understanding of how AI systems are actively misused in practice remains limited. This paper presents a systematic review of AI misuse across modern AI technologies. We analyze documented incidents, attack mechanisms, and emerging threat vectors, drawing from existing AI risk repositories, prior taxonomies, and empirical case reports. These sources are synthesized into a unified analytical framework that categorizes AI misuse across nine primary domains. Our analysis identifies nine major domains of AI misuse: (1) Adversarial Threats, (2) Privacy Violations, (3) Disinformation, Deception, and Propaganda, (4) Bias and Discrimination, (5) System Safety and Reliability Failures, (6) Socioeconomic Exploitation and Inequality, (7) Environmental and Ecological Misuse, (8) Autonomy and Weaponization, and (9) Human Interaction and Psychological Harm. Within each domain, we examine distinct misuse patterns, providing technical insights into exploitation mechanisms, documented real-world cases with quantified impacts, and recent developments such as large language model vulnerabilities and multimodal attack vectors. We further evaluate existing mitigation strategies, including technical security frameworks (e.g., MITRE ATLAS, OWASP Top 10 for Large Language Models, MAESTRO), regulatory initiatives (e.g., EU AI Act, NIST AI Risk Management Framework), and compliance standards. The findings reveal substantial gaps between the rapid advancement of AI capabilities and the robustness of current defensive, governance, and mitigation mechanisms, with adversaries holding persistent advantages across most attack categories. This work contributes by (i) systematically consolidating fragmented AI risk repositories and misuse taxonomies, (ii) developing a unified taxonomy grounded in both theoretical models and empirical incident data, (iii) critically assessing the effectiveness of existing mitigation approaches, and (iv) identifying priority research gaps necessary for advancing more secure, ethical, and resilient AI systems.

This study aims to analyze the contribution of risk management and strategic control in enhancing the effectiveness of corporate governance in the general insurance industry. Strong corporate governance is a key prerequisite for addressing risk complexity, regulatory requirements, and the competitive dynamics of the insurance sector. This study adopts a qualitative approach using a systematic literature review and descriptive analysis of risk management frameworks, strategic control mechanisms, and corporate governance practices in general insurance companies. Data were obtained from secondary sources, including reputable international journal articles, industry regulations, and relevant corporate reports. The findings indicate that the integration of comprehensive risk management with effective strategic control strengthens oversight functions, improves the quality of strategic decision making, and promotes the implementation of transparency, accountability, and responsibility principles. These findings confirm that the synergy between risk management and strategic control plays a significant role in improving corporate governance quality and supporting the sustainability of general insurance companies’ performance.

The construction industry is central to the socio-economic and infrastructural advancement of developing countries; however, it continues to face persistent performance challenges, most notably recurrent cost overruns. While systematic cost risk management is recognized as a critical approach to improving project outcomes, its adoption across the industry remains limited. This study seeks to identify and rank the critical obstacles that hinder contractors from integrating systematic cost risk management into building construction projects. A comprehensive methodology was employed, including an in-depth literature review and three rounds of Delphi. The Relative Importance Index (RII) was used to evaluate the severity of the identified barriers, and Holm-corrected Spearman’s rank correlation analysis was applied to examine the relationships among them. The findings reveal that the most influential barriers include the absence of structured risk management frameworks within organizations, insufficient top management support, the lack of collaborative risk management mechanisms among stakeholders, limited technical knowledge and skills in risk management, and inadequate client support. The strong positive correlations among these barriers highlight their interdependent nature and underscore the systemic challenges facing contractors. This study contributes to the broader field of civil and structural engineering by providing evidence-based insights that can support the development of targeted strategies to enhance cost risk management practices in developing-country construction environments.

The rapid advancement of Artificial Intelligence (AI) has created a polarised public response, oscillating between utopian visions and existential fear. This analysis refutes these extremes, arguing that such anxiety is not a new phenomenon but a recurring historical cycle associated with the externalisation of human faculties. By examining historical precedents, the text reframes the AI challenge as a manageable variable rather than an uncontrollable force. The Socratic critique of writing, which warned of cognitive atrophy from externalised memory, is presented as an ancient parallel to modern concerns about AI fostering superficial competence. Similarly, the 19th-century Luddite movement is reinterpreted not as an irrational opposition to technology, but as a rational response by skilled artisans to the deskilling of their labour and the degradation of product quality-an analogue to fears that AI will devalue human expertise. Further parallels from the 20th-century "calculator wars" in education illustrate how curricula shifted from rote computation to higher-order problem-solving. These historical examples collectively argue that technological disruptions compel a redefinition of human competence and create new opportunities, rather than simply leading to cognitive or economic decline. Building on this historical perspective, the analysis proposes that the antidote to technological anxiety is a disciplined, managerial approach grounded in rigorous contingency planning. Through corporate case studies-contrasting Kodak’s strategic inertia with Fujifilm’s successful diversification, alongside the proactive pivots of Intel and Netflix-the text illustrates that organisational resilience depends on the ability to critically reassess core capabilities and cannibalise legacy models when necessary. This evidence informs a comprehensive, tiered risk management framework designed for professionals and institutions. "Plan A" focuses on Mitigation and Integration, advocating a "Centaur" model in which humans and AI collaborate as distinct but complementary agents, preserving human authority and using cognitive forcing functions to prevent automation complacency. "Plan B," a Contingency and Diversification strategy, involves developing multi-skilled, "M-shaped" professionals and cultivating an "analogue hedge" in roles requiring physical presence or legal accountability. Finally, "Plan C" outlines a strategy for Resilience and Sovereignty, serving as a last resort against systemic failure through the development of technological sovereignty via locally controlled AI and the willingness to execute a radical pivot to entirely new sectors. The overarching thesis is that by establishing these explicit contingency plans, organisations can transform existential risk into a manageable operational procedure, navigating the AI revolution with strategic preparedness rather than reactive panic.

ABSTRACT Urban areas are increasingly vulnerable to flooding due to rapid urbanization, inadequate stormwater infrastructure, and the intensifying impacts of climate change. To manage these challenges, reliable hydrological models are essential for mitigating the adverse impacts of hydrometeorological events. In data-scarce regions, the calibration of such models is hindered by limited field data. This study presents a practical methodology for calibrating a 1D–2D Stormwater Management Model (SWMM) for tropical urban catchments through a case study in Udon Thani City, Thailand. An iterative calibration process was applied to address major flooding identified in initial simulations, leading to improved runoff routing that ensured compliance with the 5-year, 1-h design storm of the system. The detailed one-factor-at-a-time (OAT) sensitivity analysis identified Curve Number (CN) and Imperviousness as the most influential parameters, followed by sub-catchment width and slope. The findings underscore the importance of prioritizing these parameters for calibration, particularly in regions with limited data availability. The proposed approach provides a scalable and transferable framework for flood risk assessment and management in similar tropical urban catchments globally. By integrating sensitivity analysis into the planning and optimization of green-grey infrastructure, the study contributes to the development of resilient and sustainable stormwater management strategies in vulnerable urban areas.

The rapid development of artificial intelligence (AI) has transformed the landscape of higher education, including State Islamic Higher Education in Indonesia, referred to in this study as Perguruan Tinggi Keagamaan Islam Negeri (PTKIN). In this context, this study examines PTKIN lecturers’ perceptions of AI development, their awareness of potential risks, and the strategies they employ for risk mitigation. This study is significant as it also explores whether Islamic ethical principles are integrated or absent in these processes. Using a qualitative approach, data were collected through interviews and document analysis, including institutional guidelines and academic integrity policies, involving lecturers from diverse disciplinary backgrounds at two PTKINs. The findings reveal two main orientations in AI risk management. Some lecturers emphasize technical controls such as plagiarism detection, supervised examinations, and accuracy assurance, while others highlight ethical guidance, verification, and the cultivation of critical awareness. Despite these efforts, Islamic values, although frequently mentioned, remain declarative and have not yet been institutionalized into formal university governance structures. By reinterpreting the COSO Enterprise Risk Management (ERM) framework through the lens of maqāṣid al-sharīʿah, this study proposes an integrative model that connects technical risk mitigation with Islamic normativity. The study concludes that PTKIN has the potential to pioneer an Islamic framework for AI ethics and governance that aligns technological innovation with moral accountability and contributes to the broader transformation of Islamic education in the digital era.

Collapses represent a major geological threat in China's mountainous regions, which cover 65% of its land area. Accurate susceptibility assessment is crucial, yet human engineering impacts in peri-urban mountains remains poorly quantified. This study develops an interpretable Random Forest model for collapse susceptibility in Changping District, Beijing. A spatial database included ten factors, including topography, geology, environment, and human activity. The model identified DTRO as the most critical factor, contributing 29.54% of total importance. This underscores the dominant role of human engineering activities. NDVI (20.38%), DTR (10.44%), and ELV (8.65%) were also key contributors. The top four factors contributed to 69.01% of total predictive importance. The optimized model achieved outstanding performance, with an AUC of 0.981 and accuracy of 0.9315. Spatial validation confirmed reliability, as 98.01% of collapses fall within the ʻhigh’ and ʻvery high’ susceptibility zones, covering just 17.3% of the study area. The susceptibility map reveals a distinct linear pattern of high-risk zones along roads and river valleys. This demonstrates that human factors can surpass natural factors in controlling collapse distribution in developed mountainous regions. This model provides an actionable tool for risk management and transferable framework for similar regions globally.

This study assessed the factors affecting the implementation of government-funded projects at the Tanzania Broadcasting Corporation (TBC), focusing on three key determinants: risk management, stakeholder involvement, and resource management. Specifically, the study examined how effective risk identification and mitigation, inclusive stakeholder participation, and efficient resource allocation influence the success of project implementation. A descriptive research design with a quantitative approach was adopted under a positivist research philosophy. Data were collected via structured questionnaires administered to 119 TBC officials, including engineers, technicians, procurement officers, ICT officers, accountants, and line managers. Stratified random sampling ensured representation across departments. Data were analysed in IBM SPSS version 27.1.0 using descriptive and inferential statistics. Descriptive analysis reported means, standard deviations, skewness, and kurtosis, while multiple regression tested relationships between variables. The findings show that risk management significantly enhanced project implementation by reducing uncertainty and improving decision-making. Stakeholder involvement strengthened transparency, accountability, and collaboration, thereby improving communication and project ownership. Resource management had the greatest impact, as effective allocation, utilisation, and monitoring of resources directly improved project efficiency and performance. The study concludes that strengthening risk management frameworks, fostering inclusive stakeholder participation, and ensuring prudent resource utilisation are essential to improving the effectiveness and sustainability of government- funded projects. It recommends that TBC and relevant ministries, including the Ministry of Finance and Planning, enhance capacity building, monitoring systems, and interdepartmental coordination. The study contributes empirical evidence to the public project management literature and offers policy insights to improve accountability and performance in government-funded projects in Tanzania.

Framework for real-time multimodal container transport risk management

Environmental and health risk assessment of radon in Capodifiume Lake: Investigating elevated radon levels in a karst aquifer system.

Open banking reshapes the financial sector by enabling regulated third-party providers to access bank data through APIs, fostering innovation but amplifying operational and financial-crime risks due to increased ecosystem interdependence. To address these challenges, this study proposes an integrated risk-management framework combining System Dynamics, Agent-Based Modelling, and Monte Carlo simulation. This hybrid approach captures feedback effects, heterogeneous agent behaviour, and loss uncertainty within a simulated PSD2-style environment. Simulation experiments, particularly those modelling credential-stuffing waves, demonstrate that stricter onboarding thresholds, tighter API rate limits, and enhanced anomaly detection reduce operational tail losses by approximately 20-30% relative to baseline scenarios. Beyond these specific findings, the proposed framework exhibits significant universality; its modular design facilitates adaptation to broader contexts, including cross-border regulatory variations or emerging BigTech interactions. Ultimately, this multi-method approach translates complex open-banking dynamics into actionable risk metrics, providing a robust basis for targeted resource allocation and supervisory stress testing in evolving financial ecosystems.

LNG serves as a pivotal element within integrated energy systems, especially in coastal regions where the implementation of a stable and reliable LNG cold energy power generation system significantly elevates energy efficiency. This system can effectively meet concurrent demands for cold energy utilization and electricity supply while contributing to the mitigation of carbon emissions. However, the inherent complexity of the system coupled with the scarcity of historical operational data for the novel dual-Rankine cycle process renders conventional reliability assessment methodologies inadequate. This study proposes an integrated framework utilizing fuzzy Bayesian methods to address data scarcity during the early stages of equipment deployment. A hierarchical risk factor model, incorporating process decomposition, expert evaluations, and triangular fuzzy numbers, is developed to quantify uncertainties in failure probabilities. The Bayesian network models the causal relationships among equipment failure factors, allowing for the inference of overall system reliability from individual equipment performance. Through a case study of a LNG terminal in Zhoushan, this approach integrates sensitivity analysis with forward-backward reasoning methodologies to rigorously evaluate and quantify system reliability under operational conditions. The results show that under high load conditions within the 1000 h prior to overhaul, following long-term accumulated operation, the probability of complete system shutdown in the power generation system is 3.30%, while the probability of the LNG cold energy power generation system failing to operate fully due to aging-related faults is 8.24%, demonstrating the system’s strong reliability under extreme conditions. Critical risks identified through backward inference include the seawater pump SWP1, with a posterior failure probability of 59.92% during complete shutdown, and the propane-side pump SWP3, with a posterior failure probability of 32.29% when the cold energy power generation system can only operate in a single-cycle mode. This study provides an advanced methodological framework for risk management in newly constructed LNG cold energy power generation systems, playing a crucial role in promoting sustainable, low-carbon technologies in the energy sector.

This study examined the impact of excluded risks on the cost and schedule performance of construction projects in Samarra, a city affected by persistent security-related challenges. A quantitative research approach was adopted using a structured questionnaire distributed to 49 engineers and construction experts from different engineering disciplines. The collected data were analyzed using the Relative Importance Index (RII) to evaluate excluded risks in terms of likelihood of occurrence, impact on project cost, and impact on project duration. The results indicated that security-related risks, particularly those associated with war conditions and civil disturbances, were perceived as the most critical, with RII values exceeding 0.70 in several cases. In contrast, risks related to partial occupation of projects by the employer, contract-driven design constraints, and nuclear-related considerations were assessed as less significant, with RII values generally below 0.50. The findings also showed that contracts incorporating proactive risk mitigation measures were perceived as more effective in reducing cost overruns and schedule delays than traditional insurance-based risk allocation approaches. The study concluded that improving construction project performance in security-dominant environments requires preventive contractual strategies, locally adapted risk management frameworks, and continuous professional training for engineers and contractors.