Operational Risk Research Articles

The Effectiveness of Operational Residual Risk Assessment: The Case of General Aviation Organizations in Enhancing Flight Safety in Alignment with Sustainability

Operational risk management (ORM) is crucial for every aviation organization. The assessment of operational risk (OR) is a critical area of study, as organizations must continuously evaluate and mitigate potential risks to maintain high levels of performance and safety. The motivation for writing this paper was to address the cognitive gap identified through literature analysis. The aim of this paper is to assess the effectiveness of operational residual risk assessment in general aviation (GA) organizations, with a specific focus on its role within the decision-making process to enhance flight safety in line with sustainability. By addressing a cognitive gap identified in the literature, this study seeks to determine whether current risk management practices adequately assess and mitigate residual risks, especially in organizations where operational risk is inherently high. Based on a literature review, the authors present adopted concepts of ORM and OR. The survey methodology involved a questionnaire on OR assessment, consisting of 32 questions completed by respondents twice—before and after 63 series of flights. The survey was carried out across two groups with significantly varying levels of flying experience (students and instructor pilots), with a particular focus on the influence of human factors. The conclusions are based on a comparative analysis of the difference in the results obtained after and before the series of flights in both surveyed groups. The survey was conducted in three selected general aviation organizations in Poland using nonprobability convenience sampling. The results demonstrate an overall significant underestimation of OR in both student and instructor groups. Therefore, it can be concluded that operational risk assessment in the selected organizations was not sufficiently effective. Additionally, it was shown that staff experience affected the effectiveness of OR assessment. Moreover, this study identified specific aspects of operational risk that were most underestimated. By addressing the cognitive gap, this study enhances both the theoretical and practical understanding of residual risk management, particularly in relation to safety and efficient resource use in aviation. It also offers the Operational Residual Risk Underestimation Index (ORRUI) as an actionable parameter developed to quantify and standardize the level of underestimation of operational residual risks in civil aviation.

Does Supply Chain Transaction Volatility Affect Corporate Sustainability? Evidence from Corporate Tax Burden

The tax burden significantly influences corporate sustainability, making the study of the impact of supply chain transaction volatility on corporate tax burden crucial for alleviating tax pressures and promoting healthy corporate development. Using a sample of A-share listed companies in China from 2013 to 2019, we find the following: (1) Overall, supplier transaction volatility significantly increases corporate tax burden, while customer transaction volatility does not have an effect, a finding that remains robust under various tests for endogeneity. (2) Mechanism analysis reveals that supplier transaction volatility raises the level of corporate tax burden by increasing operational risk and relationship maintenance costs. (3) Further analysis indicates that the volatility of major supplier transactions exacerbates corporate income tax burdens, while the impact of customer transaction fluctuations on the tax burden is more pronounced for non-state-owned enterprises, and state-owned enterprises experience a suppressive effect on value-added tax from customer transaction volatility. This study clarifies the tax burden dynamics among supply chain firms, expands the literature on the determinants of corporate tax burdens and the economic consequences of transaction volatility, and provides insights for promoting corporate sustainability.

Operational Risk Assessment Tool for Evaluating Leishmania infantum Introduction and Establishment in the United States through Dog Importation1.

International pet travel and commercial operations have increased animal disease importation risks, including for Leishmania infantum, a deadly parasite of humans and domestic dogs. Collaborating as an interdisciplinary working group, we developed an operational tool for veterinary and public health practitioners to assess and manage L. infantum risk in dogs imported to the United States. Overall risk varies by dog, human, and geographic factors but could be high without proper controls. We determined dog risk management strategies should include application of sand fly insecticides and repellents, sterilization, and treatment. US public health authorities can use a One Health approach to manage L. infantum importation risks via infected dogs.

Strategic risk management in outsourced business processes: Navigating geopolitical and cybersecurity challenges

Outsourcing has become increasingly important for organizations around the world because the practice offers optimization opportunities for the organizations. However, the increase in the magnitude of outsourcing has brought new complex hazards that need organizations to be aware and ready to tackle. The hazards include operational disruptions due to data breaches and harm to brands. This research was aimed at comprehending the strategic risk management within the realm of outsourced processes with the intention of geopolitical and cybersecurity obstacles. The study sought to establish a framework that will help organizations to improve their risk management practices within the context of outsourcing. The study employed qualitative and quantitative methods to examine the operational, financial, geopolitical, and cybersecurity hazards of outsourcing. The qualitative component included in-depth interviews with key stakeholders in outsourcing and the quantitative component included surveys. The thematic analysis and inferential statistics indicated a strong association between geopolitical factors, cybersecurity threats, and strategic risk management. The recommends an inclusion of the geopolitical risk assessment as an integral part of strategic planning in the outsourcing practice. Also, the study recommends enhancement of cybersecurity processes to avert financial and operational risk.

Advancing process safety management systems in the oil and gas industry: Strategies for risk mitigation

Process Safety Management (PSM) is critical for mitigating operational risks and enhancing worker safety in the oil and gas industry. This paper explores the essential components of PSM systems, such as hazard analysis, incident investigation, and management of change, highlighting the role of safety culture, leadership, and accountability. Key challenges in implementing effective PSM, including aging infrastructure and compliance issues, and lessons learned from industry incidents are examined. The paper presents strategies for improving risk mitigation through advanced technologies like digital tools, predictive maintenance, real-time monitoring, and continuous workforce training and engagement. The findings underscore the need for a balanced approach that integrates human oversight with technology to ensure more effective risk management. Recommendations include further investments in digital transformation, stronger leadership commitment to safety, and collaborative efforts with regulatory bodies to improve industry standards. The oil and gas sector can significantly reduce risks and improve operational safety by adopting these strategies.

Graph neural networks for power grid operational risk assessment under evolving unit commitment

This article investigates the ability of graph neural networks (GNNs) to identify risky conditions in a power grid over the subsequent few hours, without explicit, high-resolution information regarding future generator on/off status or power dispatch decisions. The GNNs are trained using supervised learning to predict the power grid’s aggregated bus-level (either zonal or system-level) or individual branch-level state under different power supply and demand conditions. The variability of the stochastic grid variables (wind/solar generation and load demand), and their statistical correlations, are considered while generating the inputs for the training data. The outputs in the training data include system-level, zonal and transmission line-level quantities of interest (QoIs). The ground truth of QoIs are obtained by numerically solving deterministic optimization problems (e.g., security-constrained unit commitment) with the same inputs. The GNN predictions are used to conduct hours-ahead, sampling-based reliability and risk assessment w.r.t. zonal and system-level (load shedding) as well as branch-level (overloading) failure events. The proposed methodology is demonstrated for three synthetic grids with sizes ranging from 118 to 2848 buses. Our results demonstrate that GNNs are capable of providing fast and accurate prediction of QoIs and can be good proxies for computationally expensive optimization algorithms. The excellent accuracy of GNN-based reliability and risk assessment suggests that GNN models can substantially improve situational awareness by enabling quick, high-resolution reliability and risk estimation.

Integrating AI in financial risk management: Evaluating the effects of machine learning algorithms on predictive accuracy and regulatory compliance

This research focuses on adopting ML models in risk management and how such factors influence predictive abilities and compliance with relevant rules. With more financial institutions using some of these advanced AI technologies in their decision-making capacities, a clear understanding of their effectiveness and what legal compliance would mean for their growth becomes vital. This research presents a comprehensive literature review of traditional risk management methods compared to the newer, AI-based methodologies by meticulously evaluating difficult standard measurements, including accuracy, precision, and recall. Further, the research analyses the compliance risks that arise with AI, especially concerning significant regulations such as Basel III and GDPR, which are essential in preserving financial stability and customer confidence. The study shows that applying AI approaches enhances predictive efficiency to a very high degree and the pressing and major legal concerns that institutions face. Moreover, the studies reveal the beneficial sectors for applying machine learning for operational risk management and provide guidelines for employing AI. To improve and strengthen risk management approaches and guarantee strict compliance with current and future implementing regulations, this study offers pertinent information to current discourses regarding the future of finance within the rising context of technological advancements.

THE role of Artificial Intelligence in industry 5.0: Enhancing human-machine collaboration

The emergence of Industry 5.0 marks a transformative shift in the manufacturing landscape, emphasizing a synergistic relationship between humans and machines. This paper explores the pivotal role of Artificial Intelligence (AI) in enhancing human-machine collaboration within this paradigm. By leveraging AI technologies, industries can foster a more personalized, efficient, and innovative work environment. AI systems facilitate seamless communication and decision-making processes, thereby augmenting human capabilities rather than replacing them. This collaboration allows for the optimization of workflows, reduction of operational risks, and enhancement of product quality through advanced predictive analytics and real-time data processing. Furthermore, the integration of AI in Industry 5.0 supports sustainability initiatives by minimizing waste and energy consumption, aligning with the global push for greener manufacturing practices. Case studies demonstrate the successful implementation of AI-driven solutions across various sectors, showcasing improvements in productivity and employee satisfaction. As Industry 5.0 continues to evolve, the interplay between AI and human labour will redefine traditional roles, empowering workers with augmented intelligence tools. The findings indicate that embracing AI not only enhances operational efficiency but also contributes to a more resilient and adaptive workforce. Ultimately, this paper posits that the future of industry lies in the harmonious collaboration between human intellect and artificial intelligence, which together will drive innovation, productivity, and sustainable practices in the manufacturing sector.

Global HSE regulatory frameworks and their impact on operational efficiency in the energy sector

The global energy sector operates within a complex regulatory environment shaped by Health, Safety, and Environmental (HSE) frameworks that aim to protect both human health and the environment while enhancing operational efficiency. This study examines the key HSE regulatory frameworks implemented across various regions and their impact on operational practices in the energy sector. By analyzing regulations such as the European Union’s REACH (Registration, Evaluation, Authorisation, and Restriction of Chemicals) and the United States' OSHA (Occupational Safety and Health Administration) standards, alongside other national and international policies, the paper identifies the critical aspects of HSE regulations and their influence on risk management, safety protocols, environmental sustainability, and business performance. The findings highlight that while stringent HSE regulations contribute to reducing operational risks and enhancing corporate social responsibility, they may also increase compliance costs and operational complexities. The paper argues that a well-structured HSE framework can lead to improved long-term operational efficiency by reducing accidents, optimizing resource utilization, and enhancing sustainability practices. However, the balance between compliance and cost-effectiveness remains a significant challenge for energy companies operating in diverse regulatory environments. Recommendations are provided for harmonizing regulations and fostering innovation in compliance strategies to support sustainable development and enhanced operational efficiency.

Conceptualizing agile business practices for enhancing SME resilience to economic shocks

This paper examines the role of agile business practices in fortifying small and medium-sized enterprises (SMEs) against economic shocks, emphasizing resilience as a critical factor for sustainable growth. Given SMEs' vulnerability to unpredictable economic shifts, the study explores how agility — defined by rapid adaptation, flexibility, and innovation — enables these enterprises to navigate and recover from disruptions effectively. Through a review of resilience-building frameworks, the paper identifies core agile practices, such as adaptive decision-making, lean management, and iterative product development, as pivotal to enhancing SMEs' operational and strategic resilience. Findings indicate that SMEs leveraging agile methodologies experience improved responsiveness to market changes, reduced operational risks, and greater capacity to maintain continuity during crises. Additionally, the study discusses the integration of digital tools, cross-functional teams, and customer-centric approaches as enablers of agility that strengthen resilience. Conclusions underscore the necessity for SMEs to adopt agile frameworks not only as a response mechanism but also as a proactive strategy for long-term stability and competitiveness in volatile markets. This research contributes to the growing discourse on SME resilience, offering actionable insights for stakeholders seeking to embed agility as a fundamental attribute in organizational practices.

Vibration and pressure pulsation elimination in a reciprocating compressor suction system using an acoustic filter

High vibration poses significant safety and operational risks to compressor components. This study presents a thorough investigation of the root causes analysis and corrective actions to resolve vibration-induced failures faced on the suction system of a reciprocating compressor. Excessive pressure pulsations in the suction bottle and strong mechanical coupling between the cylinders and suction bottle due to high cylinder gas forces were identified as the root causes of vibration-induced failure of the suction system. The proposed solutions to eliminate this problem were implemented by splitting the suction bottle into two parts and making one bottle as an acoustic filter (Helmholtz resonator). The acoustic filter was optimized for the suppression of pressure pulsations above its Helmholtz frequency and also for the avoidance of acoustic and mechanical resonance. After applying the proposed solutions, the modified suction system achieved a 14.3-61.1% reduction in vibration and a 75.56% reduction in peak-to-peak pressure pulsation for the compressor operating at 1000 rpm. The processing capacity of the compressor has been increased by 6.82%. An acoustic filter is an effective low-cost technical measure for reduction of pressure pulsation and fluid-induced vibration, which greatly increases the reliability of the entire compressor system.

Analisis Faktor Yang Mempengaruhi Keselamatan Operasional Kapal di Pelabuhan Merak

The study, titled "Analysis of Factors Affecting Safety at Merak Port," aims to identify and analyze key factors influencing operational safety at Merak Port. This port is a strategic route linking Java and Sumatra, serving millions of passengers and vehicles annually. However, high activity levels and operational complexity present significant safety challenges. This research employs a qualitative case study approach, combining interviews, field observations, and document analysis. Quantitative data were also collected via questionnaires distributed to operators, workers, and passengers. Findings reveal that human factors, weather conditions, and infrastructure are critical to safety. Incidents in 2023, such as the KMP Royce 1 fire and a crane accident, underscore the need for enhanced risk management and infrastructure maintenance. The study concludes that gaps in safety training and compliance with safety procedures are key challenges. Additionally, extreme weather and suboptimal heavy equipment conditions increase operational risks. Recommendations include improving safety management practices, enhancing infrastructure maintenance, and providing regular training for workers to strengthen operational safety at Merak Port.

Corporate Risk Disclosure Practice and Financial Performance of Listed Industrial Goods Firms in Nigeria

In recent years, corporate risk disclosure has gained increasing attention in corporate governance discourse due to its potential impact on financial performance. The need for transparency in reporting risks has become more critical, particularly in the industrial goods sector, which is often characterized by high operational and financial risks. This study examined the influence of corporate risk disclosure on the financial performance of listed industrial goods firms in Nigeria, a sector known for high levels of operational and financial risk. It specifically assessed how financial and operational risk disclosures affect financial performance. This study employed expo-facto research design. The study population consisted of 13 industrial goods firms listed on the Nigerian Exchange Group (NGX) as of 31st December 2023. Census sampling was applied to include the entire population. Data were collected from annual reports and corporate governance disclosures were analysed with descriptive statistics and feasible generalised least squares regression analysis. The findings found that while financial risk disclosure positively and significantly influences financial performance, operational risk disclosure has a negative but significant effect. These outcomes suggest that financial transparency boosts investor trust and confidence, enhancing financial performance, whereas disclosing operational risks may reduce investor confidence due to concerns about operational stability and profitability. This study concluded that corporate risk disclosure demonstrated a significant role in influencing financial outcomes, yet its effect varies based on the type of risk disclosed. In line with empirical findings of this study, it was recommended that firms should balance transparency with discretion by selectively disclosing operational risks that have been mitigated or managed, reducing the potential for investor concerns over operational vulnerabilities.

Impact of Geographic Location on Risks of Fintech as a Representative of Financial Institutions

The activities of contemporary financial institutions require significant geographic expansion. Even the increased level of industry digitalisation does not minimise the importance of the physical assets of financial institutions. The environmental factors specific to each geographic region can significantly influence the efficiency of operations of financial institutions. The goal of the article is to determine the impact of the geographic location of physical assets via environmental risks affecting the other risks of fintech as a representative of financial institutions. The impact is determined by the employment of the PLS-SEM model implemented in SmartPLS 4.0 software. The model determines the impact of environmental risks on governance risks, operational risks, human resources and safety risks, ICT risks, compliance risks, and strategic risks. These groups of risks form the latent variables, which comprise the experts’ estimation of threats and vulnerabilities impacts and their likelihoods. After testing five hypotheses, two of them were supported—environmental risks impact human resources safety risks and operational risks.

Country risk mapping in a changing world—comparative survey on academic research and industrial practices

AbstractIn an era marked by rapid geopolitical shifts, persistent pandemics, and escalating climate threats, the imperative to transcend traditional country risk mapping methodologies has never been more critical. This study embarks on a comprehensive examination of the efficiency of current academic and industrial approaches to mapping the multifaceted country risks. By proposing a structured risk mapping framework that incorporates seven pivotal risk categories as Political Risk, Institutional Risk, War and Armed Conflict Risk, Public Security Risk, Socioeconomic Risk, Ecological Threat Risk, and Infrastructure Risk, the research seeks to foster a more nuanced understanding of how different organizations assess and prioritize these risk factors. Employing a dual approach that includes a thorough literature review and an extensive industry survey, and a detailed analysis of each of the seven risk category by juxtaposing relevant academic insights with industry practices, this study examines the discrepancies between academic theories and practical applications in country risk mapping. It reveals underestimate country risk factors, inadequate risk categorization granularity, inconsistencies in risk prioritization, terminological mismatches, and a need for a more integrated and holistic approach to country risk mapping. The paper concludes by proposing future research directions that aim to refine country risk mapping methodologies. It advocates a forward-looking perspective that adequately addresses the complexity and inter-connectivity of global operational risks.

Quantitative Detection Method for Surface Angled Cracks Based on Laser Ultrasonic Full-Field Scanning Data

Surface angled cracks on critical components in high-speed machinery can lead to fractures under stress and pressure, posing a significant threat to the operational safety of equipment. To detect surface angled cracks on critical components, this paper proposes a “Quantitative Detection Method for Surface Angled Cracks Based on Full-field Scanning Data.” By analyzing different ultrasonic signals in the full-field scanning data from laser ultrasonics, the width, angle, and length of surface angled cracks can be determined. This study investigates the propagation behavior of ultrasonic waves and their interaction with surface angled cracks through theoretical calculations. The crack width is solved by analyzing the distribution of Rayleigh waves in the full-field scanning data. This paper also discusses the differences in ultrasonic wave propagation between near-field and far-field detection and identifies the critical point between these regions. Different computational methods are employed to calculate the inclination angle and the crack endpoint at various scan positions. Four sets of experiments were conducted to validate the proposed method, with results showing that the errors in determining the width, angle, and length of the surface angled cracks were all within 5%. This confirms the feasibility of the method for detecting surface angled cracks. The quantitative detection of surface angled cracks on critical components using this method allows for a comprehensive assessment of the component’s condition, aiding in the prediction of service life and the mitigation of operational risks. This method shows promising application potential in areas such as aircraft engine blade inspection and gear inspection.

Evaluating the Role of ISO Standards in Enhancing the Performance of Medical Laboratories

The role of ISO standards in enhancing the performance of medical laboratories has become increasingly significant in ensuring quality and reliability in healthcare services. This review evaluates the impact of ISO standards, particularly ISO 15189, on the operational efficiency, diagnostic accuracy, and risk management of medical laboratories. It highlights the key components of these standards, including quality management systems, personnel competence, and continuous improvement, and examines their contributions to patient safety and institutional credibility. The article also explores the challenges of implementing ISO standards, such as financial constraints and resistance to change, and proposes strategies to overcome these barriers. The findings underscore the importance of ISO standards in promoting a culture of quality and innovation within medical laboratories, ultimately improving healthcare outcomes.

A Roadmap to Systematic Review: Evaluating the Role of Data Networks and Application Programming Interfaces in Enhancing Operational Efficiency in Small and Medium Enterprises

The adoption of Data Networks and Application Programming Interfaces (APIs) has become crucial for small and medium enterprises (SMEs) to streamline operations, improve efficiency, and reduce costs. However, SMEs often face challenges such as resource limitations and security vulnerabilities, which hinder their ability to fully leverage these technologies. This systematic review examines the role of Data Networks and APIs in enhancing operational efficiency within SMEs, focusing on key metrics such as speed, cost reduction, scalability, and security challenges. Following PRISMA 2020 guidelines, we conducted a systematic search across multiple databases including Web of Science, Scopus, IEEE Xplore, and Google Scholar. Studies published between 2014 and 2024, focused on SMEs, and addressing the role of Data Networks and APIs in operational efficiency were included. A total of 49 studies met the inclusion criteria and were analyzed for key outcomes related to operational efficiency, cost-effectiveness, and security risks. The review found that Data Networks and APIs significantly improve operational efficiency by increasing process speed (12% increase), reducing operational costs (8% reduction), and enhancing overall productivity. However, security challenges, particularly related to API vulnerabilities, were a major concern, with cyberattacks on APIs increasing by 400% in Q1 2023 alone. Despite these risks, the benefits of implementing Data Networks and APIs in SMEs, particularly in terms of scalability and real-time data processing, were evident across industries. Data Networks and APIs offer substantial improvements in operational efficiency for SMEs, although security remains a significant challenge. Future efforts should focus on developing security frameworks tailored to SMEs while maintaining the operational benefits of these technologies. Further research is needed to explore scalable and secure API models for SMEs.

Application of Mind Map and TRIZ to an Advanced Air Mobility System for Post-Disaster Response

In this article, an Advanced Air Mobility (AAM) platform focused on search and rescue applications is discussed and analyzed from a systems thinking perspective. By applying two systems thinking tools, namely Mind Map and TRIZ, the strong interactions within the constituent parts that make up the system’s whole are examined with the aim of providing a comprehensive roadmap for a proposed Advanced Air Mobility Post-Disaster Response (AAMPDR) system. Furthermore, two problems are discussed to demonstrate the application of the TRIZ technique. The first is in regards to a clause in the AGL rule that could present operational risks to the AAM’s airframe, while the second relates to a potential conflict ensuing from the advent of the 5G C-band and its effect on the AAM altimetry. The resulting solutions to resolve these conflicts using this same technique are also discussed, firstly by taking into account the mean sea/water level as a reference for vertical height within the provisions of the Federal Aviation Regulation requirements, and secondly by applying segmentation of the mission profile as well as a multi-stage frequency designation for each segment depending on a threshold vertical distance. Finally, this study demonstrated that Mind Map and TRIZ can be effective techniques in the early stages of conceptual model development for an AAM system applied to post–disaster response. Furthermore, that the contradictions tool of TRIZ can also be utilized in resolving those potential conflicts identified in relation to the system of interest. To this end, this paper proposes the amendment of the current Part 107 rule to include the term Above Mean Sea (or Water) Level (AMS/WL), a critical yet missing piece of the system requirements that engineers should take into account in future AAM system designs.

Design and Visual Implementation of a Regional Energy Risk Superposition Model for Oil Tank Farms

Ensuring the safety of oil tank farms is essential to maintaining energy security and minimizing the impact of potential accidents. This paper develops a quantitative regional risk model designed to assess both individual and societal risks in oil tank farms, with particular attention to energy-related risks such as leaks, fires, and explosions. The model integrates factors like day–night operational variations, weather conditions, and risk superposition to provide a comprehensive and accurate evaluation of regional risks. By considering the cumulative effects of multiple hazards, including those tied to energy dynamics, and the stability and validity of the model are researched through Monte Carlo simulations and case application. The results show that the model enhances the reliability of traditional risk assessment methods, making it more applicable to oil tank farm safety concerns. Furthermore, this study introduces a practical tool that simplifies the risk assessment process, allowing operators and decision-makers to evaluate risks without requiring in-depth technical expertise. The methodology improves the ability to safeguard oil tank farms, ensuring the stability of energy supply chains and contributing to broader energy security efforts. This study provides a valuable method for researchers and engineers seeking to enhance regional risk calculation efficiency, with a specific focus on energy risks.