Hasil untuk "Risk in industry. Risk management"

David Olanrewaju Olutimehin, Onyeka Chrisanctus Ofodile, Irunna Ejibe et al.

The review delves into the pivotal role of technology in revolutionizing supply chain risk management practices within the logistics sector. The paper explores the myriad of risks faced by modern supply chains, ranging from natural disasters and geopolitical tensions to cyber threats and disruptions in global trade patterns. It investigates how technological innovations such as blockchain, Internet of Things (IoT), artificial intelligence (AI), and predictive analytics are reshaping traditional risk management approaches by providing real-time visibility, data-driven insights, and proactive mitigation strategies. Through a comprehensive analysis, the study examines the transformative potential of these technologies in enhancing supply chain resilience, agility, and responsiveness to unforeseen disruptions. It highlights the benefits of leveraging blockchain technology for secure and transparent supply chain transactions, IoT sensors for real-time monitoring of goods in transit, AI algorithms for predictive risk modeling, and predictive analytics for identifying and mitigating potential disruptions before they escalate. Furthermore, the paper delves into the challenges and complexities associated with adopting and integrating these technologies into existing supply chain processes, including interoperability issues, data privacy concerns, and the need for specialized expertise. By providing practical insights, case studies, and best practices, the study aims to empower logistics professionals, policymakers, and industry stakeholders to harness the full potential of technology-driven solutions in managing supply chain risks effectively and ensuring business continuity in an increasingly uncertain and volatile global environment. Keywords:  Technology, Supply Chain, Risk Management, Innovations, Challenges, Logistics.

Ibrahim Adedeji Adeniran, Angela Omozele Abhulimen, Anwuli Nkemchor Obiki-Osafiele et al.

Strategic risk management in financial institutions is a critical component for ensuring robust regulatory compliance and maintaining financial stability. This review explores the multifaceted nature of strategic risk management and its importance in the dynamic regulatory landscape of the financial sector. It delves into the fundamental components of risk management, including risk identification, assessment, mitigation, and monitoring, highlighting how these processes help institutions navigate the complexities of regulatory requirements. The discussion encompasses various types of risks faced by financial institutions, such as credit, market, operational, liquidity, and compliance risks, illustrating the need for comprehensive risk management frameworks. The review also reviews key regulatory frameworks, including Basel III, the Dodd-Frank Act, and guidelines from the European Banking Authority, emphasizing their impact on capital requirements, liquidity standards, and governance expectations. A robust risk management framework integrates compliance efforts with business strategy, ensuring that institutions are not only adhering to regulatory mandates but also aligning their risk appetite and tolerance with their strategic objectives. The role of technology, particularly in data analytics, real-time risk monitoring, and cybersecurity, is examined as a crucial enabler for effective risk management and compliance. Best practices for enhancing regulatory compliance are outlined, including continuous monitoring, regular audits, and scenario analysis. Challenges such as evolving regulations, financial product complexity, and globalization are addressed, with recommendations for adaptive strategies and industry collaboration. Through case studies, the review provides insights into successful risk management implementations and lessons learned from compliance failures. The review underscores the importance of strategic risk management in fortifying regulatory compliance and suggests future trends, such as advanced AI and machine learning, which could further revolutionize the approach to risk management in financial institutions. Keywords:  Strategic Risk, Financial Institution, Regulatory, Compliance

Michael Osinakachukwu Ezeh, Adindu Donatus Ogbu, Augusta Heavens Ikevuje et al.

The oil and gas trading sector is inherently volatile, influenced by geopolitical events, market dynamics, and regulatory changes. Effective risk management is crucial for mitigating these uncertainties and ensuring operational stability and profitability. This paper presents a comprehensive analysis of optimizing risk management in oil and gas trading, highlighting strategies, tools, and best practices to manage and mitigate risks. Risk management in oil and gas trading encompasses a broad spectrum of activities, including market risk, credit risk, operational risk, and compliance risk. To optimize risk management, firms must employ a multifaceted approach that integrates advanced analytics, robust risk assessment frameworks, and strategic decision-making processes. Key strategies include the use of financial instruments such as futures, options, and swaps to hedge against price volatility. These instruments enable traders to lock in prices and margins, thereby reducing exposure to market fluctuations. Advanced analytics and data-driven decision-making are essential components of effective risk management. By leveraging big data, machine learning, and artificial intelligence, traders can gain deeper insights into market trends, forecast price movements, and identify potential risks. Predictive analytics allows for proactive risk management, enabling firms to anticipate and respond to market changes swiftly. A comprehensive risk assessment framework is also critical. This involves regular monitoring and evaluation of risk exposure, stress testing, and scenario analysis. Such practices help identify vulnerabilities and ensure that risk mitigation measures are in place. Additionally, fostering a risk-aware culture within the organization is vital. This includes training and educating employees on risk management practices and encouraging transparent communication and reporting of risks. Compliance risk, driven by regulatory changes, is another significant aspect of risk management in oil and gas trading. Staying abreast of regulatory developments and ensuring compliance with international and local regulations is essential to avoid legal penalties and reputational damage. Implementing robust compliance programs and leveraging technology to monitor regulatory changes can help firms stay compliant. In conclusion, optimizing risk management in oil and gas trading requires a holistic approach that combines financial hedging, advanced analytics, comprehensive risk assessment, and compliance management. By adopting these strategies, firms can effectively mitigate risks, enhance decision-making, and achieve sustainable growth in a highly volatile industry. Keywords: Optimizing, Risk Management, Oil and Gas, Trading, Analysis.

Ahmad Kalateh Sadati, Zeinab Saboohi Golkar

Introduction Mining, one of humanity's oldest industries, has continuously evolved alongside technological advancements and plays a vital role in national economies. This sector not only supplies raw materials for various industries, but also creates both direct and indirect employment opportunities, serving as a source of wealth for diverse stakeholders, including corporations and governments. However, working in mines is often regarded as one of the most hazardous and demanding professions due to challenging occupational conditions. Factors like remoteness from residential areas, long shifts, and high-risk environments jeopardize the physical and mental health of workers, leading to accidents and occupational diseases. Additionally, issues like inadequate wages and a lack of welfare facilities exacerbate the psychological and social pressures faced by miners. Given these considerations, understanding the "meaning of work" is crucial for miners. This concept refers to how individuals interpret and perceive their occupational experiences, which can significantly influence their motivation, job satisfaction, and overall performance. Workers, who find meaning in their jobs, tend to be more motivated to adhere to safety protocols and engage in industrial development. In contrast, viewing work merely as a temporary source of income can diminish their commitment and focus. The objective of this research was to explore and analyze the meaning of mining from the perspective of coal miners in Tabas. This focus is particularly significant given the essential role of mining in the economy and culture of specific regions in Iran like Tabas. Gaining a deeper understanding of workers' viewpoints provides a solid foundation for improving human resource policies, enhancing safety measures, and ameliorating welfare conditions. Ultimately, these efforts aim to achieve sustainable development in the mining industry, contributing not only to an improved quality of life for workers, but also to more responsible and efficient practices across the entire sector.     Materials & Methods This qualitative research conducted in 2025 in Tabas City employed a descriptive phenomenological approach to explore the "meaning of mining" from the perspective of coal mine workers. Given its historical and strategic significance in mining, Tabas is regarded not merely as a geographical location, but as a "mining community", providing a rich context for this study. Sampling was executed using both snowball and purposive methods. Data were collected through in-depth interviews with 22 workers. While data saturation was reached by the 20th interview, two additional interviews were conducted to enhance the reliability of the findings. Throughout all interview stages, strict adherence to ethical considerations was maintained, including obtaining informed consent and ensuring the confidentiality of participants' information. For data analysis, we utilized Colaizzi’s (1978) 7-step method, which involved an initial reading of the data, extracting significant statements, formulating meanings, clustering themes, developing an exhaustive description, identifying the fundamental structure of the phenomenon, and final validation. The credibility of the study was bolstered through rich descriptions, peer debriefing, and member checking. This research aimed to address a gap in understanding the meaning of work in this specific region of Iran.   Discussion of Results & Conclusion This research employed a phenomenological approach to investigate the lived experiences of coal miners in Tabas, Iran, with a particular focus on the meaning they attributed to their work. The findings revealed that the miners’ lifeworld was characterized by routine, pervasive anxiety, and suffering, leading to a profound sense of injustice often met with fatalism due to a perceived lack of agency for change. Drawing on Heideggerian philosophy, the study suggested that mining transcended mere physical labor; it represented a deeply meaningful, distressing, and painful experience. This embodied experience began with the act of entering the mine, encompassing sensory perceptions of darkness, tactile sensations of stone, and auditory cues from tools, all intertwined with emotional responses, such as fear and anger, alongside a confrontation with inequitable socio-economic structures. Furthermore, the research highlighted a dimension of social meaninglessness as described by Schutz and Weber. This phenomenon arose from the convergence of harsh physical conditions, environmental hazards, and geographical and social marginalization. As a result, miners experienced isolation, a lack of social recognition, and social exclusion with their identities often reduced to that of manual laborers. Despite these considerable challenges, the study observed that miners demonstrated resilience by creating meaning—not necessarily derived from their work itself, but from a desire to transcend their current circumstances and aspire to a better future. Based on these findings, the research proposes several recommendations aimed at improving the miners’ conditions. These include: Conducting critical analyses of power dynamics and exploitation within the mining industry. Mandating the use of standard safety equipment and implementing robust inspection protocols. Ensuring fair wages and employment security through legal compliance and support funds. Establishing accessible mental health services and training for management to recognize psychological distress. Developing comprehensive training programs focused on professional skills, communication, problem-solving, stress management, and resilience-building. These interventions aim to address the multifaceted deprivations faced by miners and enhance their overall well-being.

Laura González-Poblete

The seasonal presence of Amoebic Gill Disease (AGD) in farmed Salmo salar was detected in preliminary samplings to characterize AGD in relation to other coinfections on the east coast of Chiloé Island. Histopathological and PCR analyses of gills revealed AGD and its etiological agent, Neoparamoeba perurans, in the Hueihue farm in March and April 2013. Therefore, to determine the spread of AGD in the Chilean salmon industry, data from the Passive Surveillance Program by SERNAPESCA were analyzed from 2013 to 2022. The reports of five farms with amebiasis in 2013 increased to 496 in 2022, but particularly, there was an explosive increase in the number of fish with other pathogens in their gills, due to Complex Gill Disease (CGD) sometimes concurrently occurring with AGD. The annual incidence of AGD ranged from 1 week to 37 weeks per farm as discontinuous outbreaks. Infected fish were almost all adults, with S. salar being the most affected species, with the largest production, but showing low correlations between production and the number of affected farms. Positive farms and production were reduced for Oncorhynchus kisutch, and it was almost zero in Oncorhynchus mykiss. More infected farms were identified in autumn and summer for both S. salar and O. kisutch. The impact of AGD is probably low in Chile, due to the focus on S. salar production and the continuous harvesting model. More AGD-infected farms were in insular locations compared to continental areas, more in Los Lagos rather than Aysén Region, but almost zero farms were in Magallanes. Risk factors and oceanographic characteristics that explain the occurrence of disease outbreaks are discussed, as well as gill surveillance in live fish and management methods.

Lorenza Saturnino, Elsa Pastor, Eulàlia Planas

Global greenhouse gas emissions are reaching unprecedented levels, driving a strong interest in decarbonization. Hydrogen, with applications in industry, transport, and power sectors, offers a CO2- free energy vector when produced renewably. However, the transition to hydrogen as a replacement for fossil fuels presents significant technical challenges including sustainable production and, crucially, safe operation, transportation and storage. Quantitative Risk Analysis (QRA) encompasses a comprehensive methodology to characterize risks widely used in risk management. Since risk depends on the probability and consequences of failure, accurately estimating consequences is essential for precise risk assessment. Various software tools assist in consequence analysis, and comparing those helps identify their strengths and limitations, improving risk management decisions. In this paper we present a benchmark analysis aimed at evaluating the capabilities of Phast and HyRAM+ software tools in modelling dispersion and fire incidents of gaseous hydrogen from losses of containment in pressurized tanks. Real-world experimental results have been used as a ground truth for comparing simulation outcomes, ensuring accurate and reliable assessments. Three different experimental studies (Ekoto et al., 2012, Han et al., 2014; Carboni et al., 2022;) were chosen to assess concentration levels of hydrogen clouds, and flame length and radiation exposure from horizontal hydrogen jet fires. Simulated experiments investigated storage pressures ranging from 60 to 400 bar, with release hole diameters spanning from 0.5 mm to 52.5 mm for large-scale hydrogen jets, defined here as flames exceeding 15 meters in length. A comparison of the results obtained for the dispersion assessment reveals that both software tools generally underestimate hydrogen concentrations, with Phast showing less pronounced underestimation than HyRAM+. On the other side, both software tools generally overpredict flame length, except for slight underpredictions in simulations with the smallest release diameter. For large-scale hydrogen jet fires, Phast tends to overpredict radiation, while HyRAM+ tends to underpredict it. In a QRA framework of hydrogen jets from pressurized tanks, this study suggests that using Phast is preferable due to its more accurate results. However, further validation of the software for large-scale jets is necessary.

Imran Ali, Ismail Golgeci, A. Arslan

Purpose Given the increasingly turbulent business landscape and unprecedented incidents (e.g. Covid-19), firms must achieve supply chain resilience (SCRes) as a dynamic capability to bounce back from adversities and ensure continuity of operations. The purpose of this study is to integrate the three interrelated [knowledge management, risk management culture (RMC) and resilience] but often separately discussed concepts to advance the understanding of their intertwined influence on SCRes in the agri-food supply chains. Design/methodology/approach This study uses a cross-sectional survey approach where quantitative data is collected from 349 participants from the Australian agri-food supply chains to test the proposed hypotheses. Findings Exposure to supply chain risks triggers the deployment of specific knowledge management practices in the agri-food supply chains. Further, the analysis on serial mediation suggests that firms’ knowledge management practices work sequentially (knowledge acquisition, assimilation and application) and develop a RMC to achieve SCRes amid supply chain risks. Practical implications The findings of this study inform practitioners and policymakers who seek to understand the key mechanisms that facilitate the development of SCRes when facing supply chain risks, particularly in the Australian agri-food supply chains. Social implications The growth of the food industry through more resilient food supply chains could ensure sustained food supply and more employment opportunities. Originality/value Using dynamic capability theory, the authors devise a novel empirical model that explicates how knowledge management practices and RMC instigate the dynamic capability of SCRes amid supply chain risks facing agri-food supply chains.

Chairani Chairani, S. Siregar

Purpose This study aims to examine the effect of enterprise risk management (ERM) on financial performance and firm value, as well as the moderating role of environmental, social and governance (ESG) performance. Design/methodology/approach The samples in this study are listed companies in the ASEAN 5 (Indonesia, Malaysia, Philippines, Singapore and Thailand) during the years 2014–2018, with total observations of 680 firm-years. Fixed effect panel data regressions were used to test the hypotheses. The data was collected from Financial Report, Annual Reports and Thomson Reuters. Findings The results show that ERM has a positive significant effect on financial performance and firm value. This paper also finds that ESG has a significant moderating role in increasing the effect of ERM on firm value. Further, this paper divides the samples into sensitive and non-sensitive industries and find a significant moderating role of ESG performance on firm performance for sensitive industries. Originality/value Extant studies have not empirically examined the moderating role of ESG on the effect of ERM on firm performance and firm value. The findings have important implications in suggesting that firms need to analyze various threats and opportunities related to and ESG risks in achieving competitive advantage.

E. Pacheco-Velázquez, Virginia Rodes-Paragarino, Alberto Marquez-Uribe

This study explores the transformative impact of Industry 4.0 on industrial operations, emphasizing the integration of advanced technologies like AI, IoT, and Big Data Analytics to enhance process optimization, automation, and connectivity. Despite its potential for efficiency, Industry 4.0 introduces significant complexities, challenging existing operational and decision-making frameworks. Addressing these challenges, the research investigates the role of simulation platforms in logistics, seeking to identify their critical attributes for effective complexity management. It highlights the need for innovative tools in system evaluation, performance measurement, and skill development, aiming to equip the workforce with essential Industry 4.0 competencies. Through qualitative insights from logistics experts, the study aims to offer practical recommendations for educators and industry professionals, contributing to the design and implementation of educational simulations that align with the intricate demands of Industry 4.0 logistics.This study employs a qualitative content analysis approach to develop an Industry 4.0-adapted logistics simulator, leveraging the Asteraceae framework for digital game co-design and pedagogical reflection. Data were collected from six industry and academia experts through semi-structured interviews, designed around the framework’s key steps to explore simulator design, decision-making, impact, and skill development. Utilizing convenience sampling, the research engaged participants with experience in educational logistics platforms and simulators. Interviews were conducted online, with ethical considerations including informed consent. Transcription used OpenAI’s API for accuracy, followed by manual review. The analysis combined qualitative content with frequency analysis, employing Atlas.ti software to identify and code key simulation features as informed by expert insights. This methodology underscores a comprehensive approach to understanding and innovating logistics education for Industry 4.0, aiming to equip learners with necessary competencies through targeted simulation tools.The study’s findings emphasize the critical role of simulation tools in Industry 4.0 logistics for risk mitigation, operational planning, and decision-making. Experts pointed out the significant benefits of simulations in providing safe spaces for experimentation, especially valuable for SMEs with limited access to advanced technologies. They advocated for simulators to incorporate current technological and e-commerce trends, suggesting a customizable business model based on diverse logistics requirements. Key insights included the necessity for adaptable simulation architectures to handle various operational variables, the importance of integrating multidisciplinary competencies like data analytics and strategic management, and the role of performance metrics in evaluating simulations and logistics operations. The analysis revealed essential features for an educational logistics simulator, highlighting the importance of operational knowledge, predictive analytics, and the need for a comprehensive tool that integrates technology, strategy, operations, and data analysis. This approach aims to equip users with the skills necessary for navigating the complexities of modern logistics, promoting a deep understanding of systems thinking and complex reasoning skills.The discussion centers on the essential requirement for a multidisciplinary approach in creating an educational logistics simulator for Industry 4.0, emphasizing the need for technological adaptability and operational efficiency. It highlights the importance of integrating advanced technologies and collaborative paradigms to enhance logistics operations and improve decision-making processes. The utility of simulation-based learning as a pedagogical tool is acknowledged, with an emphasis on its role in developing complex thinking and practical skills relevant to the digital transformation of the logistics sector. The discussion suggests that educational simulations are poised to play a pivotal role in preparing the workforce for Industry 4.0 challenges by bridging technological advancements and pedagogical strategies. However, it also points to the limitations of the current study, such as its sampling method and regional focus, and calls for future research to explore broader applications and the integration of comprehensive strategies to ensure the educational simulator’s effectiveness and relevance in a global context.

Osemeike Gloria, Eyieyien, Osemeike Gloria Eyieyien et al.

Effective stakeholder and risk management strategies are critical components for ensuring the success of large-scale international projects amidst diverse cultural, political, and economic landscapes. This paper examines strategic approaches that organizations employ to mitigate risks, foster stakeholder engagement, and achieve project objectives on a global scale. Large-scale international projects often face multifaceted challenges such as geopolitical uncertainties, cultural differences, regulatory complexities, and logistical hurdles. Successful management hinges on proactive identification and assessment of risks, coupled with robust mitigation strategies tailored to local and global contexts. Stakeholder management plays a pivotal role in navigating the complexities of international projects. It involves identifying key stakeholders, understanding their expectations and interests, and fostering open communication channels. Engaging stakeholders early and continuously throughout the project lifecycle enhances transparency, builds trust, and aligns project outcomes with stakeholder priorities. Risk management strategies for international projects encompass comprehensive risk assessment methodologies, scenario planning, and contingency planning. Organizations leverage advanced analytics, risk mitigation frameworks, and cross-functional collaboration to anticipate and mitigate potential disruptions. Flexibility and adaptability are crucial in adjusting strategies in response to evolving risks and external dynamics. Case studies highlight effective stakeholder and risk management practices across various industries and regions. Successful projects underscore the importance of local knowledge, strategic partnerships, and cultural sensitivity in navigating international landscapes. Organizations that prioritize stakeholder engagement and proactive risk mitigation not only enhance project resilience but also achieve sustainable outcomes that align with global business objectives. Looking ahead, the integration of technology-driven risk management tools, adoption of agile methodologies, and enhanced cross-cultural competence will continue to shape effective strategies for international project success. Embracing digital solutions and fostering a collaborative global mindset will enable organizations to navigate complexities, capitalize on opportunities, and drive successful outcomes in diverse international environments. In conclusion, effective stakeholder and risk management strategies are integral to achieving success in large-scale international projects. By prioritizing proactive risk mitigation, fostering stakeholder engagement, and embracing cultural diversity, organizations can navigate uncertainties and achieve sustainable success on a global scale.

Mujeeb Ur, Rehman Shaikh, Rafi Ullah et al.

This study explores the issue of preventing ransomware attacks using risk management and insurance techniques. Threats from ransomware, which compromise operations, data integrity, and financial stability, have emerged as a major concern for enterprises. The present status of ransomware attacks and their possible effects on organizations are first examined after which we analyse several strategies for reducing the dangers to cyber security posed by these threats. These include non-technical approaches such as conducting a risk assessment to identify areas of vulnerability, implementing a comprehensive cybersecurity policy, obtaining appropriate cybersecurity insurance coverage, and technical measures such as firewall protection, user education, and software vulnerability patching. Such tactics rely heavily on ransomware insurance, which provides monetary security and assistance for incident responses. The findings show that, while technological solutions are essential for efficient ransomware attack mitigation, they should be accompanied by strong insurance plans created to offer financial security in the event of an attack using static and dynamic analysis detection techniques. This article provides a thorough overview of the complexities of ransomware insurance strategies by synthesizing opinions from industry experts, legal viewpoints, and cybersecurity professionals. To reduce their exposure to potential crippling losses due to successful breaches, organizations must take proactive steps to defend themselves against the constantly evolving threat of ransomware by utilizing both technical and non-technical measures, including adequate cyber security insurance

Yaqoob Yusuf Abdulla, A. Al-Alawi

Financial risk management is evolving rapidly with the integration of machine learning techniques, which offer sophisticated tools for managing complex and interconnected financial systems. Its crucial role in risk identification, assessment, mitigation, and prediction accounts for its significance. This systematic literature review analyzes the utilization of machine learning in financial risk management across 15 scholarly papers. The papers were selected from reputable journals available on databases such as ScienceDirect and IEEE. Only papers published during the last five years were selected to ensure their relevance. The selected papers include various machine learning algorithms, such as neural networks, deep learning, and ensemble methods, applied to financial risks such as credit, market, liquidity, and systemic risks. The research uses multiple methodologies, including but not limited to quantitative, empirical, and computational modeling approaches. The findings of the comparative analysis reveal that machine learning techniques are more effective and adaptive than traditional statistical methods at managing intricate risk patterns across a range of financial risk domains. Additionally, there is a clear trend toward leveraging big data and advanced analytics to enhance financial risk management practices. Academics and decision-makers from various industries can get valuable insights from the synthesis of existing literature, which will improve their comprehension of the progress in the financial risk management process utilizing machine learning techniques.

Tapiwa Shabani, Steven Jerie, Takunda Shabani

Sravya Sai Guddeti, Rama Mohan Kurakalva, Shankar Karuppannan

The present study is undertaken at the lower Manair River basin, the central part of Telangana in southern India, as the Government authorities has done rapid developmental activities over the last seven years demanded identifying change detection in environmental indicators. Geospatial tools, viz., remote sensing and geographic information system, are used to classify and identify land-use/land cover (LULC) changes during 2015–2021 based on the images collected from Landsat 8 OLI/TIRS multispectral and multi-temporal satellite data set. Change detection of environmental indicators such as LULC changes, land surface temperature (LST), and normalized difference vegetation index (NDVI) are crucial parameters that play a vital role in identifying vulnerable areas, which helps in planning and utilizing natural resources. The results revealed that the agricultural cropland filled in the top class with an area of 1124.70 km2 (33.82%) in 2015, amplified to 1442.95 km2 (43.39%) in 2021. The built-up area has marginally raised by 581.45 km2 (17.49%) in the study region. A negative correlation is observed between LST and NDVI. LULC patterns are changing, and its imprint echoed on a surge of LST. It establishes a foundation for evidence-based policymaking and sustainable growth, emphasizing the importance of proactive measures in preserving the delicate balance between development and environmental conservation.

Dakwatun Shofia, Ana Islamiyah Syamila

Background: One of the Occupational Health and Safety (OHS) efforts to minimize risk is by carrying out risk management. The challenge in informal industries is that comprehensive risk analysis has not been carried out, so there is no control program to prevent work accidents. There have been work accidents in the roof tile industry due to various potential dangers that were not controlled beforehand. Purpose: To analyze the risks that exist in the roof tile manufacturing process. Method: This research uses descriptive research with a quantitative approach. This research was conducted in one of the roof tile industries in Indonesia. The units of analysis in this research are the process of mixing raw materials, grinding, molding, drying, and burning. The type of OHS risk analytical used is HIRARC, one of the implementations of ISO 31000 : 2018 for company risk management. HIRARC consists of hazard identification, risk assessment, risk evaluation, and risk control. Result: There are 89 potential hazards in the roof tile manufacturing process from. Most of the risks are low-level though there are still two categorized as very high. The results of the risk evaluation are categorized as Acceptable. Controls are carried out, starting from elimination until the use of Personal Protective Equipment (PPE). Conclusion: The most commonly identified hazards are physical hazards. Most risks fall to "Low and Acceptable’"category. However, there are still some risks that fall to "Unacceptable" category. Therefore, risk controls still need to be implemented based on hierarchy of controls.

Dongchi Yao, Borja García de Soto

Construction 4.0 integrates digital technologies that increase vulnerability to cyber threats. A dedicated cyber risk assessment framework is essential for proactive risk mitigation. However, existing studies on this subject within the construction sector are scarce, with most discussions still in the preliminary stages. This study introduces a cyber risk assessment framework that integrates machine learning techniques, pioneering a data-driven approach to quantitatively assess cyber risks while considering industry-specific vulnerabilities. The framework builds on over 20 literature reviews related to construction cybersecurity and semi-structured interviews with two industry experts, ensuring both rigor and alignment with practical industrial needs. This study also addresses the challenges of data collection and proposes potential solutions, such as a standardized data collection format with preset fields that computers can automatically populate using data from construction companies. Additionally, the framework proposes dynamic machine learning models that adjust based on new data, facilitating continuous risk monitoring tailored to industry needs. Furthermore, this study explores the potential of advanced language models in cybersecurity management, positioning them as intelligent cybersecurity consultants that provide answers to security inquiries. Overall, this study develops a conceptual machine learning framework aimed at creating a robust, off-the-shelf cyber risk management system for industry practitioners.

Yuemin Sun, Jiewei Zhan, Fei Qiang et al.

For over 50 years, the Xianyang city on the Chinese loess plateau, has been deeply affected by land subsidence and its associated ground fissures. In this study, 67 Sentinel-1A images from 2015 to 2022 were analysed to obtain the spatio-temporal evolution of land subsidence. Subsidence centers identified in Yunyang town and Luqiao town exhibit annual subsidence rates of −31 mm/a and −26.7 mm/a, respectively, culminating in total subsidence of −258 mm in Yunyang town and −139 mm in Luqiao town. Moreover, time series analysis revealed that both towns exhibit pronounced seasonal subsidence patterns. It is believed that human cultivation and groundwater overuse, combined with the effects of active faults, have led to uneven land subsidence. Then, the gradient of land subsidence and its potential relation to ground fissure hazards were evaluated. The results highlight a strong spatial correlation between high subsidence gradient areas and dense ground fissure distribution. Therefore, we proposed for the first time to introduce the land subsidence gradient factors for the susceptibility mapping of ground fissures using the artificial neural network algorithm. The susceptibility zonation results show that integrating the gradient factor can improve the rationality of the susceptibility evaluation. The above understanding provides valuable support for disaster prevention and mitigation in urban areas affected by land subsidence and ground fissures in loess regions.

Thu Luong Huynh Anh

In this financial oriented business world, the risk and risk measuring activities such as identifying the issues, analysing and modifying of ambiguity in the credit creation and investment behavioural decision making. (Kishk et. al. 2008) Basically, the risk management process comes when a stakeholder of a corporation or the fund allocator decides on the basis of analysis and attempts to evaluate the probable losses in any investment. To avoid this kind of risk or technically termed as the moral hazard problem, the investor has to take certain necessary action for gaining better profitability or minimize the risk of loss. The risk management strategies are termed as behavior of the financial risk (Moles, 2016). The present paper aims to study the various behavioral decision-making process of the manager or the investor of the corporation towards the profitability.  It also aims to emphasizes the impact of this strategic behavior of the firm or corporation’s decision on the successful growth and establishment. The study is significant with respect to evaluate the cause and effect through the strategies implemented by the investors. It also attempted to reveal the project success story by implementing the risk averse practices. The project victory criteria are a measurable or quantifiable term of expected outcome of the running project which must be accepted by the stakeholder. Financial risk measurement is always being an implicit proportion of the management in the firm or industry. The present study adopts the descriptive research method and uses the secondary data sources published in the company’s websites and annual statements. The collected data have been analyzed by an appropriate statistical and econometrical tool to evolve the relationship between the behavioural aspects of risk management strategies and its influence on the project success of the firm.  The risk management of credit on commercial bank is most essential for the benefit and stop suffering from the losses on the project. Prevention and controlling the risk of loans and advances is a tough and very challenging target for the business project. It is statistically evidence that there is an association between the profit and credit loss expense. On the whole, the present study explores the profitability and the success of the financial organization.

Azhar Alam, Bayu Arie Fianto, Ririn Tri Ratnasari et al.

This paper explored a trend analysis related to takaful research from 1989 until March 2022. This research aims to determine: (1) the current growth and trends of publications in takaful; (2) the most productive contributors in takaful studies; (3) the highly-cited documents in takaful research; and (4) the essential keywords and themes involved in the takaful studies. The data was obtained through the Scopus database with the keywords “takaful,”“Islamic insurance,” or “sharia insurance.” The search resulted in 423 documents and became 356 documents after screening. The data has been exported and analyzed using tools such as Biblioshiny, VOSviewer, Publish or Perish (PoP) and Microsoft Excel. The results showed that most publications were in 2017 and 2020. The most significant contributor that published the most research documents were Syed Ahmad Salman by the author (21 publications), International Islamic University Malaysia by Institution (24,4%), English by language (97,5%), Malaysia by country (64,04%), Journal of Islamic Accounting and Business Research by title (22 publications). This study found the article “the cost efficiency of takaful insurance companies” written by Kader as the most cited publication. Moreover, based on the results of network visualization mapping, takaful research was divided into four main themes: risk management in the takaful industry and its relation with Islamic banks, efficiency in the takaful industry, and behavior of takaful customers, and development of takaful. This study recommended a systematic literature review on popular topics such as efficiency and family takaful for further studies.

J. Farber, M. Zwietering, M. Wiedmann et al.

Abstract Listeria monocytogenes is an important foodborne pathogen, which is associated with high hospitalization and case-fatality rates. Outbreaks due to food contaminated with this pathogen continue to occur globally. In terms of risk management, major food trade associations have come together in a non-competitive manner to develop excellent guidance documents on the control of this pathogen. In addition, regulatory agencies responsible for food safety have made significant advances to help control L. monocytogenes. Many countries around the world have established microbiological criteria for L. monocytogenes of 100 cfu/g for low-risk foods that do not support the growth of the organism. In contrast, the US currently has a “zero-tolerance” approach for all ready-to-eat (RTE) foods, regardless of their risk profile, therefore all positive test results lead to a recall. A blanket “zero-tolerance” policy for all RTE foods provides a very strong disincentive for zone 1 (product contact surface) testing, as well as a significant disincentive for finished product testing. More specifically, the challenge with a “zero-tolerance” approach for all foods is that all positive test results will lead to a recall, therefore potentially limiting the willingness to frequently sample. To compensate for moving away from a zero-tolerance approach for low-risk foods, industry would likely be willing to do a higher frequency of testing, which would enable them to generate and use more data, including next generation tools, to inform risk-based decision-making, long before committing products to commerce. Moreover, analysis of various alternate sampling approaches demonstrates that using a 3-class sampling plan can even be more stringent than the current 2-class presence-absence zero-tolerance approach. In addition to more stringent testing, the benefits of not doing a recall on low-risk foods that do not support the growth of L. monocytogenes and that contain only low levels of the pathogen include i) not wasting limited industry and regulator resources; ii) not losing consumer confidence, iii) maintaining a secure and sufficient food supply, iv) decreased food waste, v) avoiding negative effects on the environment, and vi) avoiding unnecessary costly food recalls. In this review, we provide for an alternative approach to “zero-tolerance” and argue that some of the actions that could be undertaken as part of a country's policy and/or regulatory approach to enhance the control of L. monocytogenes include: i) using alternate sampling approaches to the current 2-class sampling plans for low-risk foods that do not support the growth of the organism; ii) using big data to better inform microbial risk assessments; iii) performing a risk-benefit assessment; and iv) developing novel consumer food handling/risk communication strategies. As evidenced by many years of studying this foodborne pathogen, a multi-pronged approach to the control of L. monocytogenes in high-risk RTE foods is necessary to reduce risk. This approach should include evidence-based, globally harmonized definitions for RTE and non-RTE foods, along with guidance on how these definitions should be applied in any policy on L. monocytogenes.