Robust Risk Management Strategies Research Articles

Artificial Intelligence-Powered Risk Assessment in Supply Chain Safety

The increasing complexity and globalization of supply chains necessitate robust risk management strategies to ensure safety and resilience. Traditional risk assessment methods often fall short in dynamically adapting to the rapidly changing conditions and voluminous data inherent in modern supply chains. This study explores the potential of Artificial Intelligence (AI)-powered risk assessment to address these limitations in the context of Malaysia's supply chain industry. By employing AI technologies such as machine learning, IoT, and predictive analytics, organizations can significantly enhance their risk management capabilities, improving predictive accuracy, real-time monitoring, and overall operational efficiency. Through a qualitative analysis involving in-depth interviews with supply chain managers, AI experts, and technology vendors, the study identifies the strategies employed for AI integration, the perceived effectiveness of these technologies, and the challenges faced in implementation. The findings highlight the importance of robust data governance, the development of explainable AI models, and continuous skill development to overcome barriers related to data quality, model interpretability, and high implementation costs. The study concludes with recommendations for fostering a safer and more resilient logistics environment in Malaysia, emphasizing the need for comprehensive AI adoption frameworks and scalable solutions for small and medium-sized enterprises.

Efficient risk-based inspection framework: Balancing safety and budgetary constraints

Efficient equipment maintenance is paramount across various industries to mitigate energy wastage and avert potential disasters such as hazardous emissions, fires, and explosions. Within this context, the adoption of risk-based inspection strategies has emerged as a crucial method for assessing equipment integrity. This study integrates the principles of Risk-Based Inspection (RBI) with a novel two-objective mathematical model, resulting in a comprehensive framework for equipment inspection programs. The primary aim of this framework is to reduce overall risk exposure while optimizing inspection expenditures. Unlike conventional approaches, this methodology eliminates the necessity to define threshold risk levels. By integrating inspection costs into the model, the assessment of Failure Consequences, and thereby, the decision-making process has been streamlined. This innovative algorithm effectively balances the reduction of failure likelihood with the minimization of inspection costs, enhancing decision-making capabilities. Importantly, this approach offers significant protection against energy wastage and the occurrence of leaks through robust risk management strategies. The algorithm employs specialized operators to expedite the discovery of optimal solutions. Empirical validation through a case study conducted at a Petrochemical Plant highlights the practicality and effectiveness of the proposed framework.

Integrating policy incentives and risk management for effective green finance in emerging markets

Integrating policy incentives and risk management is pivotal for driving the growth of green finance in emerging markets. The transition to sustainable finance necessitates an alignment between government policies and financial institutions to mitigate the risks associated with green investments. This abstract explores how policy incentives, such as tax breaks, subsidies, and regulatory frameworks, can encourage financial institutions to channel investments into green projects while addressing market-specific challenges like underdeveloped financial infrastructure and regulatory gaps. In emerging markets, the perceived risks of green investments, such as uncertain returns and regulatory volatility, often deter private sector engagement. However, integrating robust risk management strategies—including diversification, public-private partnerships, and risk-sharing mechanisms—can significantly reduce these risks, thereby enhancing the attractiveness of green finance. Additionally, government-backed incentives can lower capital costs for green projects, enabling financial institutions to provide more favorable lending terms. Regulatory frameworks that standardize green finance criteria and reporting are also critical for fostering transparency and accountability, which in turn build investor confidence. The interplay between policy incentives and risk management is further highlighted through case studies from emerging markets that demonstrate successful implementation of green finance initiatives. These examples illustrate how policy-driven support mechanisms and comprehensive risk management frameworks can unlock significant investment potential in green infrastructure, renewable energy, and sustainable agriculture. By fostering a supportive policy environment and addressing risk factors through innovative financial instruments, emerging markets can enhance green finance flows, promote sustainable development, and contribute to global climate goals. This integrated approach is essential for bridging the financing gap in green projects, ensuring that environmental sustainability is aligned with economic growth and risk mitigation.

Integrating risk management in implementing circular economy principles in the healthcare sector: a case study from Indonesia

Purpose The purpose of this study is to explore the integration of risk management and circular economy (CE) principles within the healthcare sector to promote sustainability and resilience. Specifically, the study aims to demonstrate how risk management can support the transition to a circular economy in healthcare supply chains. By integrating risk management practices with CE principles, healthcare organizations can identify potential risks and opportunities associated with circular initiatives. Design/methodology/approach This study adopts a qualitative research approach, using a case study methodology with semi-structured interviews conducted at primary care facilities to understand the application of CE principles in practice. The study uses fuzzy logic methods to assess and mitigate risks associated with strategies promoting CE principles. Additionally, key performance indicators are identified to evaluate the effectiveness and enhance the resilience of these strategies within healthcare supply chains. Findings The study highlights the critical role of robust risk management strategies in facilitating the transition to a circular economy within healthcare organizations. Primary care facilities, which are critical to frontline healthcare delivery, are particularly vulnerable to product shortages due to supply risks. This study focuses on critical protective equipment, specifically latex gloves and assesses operational risks, including supply, demand and environmental risks, using a fuzzy logic-based model. Import delays were found to be a moderate risk, typically occurring once a year. The research highlights critical KPIs for a successful CE transition within healthcare supply chains, such as on-time delivery and service quality, which are directly related to the risk of supply chain disruption. In addition, the study highlights the significant impact of other CE strategies on healthcare supply chains, including localized production and manufacturing, innovation in product development, reverse logistics, closed-loop supply chains and the adoption of lean principles. Practical implications This study provides valuable insights for healthcare organizations to optimize resource efficiency, reduce waste and promote circularity in their operations. By implementing the proposed solutions and focusing on the identified KPIs, organizations can develop strategies to achieve sustainability goals and enhance resilience in healthcare supply chains. Originality/value This study contributes to the literature by demonstrating the application of risk management in facilitating the transition to a circular economy in the healthcare sector. The use of fuzzy logic methodology offers a novel approach to assessing and mitigating risks associated with critical product failures in supply chain activities. The study’s findings provide practical guidance for healthcare organizations seeking to integrate circular economy principles and improve sustainability performance.

Trade Facilitation as a Catalyst for Government Revenue Enhancement: Exploring the Synergies Between Trade Efficiency and Tax Collection

Customs administrators worldwide are mandated to mobilize national revenue collections through the assessment and collection of applicable duties and taxes on all imports and exports. One of their primary concerns following the ratification of the Trade Facilitation Agreement is the need to optimise revenue collections while simultaneously upholding trade facilitation. This research assesses trade facilitation implications on government revenue mobilization in developing countries with a particular emphasis on Zimbabwe. The paper adopts a qualitative approach, capturing several subjective elements including the examination of the Critical Success Factors for enhanced revenue collection as well as the evaluation of trade facilitation as a solution to customs revenue leakages. Purposive sampling was employed to collect data from employees working in the Customs Division at the Zimbabwe Revenue Authority. Eighty questionnaires were distributed to participants working in Beitbridge, Chirundu, Forbes border posts and the Robert Mugabe International Airport targeting Customs Senior Managers, Customs Middle Managers, Revenue Supervisors and Revenue Officers as key respondents. Data was analysed using the Statistical Package for Social Sciences version 29. This analysis focused on four dimensions of trade facilitation, which includes port efficiency, customs environment, regulatory environment, and electronic-business. The findings indicate that trade facilitation reforms, when executed appropriately in conjunction with enhancements in electronic-business, port efficiency, customs environment and the regulatory framework, can effectively augment revenue collection. Regulatory environment improvements are key in influencing increasing revenue collection and should be prioritised in resource allocation for the achievement of best possible outcomes. We recommend ‘continuous refresher training’ on trade facilitation awareness targeting all stakeholders in ports of entry, accompanied by the implementation of robust risk management strategies as well as intensified implementation of integrity management tools.

The Dissimilar Market Volatility in Neighboring Financial Markets: An Empirical Study Using A Multivariate Garch Model

ABSTRACT: Conventional knowledge of market volatility represents that two proximate financial markets operated in the same country would display a similar pattern in their time-varying volatility. In this paper, we propose that the heterogeneity in financial policy orientation of stock markets creates significant inter-market differences in terms of the volatility of stock returns, even if they are culturally and geographically linked to each other. For the empirical investigation of our proposition, the volatility data from two major stock exchanges in the Middle East, the Abu Dhabi Securities Exchange (ADX) and the Dubai Financial Market (DFM) are used. Both the ADX and DFM stock exchanges operate in the same country, the United Arab Emirates (UAE). The ADX is based in Abu Dhabi, the administrative capital, while the DFM is based in Dubai, the commercial and business hub of the UAE. They were both established in the year 2000, and their operational headquarters are located about 150 km from each other. This paper uses a multivariate GARCH model, in particular a diagonal VECH GARCH (1, 1) model to estimate volatility measures for stock returns between ADX-listed and DFM-listed stocks. The paper finds that the stock returns are significantly less volatile in the ADX compared to those in the DFM suggesting that the volatility transmission is incomplete between these two neighboring financial markets. This difference in volatility can potentially be attributed to the relatively conservative financial policies adopted by the oil-rich emirate of Abu Dhabi compared to the more market-oriented economic policies of Dubai, the country’s financial and commercial hub. Our findings have considerable implications for portfolio managers in ascertaining risk premiums when allocating investments across the two stock exchanges. For instance, this disparity in volatility should be taken into account by investors and policymakers when designing risk management strategies because it suggests that investors in the DFM may be exposed to higher levels of risk and uncertainty compared to their counterparts in the ADX. Investors operating in the DFM may require more robust risk management strategies, such as asset diversification and hedging, compared to their ASX counterparts.

Volatility in the Equity Stock Market in India from 2019 to 2024: An Empirical Analysis

This research investigates the volatility and fluctuations in the Indian equity stock market from 2019 to 2024, a period characterized by unprecedented global and domestic challenges. The Indian stock market, like many emerging markets, experienced heightened volatility due to a confluence of events, including the COVID-19 pandemic, geopolitical tensions, economic reforms, and shifts in global financial conditions. The study employs advanced econometric models, including GARCH (Generalized Autoregressive Conditional Heteroskedasticity) and event study analyses, to capture the time-varying nature of market volatility and to identify the key factors driving these fluctuations. Our findings reveal that the COVID-19 pandemic triggered the most significant spikes in volatility, particularly during the early months of 2020, as uncertainty regarding the pandemic's impact on the economy led to sharp market corrections and investor panic. Additionally, the study highlights the influence of macroeconomic variables such as GDP growth, inflation, and monetary policy changes on market behavior. The paper also explores the role of investor sentiment and market liquidity in exacerbating volatility during crisis periods. The results provide valuable insights into the dynamics of the Indian equity market, offering implications for investors seeking to manage risk and for policymakers aiming to enhance market stability. The study underscores the need for robust risk management strategies and proactive regulatory measures to mitigate the adverse effects of such volatility, especially in an increasingly interconnected global financial environment. Keywords: Equity Stock Market, Volatility, India, COVID-19, Economic Reforms, 2019-2024

Seismic hazard analysis and financial impact assessment of railway infrastructure in the US West Coast: A machine learning approach.

This research examines the seismic hazard impact on railway infrastructure along the U.S. West Coast (Washington, Oregon and California), using machine learning to explore how measures of seismic hazard such as fault density, earthquake frequency, and ground shaking relate to railway infrastructure accidents. By comparing linear and non-linear models, it finds non-linear approaches superior, particularly noting that higher fault densities and stronger peak ground shaking correlate with increased infrastructure accident rates. Shallow earthquakes with magnitudes of 3.5 or greater and hypocentral depths <20 km also exhibit a pronounced correlation with the incidence of railway infrastructure accidents The study extends to financial impact analysis through Net Present Value and Monte Carlo Simulation, and evaluates damage costs from 2000-2023 to guide financial planning and risk management strategies. It highlights the crucial role of advanced financial tools in optimizing maintenance and long-term planning that could result in better preparedness in high seismic hazard regions and emphasizes the need for robust risk management strategies in enhancing railway operational safety that considers the local and regional tectonic and seismic activity and local ground shaking intensity.

Impact of Liquidity Risk and Leverage on the Financial Performance of Nigerian Deposit Money Banks

This study investigates the impact of liquidity risk and leverage on the financial performance of listed Deposit Money Banks (DMBs) in Nigeria. The study utilized a census approach to gather data from all 15 listed DMBs on the Nigerian Exchange Group as of December 31, 2022. The study spanned from 2013 to 2022, employing various statistical analyses including descriptive analysis, correlation analysis, skewness and kurtosis tests for normality, multiple regression models for fixed-effects and random-effects models, and the Hausman test to ensure robust findings. The results indicated that liquidity risk exhibited a positive and significant impact on return on equity (ROE), a measure of financial performance, with a coefficient of 0.132 and a p-value of 0.000, suggesting that effective management of liquidity risk enhances profitability. Conversely, leverage was found to have a significant negative impact on ROE, with a coefficient of -1.351 and a p-value of 0.007, highlighting that higher debt levels substantially reduce profitability. In conclusion, the study suggests that while liquidity risk can be effectively managed to enhance profitability, excessive leverage poses significant threats to financial performance. The findings underscore the importance of robust risk management strategies for improving the financial performance of listed DMBs in Nigeria. These insights are crucial for policymakers, banking executives, and investors seeking to enhance the stability and performance of the banking sector.

Product Quality Improvement through Effective Operational Management

Purpose: This study explores the impact of advanced technologies and strategies on supply chain optimization within operational management, aiming to understand how AI, ML, IoT, blockchain, effective inventory management, supplier relationship management, risk management strategies, and sustainability practices enhance supply chain performance. Research Design and Methodology: The study uses a qualitative research design, including semi-structured interviews with supply chain experts from various industries and document analysis. The thematic analysis identifies patterns and themes, offering a detailed understanding of factors contributing to supply chain optimization. Findings and Discussion: The study reveals advanced technologies significantly improve demand forecasting accuracy, real-time decision-making, and supply chain transparency. Strategies such as JIT, Lean Inventory, EOQ, and VMI optimize inventory levels and reduce costs. Strong supplier relationships and robust risk management strategies enhance supply chain resilience and agility, while sustainability practices lead to cost savings, improved brand reputation, and regulatory compliance. The findings support the hypothesis that technological integration and strategic management enhance supply chain performance, aligning with the resource-based view and dynamic capabilities theories. Implications: This research provides insights for businesses seeking to optimize their supply chains. It highlighting the need for a holistic approach integrating technological solutions with human and organizational factors. The findings offer practical guidance for implementing advanced technologies and strategies, contributing to scientific understanding and practical applications in supply chain management.

Effectiveness of Risk Management Strategies in Mitigating Supply Chain Disruptions in South Africa

Purpose: The aim of the study was to examine the effectiveness of risk management strategies in mitigating supply chain disruptions in South Africa Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The effectiveness of risk management strategies in mitigating supply chain disruptions in South Africa has proven to be critical in maintaining operational stability and ensuring business continuity. In an environment characterized by frequent economic, political, and environmental challenges, robust risk management strategies have become indispensable for South African businesses. These strategies, including risk assessment, diversification of suppliers, implementation of advanced technologies, and development of contingency plans, have significantly enhanced the resilience of supply chains. By systematically identifying and evaluating potential risks, businesses have been able to proactively address vulnerabilities and reduce the impact of disruptions. The use of advanced technologies, such as predictive analytics, real-time monitoring systems, and blockchain, has further strengthened risk management efforts. These technologies provide valuable insights into supply chain dynamics, enable early detection of potential disruptions, and facilitate rapid response measures. As a result, businesses can maintain smoother operations and minimize downtime during unforeseen events. Unique Contribution to Theory, Practice and Policy: Resilience Theory, Resource-Based View (RBV) &amp; Contingency Theory may be used to anchor future studies on effectiveness of risk management strategies in mitigating supply chain disruptions in South Africa. Encourage the adoption of advanced technologies such as Internet of Things (IoT), artificial intelligence (AI), and blockchain for real-time monitoring and supply chain visibility. Practical implementation of these technologies can enhance early detection of disruptions and facilitate rapid response strategies. Foster closer collaboration with suppliers to co-develop robust contingency plans and risk-sharing mechanisms. Practices such as dual sourcing, supplier diversification, and joint risk assessments can build resilience across the supply chain network. Advocate for policies that incentivize resilience-building practices within supply chains. This could include tax incentives for investments in resilient infrastructure, as well as mandatory reporting on supply chain risk management practices to enhance transparency and accountability.

A proposed framework for defining the relationship between complexity, project categorization, and project risk management: Case study of a medical company in Morocco

Recent financial crises have highlighted the utmost importance of implementing risk management practices, as exemplified by the profound repercussions of the COVID-19 pandemic. Moreover, we witnessed the rise of various initiatives within the medical sector, specifically in the fields of biomedicine, hospitals, and pharmaceuticals, across Africa, with a notable emphasis on Morocco. The government in Morocco has implemented measures to foster investment and encourage participation from companies and stakeholders. Taking into account an indeterminate and volatile future, it becomes imperative for organizations to establish robust risk management strategies to navigate successfully through these uncertainties. This research paper concentrates on the convergence of complexity, project categorization, and risks. We propose a novel approach to the implementation of the Risk Management Process, utilizing the Enterprise Risk Management framework. By establishing Risk Management rules within the context of a “complex” project, we observed enhanced performance and improved risk management through the holistic consideration of interdependencies rather than treating them as separate entities. Additionally, to substantiate this interdependency, we conducted a comparative analysis of the project's risk and complexity between 2020 and 2022.

Resolving the issues of translocated species in freshwater invasions

Biological invasions, driven by human-mediated species movements, pose significant threats to global ecosystems and economies. The classification of non-native species is a complex issue intertwining ecological considerations and ethical concerns. The need for nuanced and less ambiguous terminology is emphasised, considering biogeographic, evolutionary, and ecological principles. In-country translocations of native species into ecosystems in which they do not naturally occur, are often overlooked and are the least regulated among species movements, despite being increasingly common in conservation. Our case studies, spanning various ecosystems and taxa, illustrate the diverse impacts of translocations on native species and ecosystems. The challenges associated with translocated species underscore the urgency for robust risk management strategies and rigorous monitoring. A comprehensive and adaptable management framework that considers translocated species for evidence-based management decisions is critical for navigating the complexities of translocations effectively, ensuring the conservation of biodiversity and ecosystem sustainability.

Based on Symmetric Jump Risk Market: Study on the Ruin Problem of a Risk Model with Liquid Reserves and Proportional Investment

In order to deal with complex risk scenarios involving claims, uncertainty, and investments, we consider the ruin problems in a compound Poisson risk model with liquid reserves and proportional investments and study the expected discounted penalty function under threshold dividend strategies. Firstly, the integral differential equation of the expected discounted penalty function is derived. Secondly, since the closed-form solution of the equation cannot be obtained, a sinc method is used to obtain the numerical approximation solution of the equation. Finally, the feasibility and superiority of the sinc method are illustrated by error analysis. In addition, based on a symmetric jump risk market, we discuss the influence of some parameters on the ruin probability with some examples. This study can help actuaries develop more robust risk management strategies and ensure the long-term stability and profitability of insurance companies. It provides a theoretical basis for actuaries to carry out risk management.

Risk Management Strategy on Financial Performance of Micro Finance Institutions in Uganda: A Case of Rushere Savings and Credit Cooperative Organization in Kiruhura District

Microfinance institutions (MFIs) play a crucial role in promoting international and local development goals, especially in the context of poverty reduction, economic empowerment, and financial inclusion. MFIs provide financial services, such as microloans and savings accounts, to low-income individuals and small businesses. These services are intended to help people lift themselves out of poverty by providing access to capital for income generating activities. Many of the United Nations' Sustainable Development Goals, such as no poverty, zero hunger, and gender equality, can be furthered through the work of MFIs. However, it's essential to note that the impact of MFIs varies depending on the specific institution, its approach, and the regulatory environment in which it operates. While microfinance has the potential to be a powerful tool for development, it is not a panacea and must be implemented effectively to achieve the desired outcomes. Consequently, MFIs face various risks in their operations, which impact their financial stability and ability to achieve their social and economic development goals. To manage these risks effectively, MFIs need to implement robust risk management strategies. The specific objective of carrying out this study was to examine the extent to which risk management influences the financial performance of Rushere Savings and Credit Cooperative Organization in Kiruhura Uganda. The research questions focused on risk assessment, diversification of portfolio, credit risk management, member education, technology risk management, and insurance risk coverage. This study was based on a quantitative research approach. The study was underpinned by the modern portfolio theory. A descriptive research design was used to obtain the responses that were later statistically described in quantified formats. The study considered a target population of 160 people from which a sample size of 127 respondents was selected for this study. Both Stratified proportionate sampling and simple random sampling techniques were used to select individual respondents in their strata. Structured self-administered questionnaires were used for primary data collection. Data was analyzed by the use of inferential statistics with the aid of Statistical Package for Social Scientists (SPSS) version 24.0. The study established a significant positive relationship between risk management and financial performance (β1=-124, p=0.000&lt;0.05). The study concluded that there is a strong positive relationship between risk management and financial performance. The study recommended the implementation of risk management strategies to enhance the performance of SACCOs. Keywords: Risk Management, Performance, Strategy, SACCOs

Risk management strategies for smart hotel supply chain

&lt;p&gt;In the dynamic and interconnected world of hospitality, smart hotel supply chains play a pivotal role in maintaining operational efficiency and service excellence. However, these supply chains are susceptible to many risks, including transportation disruptions, supplier insolvencies, and cybersecurity threats, which can severely impact business continuity and degrade service quality. This conceptual paper proposes a holistic framework for identifying, assessing, and mitigating supply chain risks within the context of smart hotels. By integrating advanced technologies and strategic management practices, this study aims to reinforce smart hotel supply chains against potential vulnerabilities, ensuring sustainable business operations and superior guest satisfaction. The paper explores various risk management measures and leverages supply chain management, hospitality, and cybersecurity insights to develop a robust risk management strategy tailored for smart hotels.&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;

Ethics in international HRD: examining conversational AI and HR chatbots

PurposeThe integration of artificial intelligence (AI) technologies like conversational AI and HR chatbots in international human resource development (HRD) presents both productivity benefits and ethical challenges. This study aims to examine the ethical dimensions of AI-driven HR chatbots, emphasizing the need for fairness, autonomy and nondiscrimination. It discusses inherent biases in AI systems and addresses linguistic, cultural and accessibility issues. The paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework. By embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.Design/methodology/approachSystematic literature review.FindingsThe paper advocates for a comprehensive risk assessment approach to guide ethical integration, proposing a “risk management by design” framework.Practical implicationsBy embracing ethical principles and robust risk management strategies, organizations can navigate AI-driven HR technologies while upholding fairness and equity in global workforce management.Originality/valueThis study explores the intricate ethical landscape surrounding AI-driven HR chatbots, spotlighting the imperatives of fairness, autonomy, and nondiscrimination. Uncovering biases inherent in AI systems, it addresses linguistic, cultural, and accessibility concerns. Proposing a pioneering “risk management by design” framework, the study advocates for a holistic approach to ethical integration, ensuring organizations navigate the complexities of AI-driven HR technologies while prioritizing fairness and equity in global workforce management.

Comparative Analysis of Returns and Standard Deviations of Companies' Stocks: a Five-year Study (2019-2023)

The banking sector operates within a dynamic landscape characterized by a multitude of risks and uncertainties. This study aims to explore the intricate relationship between risk and return within the banking industry, shedding light on its implications for financial stability, investment decision-making, and strategic planning. Risk Management: Banks contend with various risks, including credit, market, liquidity, and operational risks. An in-depth understanding of the risk-return interplay is essential for implementing robust risk management strategies aimed at mitigating potential losses and safeguarding financial resilience. Investment Decisions: Banks are tasked with making crucial investment decisions across a spectrum of assets, including loans, securities, and other financial instruments. Evaluating the risk-return dynamics enables banks to assess potential returns vis-a-vis associated risks, guiding investment strategies to optimize profitability while prudently managing risk exposure. Regulatory Compliance: Regulatory frameworks mandate banks to uphold stringent capital adequacy standards to mitigate risks and ensure financial stability. Risk and return analysis provides insights into capital adequacy assessments, facilitating compliance with regulatory requirements.

Leveraging Capitalization for Enhanced Project Delivery in the Nigerian Construction Industry: A Sustainable Risk Management Approach

The Nigerian construction industry grapples with challenges such as low profit margins, cost overruns, and project abandonment, necessitating robust risk management strategies. This study investigates the impact of capitalization on sustainable risk management within large construction firms in Nigeria. Data from 198 firms were collected via questionnaires, interviews, and secondary sources, revealing significant benefits of capitalization including increased turnover, risk reduction, and improved image. The findings underscore the importance of integrating risk management evaluation into construction procurement processes to optimize project delivery. This research contributes to the discourse on sustainable development in the construction sector by advocating for strategic capitalization as a means of mitigating risks and enhancing project outcomes. Keywords: Capitalization, project delivery, risks, risk management, sustainability

Investigating the Impact of Agricultural, Financial, Economic, and Political Factors on Oil Forward Prices and Volatility: A SHAP Analysis

Accurately forecasting crude oil prices is crucial due to its vital role in the industrial economy. In this study, we explored the multifaceted impact of various financial, economic, and political factors on the forecasting of crude oil forward prices and volatility. We used various machine learning models to forecast oil forward prices and volatility based on their superior predictive power. Furthermore, we employed the SHAP framework to analyze individual features to identify their contributions in terms of the prediction. According to our findings, factors contributing to oil forward prices and volatility can be summarized into four key focal outcomes. First, it was confirmed that soybean forward pricing overwhelmingly contributes to oil forward pricing predictions. Second, the SSEC is the second-largest contributor to oil forward pricing predictions, surpassing the contributions of the S&amp;P 500 or oil volatility. Third, the contribution of oil forward prices is the highest in predicting oil volatility. Lastly, the contribution of the DXY significantly influences both oil forward price and volatility predictions, with a particularly notable impact on oil volatility predictions. In summary, through the SHAP framework, we identified that soybean forward prices, the SSEC, oil volatility, and the DXY are the primary contributors to oil forward price predictions, while oil forward prices, the S&amp;P 500, and the DXY are the main contributors to oil volatility predictions. These research findings provide valuable insights into the most-influential factors for predicting oil forward prices and oil volatility, laying the foundation for informed investment decisions and robust risk-management strategies.