Supply Chain Risk Management Research Articles

Developing a smart green supplier risk assessment system integrating natural language processing and life cycle assessment based on AHP framework: An empirical study

Global carbon reduction drives the transformations of corporations, emphasizing carbon and environmental impact within supply chains. A critical challenge in risk management is converting unstructured data into quantifiable information, and ruining the conversion often leads to ineffective risk assessments. While artificial intelligence is increasingly used in supply chain risk management, previous studies seldom integrate text analysis for risk extraction and lack accurate risk assessment methods. This study pioneers an intelligent green supplier risk assessment system integrating natural language processing (NLP) and life cycle assessment (LCA) based on an analytic hierarchy process (AHP) framework. The proposed approach utilizes NLP keyword extraction to identify and assess risk and uses LCA to uncover environmental risks, minimizing negative impacts. The text classification model attains 81.7 % accuracy, ensuring a trustworthy risk assessment system. The proposed method could significantly improve risk analysis efficiency, foster sustainable procurement, and elevate enterprise competitiveness in sustainable business practices.

Assessment of global supply chain risk and mitigation strategies

This studies paper presents a comprehensive examination of global supply chain risk management, critical for navigating cutting-edge interconnected enterprise panorama. It explores diverse participants to deliver chain vulnerabilities, together with natural disasters, political instability, and economic fluctuations, highlighting the necessity for proactive chance mitigation techniques. Leveraging insights from scholarly literature and case research, the research underscores the importance of thorough understanding and evaluation of worldwide deliver chain dangers. It advocates for the adoption of progressive methodologies such as fuzzy common sense and Bayesian Belief Networks to beautify threat evaluation practices and prioritize mitigation efforts successfully. Moreover, the paper emphasizes the pivotal role of top management aid, strategic collaboration, and technological advancements in mitigating supply chain disruptions. Through the synthesis of various perspectives and strategies, the research advocates for a holistic technique to mitigate worldwide deliver chain dangers, making sure organizational resilience and sustainability. It underscores the necessity for continuous tracking, edition, and investment in chance management frameworks to navigate uncertainties and keep a competitive gain in an ever-evolving commercial enterprise surroundings. By offering practical insights and actionable tips, this paper equips groups with the expertise and gear essential to support their supply chains against disruptions, thereby improving operational performance and fostering long-time period achievement within the worldwide market. Keywords Supply chain risk management, Global supply chain,Risk mitigation strategies,Disruptions,Resilience

Is supply chain risk mitigation affected by organisational design? The roles of organic structures and cultures

The objective of this paper is to investigate the potential of organisational design as a potent approach to supply chain risk management (SCRM). Using contingency theory, the current research distinguishes between two design options: organic and mechanistic organisations, both at the structural and cultural levels. The authors predict a positive relationship between the organic nature of structural and cultural elements and the level of supply chain risk mitigation. They also predict a positive interaction effect between structural and cultural elements. To test hypotheses, multiple and moderated regression analysis was conducted on a sample of 213 small and medium-sized enterprises in the Spanish agri-food supply chain. The results confirmed the proposed hypotheses. This research contributes to the literature on SCRM by opening a discussion on the impact of organisational design as means of managing supply chain risk. In particular, it draws attention to the positive combined effects of the different design characteristics (structural and cultural). Furthermore, this study provides managers with insights into the use of organisational design as an additional tool for managing supply chain risk.

The impact of digital technology deployment on mitigating supply chain disruptions: Evidence from Chinese automotive manufacturers during the COVID-19 crisis

Digital supply chain management provided opportunities to mitigate the effects of supply chain disruptions on business activities. Unfortunately, the real-life impacts of digital technology deployment in mitigating supply chain disruptions and enhancing resilience have not been fully evaluated, and it is unclear which digital technology deployment strategy had the greatest effect on firms' operations. This research seeks to fill this gap using data from the annual reports of 123 Chinese automotive manufacturers during the COVID-19 crisis. We focus on two dimensions of digital technology deployment: amount and category. Metrics describing financial and operational performance are used to estimate firms' overall performance. Additionally, this research presents econometric models to assess the effects of digital technology deployment from the two aforementioned dimensions. We found that the deployment of digital technology assets could mitigate negative effects on firms' performance during COVID-19 crisis, albeit with a time lag. Different categories of digital technology deployment, however, had different effects on firms' financial and operational performance. Digital front-end technologies were more efficient in improving the financial performance of the automotive firms. Meanwhile, digital base technologies were more impactful on the firms’ operational performance. This research contributes to the body of research on digital SCM and supply chain risk management by examining the effect of digital technologies from a dynamic capability perspective.

Supporting Supply Chain Risk Management: An Innovative Approach Using Graph Theory and Forecasting Algorithms

Supporting Supply Chain Risk Management: An Innovative Approach Using Graph Theory and Forecasting Algorithms

Sustainable performance and disaster management in the oil and gas industry: An intellectual capital perspective

In the post-COVID era and amidst the ongoing Ukraine conflict, the natural resource extraction sector, particularly oil and gas, faces unprecedented challenges in maintaining its sustainability. Disasters in this sector, ranging from environmental catastrophes to operational disruptions, further exacerbate these challenges, eroding environmental integrity and aggravating social issues. These events underscore the urgency of strengthening disaster management capabilities in the oil and gas sector to safeguard against future uncertainties and sustain its operational viability. Against this context, this study aims to examine two critical facets of disaster management in the oil and gas sector. The first objective is to assess the role of intangible resources, particularly intellectual capital, in improving an organization's disaster management capabilities. Intellectual capital, encompassing human, relational, and structural capital, is posited as a key driver in managing complex and unpredictable challenges. The second objective is to investigate the role of supply chain risk management in mediating the impact of intellectual capital on disaster management. Data for this study were collected from firms in the oil and gas sector of Pakistan through a structured questionnaire Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for data analysis. The results reveal a significant impact of intellectual capital on improving both the responsiveness and alertness aspects of disaster management. Further, supply chain risk management emerges as a crucial factor in channeling the influence of intellectual capital on disaster management effectiveness. Findings of the study not only contributes to the theoretical understanding of disaster management in the natural resource sector but also offers practical insights for industry practitioners. The novelty of this study lies in its empirical examination of the interplay between intellectual capital, supply chain risk management, and disaster management capabilities, win the context of the oil and gas sector.

Risk management and HR practices in supply chains: Preparing for the future

This study explores the strategic integration of risk management and Human Resources (HR) practices within the context of supply chain management, aiming to identify how such integration enhances organizational resilience and sustainability. Employing a systematic literature review and content analysis, the study examines scholarly articles from key databases, focusing on the period from January 2000 to the present. The methodology involves a comprehensive search strategy, stringent inclusion and exclusion criteria, and a detailed selection process to distill insights from relevant literature. Key findings reveal that strategic HR practices, such as talent management, leadership development, and fostering a risk-aware culture, significantly contribute to mitigating supply chain risks and bolstering resilience. Furthermore, the study highlights the pivotal role of technological advancements, including artificial intelligence, blockchain, and the Internet of Things, in supporting the dynamic integration of risk management and HR practices. This integration not only addresses operational efficiencies but also aligns with strategic objectives towards sustainability and adaptability in the face of global disruptions. The study concludes that the strategic importance of integrating risk management with HR practices cannot be overstated, emphasizing its necessity for building agile, resilient, and sustainable supply chains. As organizations navigate the complexities of modern supply chains, this integrated approach offers a pathway to not only survive but thrive amid uncertainties, underscoring a blueprint for sustainable competitive advantage in evolving global markets. This review contributes to the existing body of knowledge by providing a comprehensive overview of current practices and future directions for integrating risk management and HR practices in supply chain management.

Enhancing Logistics Performance through Increased Trust and Collaboration in Supply Chain Risk Management: A Focus on the Distribution Network of Manufacturing Companies

This study aims to explore the significance of trust among companies within the supply chain and investigate its effect on collaborative supply chain risk management. In the current uncertain business environment, it is crucial for companies to establish trust relationships with their trading partners and collaboratively manage risks. This research seeks to understand how such trust relationships influence collaborative risk management and, subsequently, the effect of risk management collaboration on logistics performance. This study surveyed manufacturing companies in the Korean supply chain, and data were analyzed using SPSS 23.0 and AMOS 23.0. The results of this study imply that cognitive trust, related to the partner’s expertise and capabilities, is more crucial than emotion-based affective trust in fostering collaborative supply chain risk management among companies within the supply chain, especially in the current unpredictable and complex business environments. Given the supply chain disruptions caused by uncertainties in the business environment, it is imperative to effectively manage risks and restructure the disrupted supply chain. Therefore, companies need to strive to demonstrate their expertise and capabilities to build cognitive trust and enhance logistics performance through supply chain risk management collaboration.

Take JD as an Example to Discuss the Impact of Digital Intelligence on Supply Chain Risk Management

The complex and changeable global economic situation forces supply chain enterprises to strengthen risk management to deal with all kinds of emergencies. In the existing research, the impact of supply chain risk is still lack of in-depth exploration. From the perspective of intelligent transformation of enterprises, this paper takes JD as an example to analyze the problems existing in the risk management of the three supply chains of commodities, logistics, and finance, and then puts forward the corresponding solutions to the different problems in the three supply chains. This paper analyzes that the transformation of enterprise number intelligence can improve the efficiency of supply chain coordination and improve its risk management ability by establishing a shared information platform, but the imperfection of technology and the immaturity of technology application will also bring more unprecedented risks to enterprises.

Risk Factors of Perishable Product Supply Chain: Literature Review and A Proposed Framework for Future Research

United Nations statistics show that about one-third of globally transported perishable products are annually wasted due to damage. Where in the perishables supply chain is most likely to go wrong and how can this be corrected or prevented? This article aims to review the literature 50 articles related to the risk factors of perishable products supply chain and cluster the risk factors of perishable products supply chains. Identifying 140 risk factors from 235 risk factors through duplication filtering. And the researcher therefore clusters of risk factors with hierarchical clustering (divisive: distance matrix) into 19 clusters by KNIME machine learning. These findings offer valuable insights for future research on orchid’s supply chain risk management for sustainability in Thailand, top global orchid exporter. For the benefit of orchid supply chain stakeholders in Thailand can develop appropriate and sustainable supply chain risk management in the future. Thailand 3rd National Logistics Development Strategy (2017-2021) emphasizes cold chain logistics to elevate agricultural and industrial supply chains to meet standards. Implementing a cold chain system is vital to reduce losses, enhance traceability, and lower production costs.

Adaptive Supply Chain Risk Management Using AI Mitigating Disruptions and Enhancing Resilience in the Post-Pandemic Era.

The COVID-19 pandemic has starkly revealed the vulnerabilities within global supply chains, prompting the urgent need for enhanced risk management strategies. This paper explores the application of Artificial Intelligence (AI) in adaptive supply chain risk management to mitigate disruptions and enhance resilience in the post-pandemic era. By leveraging AI technologies such as machine learning, predictive analytics, and optimization algorithms, organizations can proactively identify, assess, and respond to risks in real-time, thereby fortifying their supply chains against unforeseen disruptions. [1] This paper reviews existing literature on supply chain risk management, AI applications in supply chain management, and post-pandemic supply chain challenges. Furthermore, it presents examples illustrating how AI-driven adaptive risk management approaches have been implemented successfully to navigate disruptions and improve supply chain resilience. Through this analysis, the paper aims to provide insights into the transformative potential of AI-enabled adaptive risk management strategies in building agile and robust supply chains for the future. DOI: https://doi.org/10.52783/tjjpt.v45.i02.6294

Risk management maturity and robustness in the Chinese manufacturing supply chain: a comparison study across organisational cultures

ABSTRACT Chinese manufacturing, a major engine of the world economy, has been at the heart of the challenge of major global supply chain disruptions. This research explores the relationships among different dimensions of supply chain risk management maturity and supply chain robustness in Chinese manufacturing organisations. A structural equation model is developed and tested based on the participation of 296 supply chain managers. Based on the Competing Values Framework, four different culture groups are assessed to determine whether the relationships differ by culture type. While all model relationships were found to be significant and positive across the culture groups, the weights associated with certain relationships were significantly different. The adoption of the proposed framework could bring the benefit of a more comprehensive evaluation of supply chain risk management maturity, as well as the identification of both strengths and areas where improvements may be necessary for achieving supply chain robustness.

Adoption of Blockchain in Critical Minerals Supply Chain Risk Management

This study examines the impact of digital transformation, digital awareness, and supply chain risk management (SCRM) on the intention to employ blockchain technology in the US critical minerals industry. It examines the influence of digital transformation on supply chain resiliency and the adoption of blockchain by analyzing responses from 122 managers and professionals through structural equation modeling and partial least squares approaches. SCRM, perceived usefulness, and usability shape the intention to use blockchain, while digital transformation enhances supply chain resiliency. This research contributes to the existing literature by confirming the relevance of the technology acceptance model in blockchain adoption and by highlighting the importance of digital transformation in supply chain resiliency. Practically, it offers valuable insights for managers, emphasizing the role of SCRM in recognizing blockchain's benefits, the need for digital literacy and transformation to facilitate blockchain adoption, and the potential of blockchain to enhance supply chain operations.

See no evil, hear no evil, speak no evil? Barriers to modern slavery risk management in supply chains: an empirical investigation

This paper seeks to identify the barriers that prohibit the detection, prevention and remedying of modern slavery incidents in supply chains. A conceptual model is developed that draws on literature on supply chain risk management and barriers to modern slavery. 22 semi-structured stakeholder interviews were conducted to examine common challenges. We distinguish between barriers at different levels – macro, supply chain and organisational – and before and after a modern slavery incident happens – pre-incident and post-incident phases. New barriers emerged in the pre-incident phase, including disparities in terminology, a lack of global law, and limited power in the supply chain; and in the post-incident phase, a lack of remediation frameworks emerged. Modern slavery is notoriously difficult to research as companies fear exposure, and we make a novel contribution by collecting primary data from 22 stakeholders engaged in the management of modern slavery.

Supply Chain Risk Management in LNG Import Terminals through Proactive and Reactive Operational Strategies

Supply Chain Risk Management in LNG Import Terminals through Proactive and Reactive Operational Strategies

Supply chain risk management capabilities during enterprise resource planning implementation: Perspectives of enterprise resource planning providers and their clients

Supply chain risk management capabilities during enterprise resource planning implementation: Perspectives of enterprise resource planning providers and their clients

The role of technology in supply chain risk management: Innovations and challenges in logistics

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.

Theoretical approaches to AI in supply chain optimization: Pathways to efficiency and resilience

The integration of Artificial Intelligence (AI) into supply chain management has emerged as a pivotal avenue for enhancing efficiency and resilience in contemporary business operations. This paper explores various theoretical approaches to AI within the context of supply chain optimization, delineating pathways to achieve heightened performance and adaptability. Commencing with a historical overview, the paper delves into the evolution of AI techniques in supply chain management, elucidating how these methodologies have transformed the landscape of logistics and operations. Fundamental to this exploration is the discussion on mathematical modeling and algorithmic frameworks that underpin supply chain optimization, providing the theoretical foundation for subsequent AI applications. A key focus of the paper lies in the application of machine learning techniques for demand forecasting and inventory management, which leverage data-driven insights to optimize resource allocation and mitigate risks associated with supply-demand fluctuations. Additionally, network theory and graph algorithms play a crucial role in optimizing the structure and dynamics of supply chain networks, enabling efficient transportation, distribution, and inventory routing. Strategic decision-making in supply chains is addressed through the lens of game theory, which offers theoretical frameworks to model interactions among multiple stakeholders and optimize outcomes in competitive environments. Moreover, swarm intelligence and multi-agent systems provide innovative solutions for coordination and collaboration within complex supply chain ecosystems. Evolutionary algorithms and artificial neural networks are discussed as powerful tools for supply chain design, predictive analytics, and risk management, offering capabilities for optimizing decision-making processes across various operational domains. Furthermore, reinforcement learning techniques empower dynamic decision-making in real-time operational settings, fostering adaptive and resilient supply chain management practices. By integrating multiple AI techniques, hybrid approaches offer synergistic solutions that capitalize on the strengths of diverse methodologies to address multifaceted challenges in supply chain optimization. Through a synthesis of theoretical insights and practical case studies, this paper provides valuable insights into the current state and future directions of AI-driven supply chain optimization.

제3자 물류 기업 활용에 영향을 미치는 공급체인 리스크에 관한 연구

The recent increase in supply chain risk due to global supply chain issues has caused logistics costs such as fuel and labor costs to rise for shipper companies engaged in import and export activities. Therefore, shipper companies are outsourcing logistics activities to third-party logistics providers(3PLP) to manage supply chain risk and solve management problems caused by rising supply chain risk. In addition, as third-party logistics companies have begun to adopt and utilize 4th industrial technologies such as smart warehouses and autonomous driving, it is necessary to examine the relationship between these technologies and firm performance. Therefore, this study categorizes supply chain risks in a logistics uncertainty environment and identifies the causal relationship between risk factors, 3PLP utilization, and firm performance. To conduct the study, a questionnaire was constructed based on previous studies and interviews with current practitioners, and a survey was conducted based on the list of member companies of the Korea International Trade Association, the Association of Small and Medium Venture Businesses, and the Korea Trade-Investment Promotion Agency. The hypotheses were tested using PLS-SEM methodology, and the results showed that among supply chain risks, only demand risk had a significant impact on 3PLP utilization, and 3PLP utilization had a significant impact on shippers' financial performance and logistics performance.

Risk Management in Global Supply Chains: Addressing Vulnerabilities in Shipping and Logistics

This paper explores the critical aspects of risk management in global supply chains, with a specific focus on vulnerabilities within shipping and logistics. The interconnected nature of today's supply chains exposes them to various risks, ranging from natural disasters and geopolitical tensions to operational challenges and cybersecurity threats. The paper outlines a comprehensive framework for risk identification, assessment, and mitigation, emphasizing the importance of proactive strategies in addressing potential disruptions. Diversification of suppliers and transportation routes, technological investments, insurance coverage, and enhanced collaboration are highlighted as key mitigation measures. Through case studies, the paper examines successful risk management practices and draws insights from failures. Additionally, it delves into emerging trends, such as technological advancements and climate change adaptation, providing a forward-looking perspective on evolving risks. The conclusion underscores the dynamic nature of global supply chain risks and advocates for continuous improvement in risk management practices to ensure resilience and sustainability.
 Keywords: Risk Management, Global, Supply Chains, Vulnerabilities, Shipping and Logistics.