Supply Chain Risk Management Research Articles

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.

TRANSPORT RISKS IN THE SUPPLY CHAINS – POST COVID-19 CHALLENGES

The COVID-19 pandemic has caused major disruptions in global supply chains with unforeseen and unpredictable consequences. However, the pandemic was not the only reason why supply chain risk management has become more crucial than ever before. In the last decade, the occurrence of previously merely theoretical risks has emphasised the importance of risk management in supply chains. This has increased interest in risk assessment and management, COVID-19 and other disaster impact studies and proposals for more stable and resilient supply chains. This article addresses the problem of transport risk in supply chains in the context of COVID-19. Particular attention is paid to quantitative approaches. Identifying and quantifying risks and modelling their interdependencies contribute to the stability of the supply chains. The analysis presents the current state of knowledge and can serve as a guide for further research. It highlights transport risk management in supply chain management as an important area of investigation. In light of the challenges of the COVID-19 pandemic, the article proposes an approach to transportation risk assessment based on quantitative assessment and interconnection of risk factors.

Integrating supply chain risk management activities into sales and operations planning

AbstractSales and operations planning (S&OP) became a relevant managerial topic for academics and practitioners with a growing literature body and implementation cases in the industry. However, S&OP has been analysed mostly in stable environments, with few implications for uncertain environments. With the current growing pressure to deal with unexpected changes in the business environment, the integration with supply chain risk management (SCRM) activities has been considered a promising direction for the next S&OP generation. Within this context, this paper aims to advance the theoretical understanding of the interrelationship between S&OP and SCRM under different contexts and provide a practical guidance for adapting S&OP in uncertain environments. This goal is achieved by combining literature-based insights, obtained through a rigorous systematic literature review of 77 studies from academic and grey literature, with empirical insights from interviews with 15 industry experts. The research leads to a novel S&OP framework for dealing with uncertain environments. It integrates SCRM activities into S&OP, applying contingency theory as a theoretical foundation to address the context-specific nature of S&OP. Moreover, it embraces a holistic view for S&OP from an integrated people-process-IT perspective, encompassing the involved actors, the process itself and its steps, and the adopted information systems. Additionally, research findings reveal the possibility for an additional process to cope better with uncertain environments, which can run in parallel with the regular S&OP process. It is characterised by a higher planning frequency and a lower planning horizon, resulting in a closer linkage with operational planning and execution.

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.
 Keywords: Technology, Supply Chain, Risk Management, Innovations, Challenges, Logistics.

Big data-driven risk decision-making and safety management in agricultural supply chains

In the era of digitization, the integration of big data technologies has become instrumental in advancing agricultural supply chain management and bolstering risk decision-making processes. Agricultural supply chains, critical to ensuring food security and bolstering rural economies, face vulnerabilities stemming from a myriad of internal and external elements, including natural disasters and market dynamics. Consequently, the urgency to adopt effective risk management strategies is paramount. Contemporary studies have explored the utilization of big data in decision-making processes specific to agricultural supply chain risks, predominantly concentrating on preliminary risk prediction and characterization. Nonetheless, there exists a shortfall in comprehensively analyzing the intricate interplay among risk factors and establishing a holistic risk management decision-making framework based on such analyses. This research addresses these deficiencies through two principal investigative components. First, this research explores the analysis of risk factors and their interrelationships in the agricultural supply chain based on a decision tree algorithm with a transition structure. This algorithm enhances decision-makers’ understanding of risk factors and their interrelationships, and guide the implementation of effective risk mitigation measures and the formulation of contingency plans. Subsequently, the research constructs a corresponding data-driven multi-criteria decision-making method, assisting managers in balancing different risk management strategies in a volatile supply chain environment, considering costs, benefits, and feasibility to formulate the optimal strategy. The innovation of this research lies in the development of a novel risk analysis tool based on the transition decision tree algorithm. This is the first time that such advanced algorithms are applied to agricultural supply chain risk management, filling a gap in the current research. The outcomes of this study not only contribute to enhancing risk management practices within agricultural supply chains but also offer novel insights and methodological tools that are applicable in research and practices across related domains.

Role of Supply Chain Risk Management on Performance of Private Organizations: A Case of MTN Rwanda

Role of Supply Chain Risk Management on Performance of Private Organizations: A Case of MTN Rwanda

Risk management in international supply chains: A review with USA and African Cases

The globalization of supply chains has brought about unprecedented opportunities for businesses to expand their reach and access diverse markets. However, it has also exposed them to a myriad of risks that can significantly impact the efficiency and resilience of international supply networks. This paper provides a comprehensive review of risk management strategies in international supply chains, with a focus on contrasting scenarios in the United States (USA) and African contexts. The United States, as a global economic powerhouse, boasts a highly developed supply chain infrastructure. In this context, risk management primarily revolves around technological disruptions, natural disasters, and geopolitical uncertainties. Advanced technologies, such as real-time tracking and data analytics, play a crucial role in mitigating these risks. Furthermore, the USA's well-established regulatory framework aids in ensuring compliance and reducing legal uncertainties in the supply chain. Contrastingly, African nations, while experiencing rapid economic growth, often contend with infrastructural challenges and political instability. The risk landscape in African supply chains encompasses issues such as inadequate transportation networks, customs inefficiencies, and varying degrees of political stability. Localized solutions, community engagement, and collaboration with international partners emerge as critical components of effective risk management in the African context. This review underscores the importance of adopting a holistic approach to risk management in international supply chains, acknowledging the diverse challenges faced by different regions. It highlights the need for businesses to tailor their risk mitigation strategies based on the unique characteristics of the regions in which they operate. Additionally, the study emphasizes the significance of fostering collaboration between developed and emerging economies, promoting knowledge sharing and technology transfer to enhance the overall resilience of global supply chains. This paper offers insights into the multifaceted nature of risk management in international supply chains, shedding light on specific challenges faced by the USA and African nations. By understanding and addressing these challenges, businesses can enhance their preparedness and agility in navigating the complex landscape of global supply chain management

Reviewing the role of AI and machine learning in supply chain analytics

The integration of Artificial Intelligence (AI) and Machine Learning (ML) in supply chain analytics has emerged as a transformative force in reshaping traditional logistics and operations. This review critically examines the multifaceted role of AI and ML in optimizing supply chain processes, enhancing decision-making capabilities, and fostering agility in an era of dynamic market demands. AI and ML technologies have revolutionized data analytics by enabling the extraction of actionable insights from vast and complex datasets. The application of predictive analytics, powered by machine learning algorithms, allows supply chain professionals to forecast demand more accurately, identify potential disruptions, and optimize inventory levels. This not only improves overall efficiency but also reduces costs and minimizes the risk of stockouts or overstock situations. Furthermore, the integration of AI-driven automation in supply chain management has streamlined routine tasks, such as order processing, inventory replenishment, and route optimization. This automation not only accelerates processes but also mitigates the risk of human errors, enhancing overall reliability. The ability of AI to continuously learn from historical data and adapt to evolving market conditions contributes to a more agile and responsive supply chain ecosystem. In the context of supply chain risk management, AI and ML play a pivotal role in identifying vulnerabilities and providing proactive strategies to mitigate potential disruptions. Sentiment analysis and predictive modeling enable organizations to assess geopolitical, economic, and environmental factors, thereby enhancing the resilience of their supply chains. However, the adoption of AI and ML in supply chain analytics is not without challenges. This review explores the ethical considerations, data security concerns, and the need for skilled personnel in managing these advanced technologies. Additionally, it delves into the importance of explainability and transparency in AI-driven decision-making processes, emphasizing the need for a balance between automation and human oversight. This review underscores the transformative impact of AI and ML on supply chain analytics, emphasizing their potential to revolutionize traditional practices, enhance efficiency, and fortify resilience in an increasingly complex and dynamic business environment.

A Decision Support Model for Mitigating Supply Chain Risks Based on a Modified FMEA, Multi-Objective Optimization and Multi-Criteria Decision-Making Approach

Abstract Recent years have seen a huge development in the subject of supply chain risk management. In this increasingly uncertain world, the use of practical and effective tools for decision making and risk mitigation has become more necessary than ever. In this research, mitigation strategies for a tier one multinational company operating in the automotive industry and providing an assembly operation to final customer Renault Tanger and Renault SOMACA were prioritized according to their effectiveness, as well as their implementation costs. Based on research in the literature and the opinions of experts in the field. 44 risks and 55 mitigation strategies were identified. FMEA (Failure Modes and Effects Analysis) method was used based on the latest AIAG 2019 edition to filter and identify the risks to be prioritized, we used then a multi-objective optimization approach to identify the mitigation strategies that constitute the Pareto front for each of the risks and finally used the EDAS method for the final ranking of the strategies. Our case revealed that strategies like ensuring elaborating a contingency planning and defining the responsibilities, imposing contractual obligations on subcontractors, applying a flexible supply contract were found to be relevant risk mitigation strategies for the company. Managers interested in mitigating risk can deploy this model to prioritize risk mitigation strategies.

Research and analysis of airline supply chain risk management-- Take Boeing Company as an example

In today’s business environment, supply chain risk management is becoming more and more important for the strategic position of airlines. As a highly complex organizational structure, the airline supply chain faces multiple challenges and potential risks that may negatively impact its operational efficiency, customer satisfaction and profitability. Therefore, a deep understanding of the key elements and practical experience of an airline’s supply chain risk management is essential to enhance its competitiveness. This paper aims to comprehensively explore the overview and core elements of airline supply chain risk management. Firstly, it clearly defines and introduces the characteristics of supply chain risk, as well as the main risk types faced by airline supply chain. Then, it delves into the key elements of airline supply chain risk management, including supply chain visibility and information sharing, supplier selection and evaluation, and inventory management and logistics planning. Then, a series of successful experiences of airline supply chain risk management are introduced, and methods of using advanced technologies and tools to mitigate supply chain risk are discussed.

Role of information processing and digital supply chain in supply chain resilience through supply chain risk management

PurposeSupply chain (SC) management is more challenging than ever. Significantly, the pandemic has provoked global and economic destruction that appeared in the manufacturing industry as a “black swan.” Therefore, the purpose of this study was to examine the role of information processing and digital supply chain in supply chain resilience through supply chain risk management.Design/methodology/approachThis study examines SC risk management and resilience from an information processing theory perspective. The authors used data collected from 251 SC professionals in the manufacturing industry, and the authors used a quantitative method to analyze the data. The data was analyzed using partial least squares-structural equation modeling. To confirm the higher-order measurement model, the authors used SmartPLS version 4 software.FindingsThis study found that information processing capability (disruptive orientation and visibility in high-order) and digital SC significantly and positively affect SC risk management and resilience. Similarly, SC risk management positively mediates the relationship between information processing capability and digital SC. However, information processing capability was found to have a more substantial effect on SC risk management than the digital SC.Research limitations/implicationsThis study has both academic and practical contributions. It contributed to existing information processing theory, and manufacturing firms can improve their performance by proactively responding to SC disruptions by recognizing the pivotal role of study variables in risk management for a resilient SC.Originality/valueThe conceptual model of this study is based on information processing theory, which asserts that synchronizing information processing capabilities and digital SCs allows a firm to deal with unplanned events. SC disruption orientation and visibility are considered risk controllers as they allow the firms to be more proactive. An integrated model of conceptualizing the disruption orientation, visibility (higher-order) and digital SC with information processing theory makes this research novel.

Influence of Inventory Management Strategy on the Performance of Retail Chains in Nairobi Central Business District.

Operations strategy is the value-adding process used by the company to guarantee that customers receive value through the conversion of resources into finished goods and services. Operations management procedures include quality control, supply chain management, inventory management, risk management, and information technology. The main objective of this study was to establish the influence of inventory management strategy on the performance of retail chains in the Nairobi Central Business District. The study was anchored on the systems theory. The study adopted a descriptive research design and the target population was 34 retail chains within the Nairobi CBD area. The sample population involved 80 managers who were in charge of the retail chains in Nairobi CBD. Self-administered structured questionnaires were used to collect primary data. Data was analyzed using descriptive and inferential statistics. The study found that inventory management strategy has a positive significant influence on the performance of retail chains in the Nairobi Central Business District. This is because an increase in a unit of inventory management strategy leads to an improvement of the performance of the retail chains. The study recommended that retail chains should implement inventory management practices that aim to reduce deadstock and minimize inventory holding costs. The study also recommended that organizations should utilize inventory forecasting techniques to accurately predict demand and adjust inventory levels accordingly. The study further recommended that retail chains should explore vendor-managed inventory (VMI) arrangements with key suppliers to maintain optimal stock levels. The study recommended that retail chains should regularly assess and update inventory turnover strategies to meet customer demand effectively.

Supply chain strategies in response to a black-swan event: a comparison of USA, French and Polish firms

PurposeThis research aims to analyse the perceptions of practitioners in three regions regarding the challenges faced by their firms during the pandemic, considered a black-swan event. It examines the strategies implemented to mitigate and recover from risks, evaluates the effectiveness of these strategies and assesses the difficulties encountered in their implementation.Design/methodology/approachIn the summer of 2022, an online survey was conducted among supply chain (SC) practitioners in France, Poland and the St. Louis, Missouri region of the USA. The survey aimed to understand the impact of COVID-19 on their firms and the SC strategies employed to sustain operations. These regions were selected due to their varying levels of SC development, including infrastructure, economic resources and expertise. Moreover, they exhibited different responses in safeguarding the well-being of their citizens during the pandemic.FindingsThe study reveals consistent perceptions among practitioners from the three regions regarding the impact of COVID-19 on SCs. Their actions to enhance SC resilience primarily relied on strengthening collaborative efforts within their firms and SCs, thus validating the tenets of the relational view.Originality/valueCOVID-19 is (hopefully) our black-swan pandemic occurrence during our lifetime. Nevertheless, the lessons learned from it can inform future SC risk management practices, particularly in dealing with rare crises. During times of crisis, leveraging existing SC structures may prove more effective and efficient than developing new ones. These findings underscore the significance of relationships in ensuring SC resilience.

Research on Spatiotemporal Heterogeneity of the Impact of Earthquakes on Global Copper Ore Supply Based on Geographically Weighted Regression

The large and super large copper deposits worldwide are mainly distributed in the Pacific Rim and Gondwana metallogenic domains, and they are highly coupled with the spatial location of seismically active zones. Major copper-producing countries such as Chile are located in areas with high seismic activity. Earthquakes often cause copper mines to shut down, copper prices to soar, and even mining disasters, affecting the stable supply of global copper. In order to study the impact of earthquakes on the global copper ore supply, information on resource endowments, production, and earthquake data from the past 30 years are collected. This article mainly analyzes (1) the spatial correlation between earthquakes and copper mine projects, and the spatial characteristics of earthquakes’ impact on copper mine production, using correlation analysis and geographically weighted regression (GWR); (2) the impact of sudden earthquake events on the export volume and price of copper mines from the perspective of time, using the earthquake index constructed based on the magnitude of the earthquake, the depth of the epicenter, and the distance from the copper mine. The results indicate that the regions with high spatial correlation between copper mine projects and earthquakes are mainly located along the Pacific coast of South and North Americas. Earthquakes can lead to an increase in copper prices, but they will fall significantly in the short term. The impact of earthquakes on export volume generally has a delay period of 1–2 months, resulting in a short-term decrease in export volume. This article quantitatively evaluates the impact of earthquake risk on the supply chain from both spatial and temporal dimensions, providing reference for supply chain risk monitoring, risk impact assessment, and prediction. On the basis of the research results of this article, mineral resource management departments can quantitatively evaluate the spatiotemporal impact of natural risks such as earthquakes on the supply chain, adjust management policies in a timely manner, and improve the level of refined management of supply chain risks.

Stability And Risk Management of Global Supply Chains in Foreign Trade Economy

This article provides an in-depth analysis of the key role of global supply chain stability in the international trade economy and the core role of efficient risk management in this process. Driven by the wave of globalization, supply chains have become a key link connecting the economies of various countries. This article provides a comprehensive analysis of the current status of global supply chains and an in-depth exploration of the many factors affecting supply chain stability, including supplier reliability, logistics system efficiency, demand forecast accuracy, and inventory management effectiveness. It further delves into many aspects of supply chain risk management, including risk identification, assessment, mitigation and monitoring. Analyze and formulate contingency plans for emergencies as well as regular monitoring and evaluation strategies and measures to improve the effectiveness and value of risk management. Finally, this study emphasizes the importance of supply chain stability and efficient risk management in the global foreign trade economic system, and provides suggestions for future research directions and possible improvement strategies. This research has far-reaching significance for enhancing the transparency, resilience and sustainability of global supply chains, and is crucial to the stable development of the global economy.

Supply Chain Risk Management Assessment and Strategy: Case Study in a Hospital Pharmacy

Health service providers such as hospitals have a very diverse supply chain in quantity and type, one of which is medicine. Hospital Pharmacy Installation (IFRS) is one of the health support activity units responsible for planning, procurement, management, storage, distribution, use of drugs, equipment, and pharmaceutical services for medical devices related to the distribution of drugs used in hospitals. Pharmacy has several risks that need to be addressed to increase customer satisfaction. This study aims to determine the extent of the implementation of Supply Chain Risk Management, identify risks in supply chain activities, and obtain risk management strategies. In this study, the method used is the assessment of Supply Chain Risk Management and continued the evaluation of the drug chain in pharmaceutical installations with the House of Risk. It is divided into two stages, namely House of Risk Stage 1, which is used to decide the risk in each supply chain, and House of Risk Stage 2, to offers a decision-making strategy for each chosen decision. There are 20 risk events and 20 risk agents in the House of Risk stage 1, and 11 proposed risk management strategies in the House of Risk stage 2. Out of 20 risks identified in stage 1, 11 risks contributed to 80% highest risk, and the top three are drug shortage, inappropriate planning, and unclear doctor’s writing. In stage 2, the three most prioritized strategies are e-prescription implementation, clear signs for LASA drugs, and conducting supplier performance evaluation.

Exploring the Potential of Large Language Models in Supply Chain Management

This study aims to identify emerging topics, themes, and potential areas for applying large language models (LLMs) in supply chain management through data triangulation. This study involved the synthesis of 33 published articles and a total of 3421 social media documents, including tweets, posts, expert opinions, and industry reports on utilizing LLMs in supply chain management. By employing BERT models, four core themes were derived: Supply chain optimization, supply chain risk and security management, supply chain knowledge management, and automated contract intelligence, which provides the present status of LLM in the supply chain. The results of this study will empower managers to identify prospective applications and areas for improvement, affording them a comprehensive understanding of the antecedents, decisions, and outcomes detailed in the framework. The insights garnered from this study are highly valuable to both researchers and managers, equipping them to harness the latest advancements in LLM technology and its role within supply chain management.

Building resilient supply chains: Empirical evidence on the contributions of ambidexterity, risk management, and analytics capability

Supply chain disruptions are a major managerial issue due to their detrimental effects on businesses and supply chain networks. Organizations must develop a resilient strategy, which is the ability to survive, adapt, and grow during all kinds of disruptions. The main purpose of this research is to empirically validate the impact of supply chain (SC) ambidexterity and risk management, on SC resilience and the mediating effect of SC analytics capability on their relationship. By using the pretested questionnaire, responses are collected from 406 supply chain professionals working in different product-based industries in three South Asian countries i.e., Pakistan, Bangladesh, and India. Five hypotheses are examined using partial least squares structural equation modelling (PLS-SEM). The findings reveal that ambidexterity and risk management have a substantial positive effect on resilience and supply chain analytics capability has a complementary, partial mediating role in their relationship. This positive result reveals that employing strategies for the utilization of existing capabilities in conjunction with practices for exploration and developing new skills, strengthens the SC's capacity to identify threats and respond to them quickly.

COVID-19 PANDEMIC'S IMPACT ON LOGISTICS AND SUPPLY CHAIN INDUSTRY

The logistics and supply chain industry forms the backbone of global business and ensures the smooth movement of goods and services. The outbreak of the COVID-19 pandemic in late 2019 set off a chain reaction that profoundly affected these critical operations. Purpose: The purpose of this study is to analyze the multifaceted impact of the COVID-19 pandemic on the logistics and supply chain industry. It aims to explore the challenges faced by supply chain professionals, the strategies organizations use to mitigate disruptions and the resulting changes in industry dynamics. Methods: The research uses a mixed method approach that includes both quantitative and qualitative data collection. Quantitative data is collected from a survey of companies in the logistics and supply chain industry. Qualitative data is collected from interviews with experts in the field. Findings: The pandemic has exposed a series of challenges that have spread throughout the supply chain. Disruptions included factory shutdowns, transportation restrictions, erratic demand patterns, and labour shortages. Organizations are responding by rapidly adopting digital technology, where real-time monitoring, predictive analytics and automation play a central role in improving supply chain visibility, sustainability and risk management. Conclusions: The study concludes that the COVID-19 pandemic has had a significant impact on the logistics and supply chain industry. The pandemic has brought many challenges to companies, but it has also brought innovations and new ways of working. Research shows that the logistics and supply chain industry is in transition, and companies that adapt to the new reality will be better off in the long run. KEYWORDS: COVID-19, Logistics, supply chain, demand, distribution