Supply Chain Risk and Disruption Management

Global supply chains (SCs) have faced many risks, vulnerabilities, and disruptions over the past two decades. The current pandemic induced by COVID-19 has had the largest impact on SCs worldwide, the depth of which is still unknown. Hence, SC risk management is a very popular topic among academics and practitioners. This chapter discusses the sources and impacts of SC risks and disruptions. A particular focus has been placed on large-scale SC disruptions and their effects in the long term. Furthermore, this chapter discusses SC resilience, sustainability, adaptability, and viability, all of which are key subjects in the management of SC risks and disruptions. Lastly, this chapter highlights the tools, techniques, and technological approaches used to help practitioners of risk management to better understand risk management techniques for SCs, outlining the main directions of research in SC risk management.

Coordinating activities among multiple independent entities in decentralized supply chain (DSC) systems are essential to ensure the smooth flow of products and/or services. The coordination becomes more difficult and challenging in the presence of uncertainties, which always occur in real-world practical scenarios. This chapter presents a literature review on quantitative modeling approaches for DSC systems under uncertainties. The articles are selected based on their relevance to this field’s specific problem descriptions, modeling, and solution approaches. The analysis is divided, based on their quantitative models and solution approaches, emphasizing optimizing DSC planning under various uncertain parameters. The analyzes reveal that most studies have used game theory approaches in modeling DSC systems with uncertain parameters. In the case of solution approaches, there is an increasing trend of using metaheuristic approaches. In contrast, very few studies have considered simulation or simulation-optimization approaches to face multiple uncertainties associated with the planning process. It is also noticed that demand uncertainty is the major parameter studied in DSC systems, followed by supply, price, and lead time uncertainties. From the major findings of the articles reviewed in this chapter, this study offers some useful research directions by highlighting the research gaps in this field.

The challenge in managing systematic disruptions across data-driven supply chains potentially underlies our inability to cope with deep uncertainty. Broad drivers of deep uncertainty such as geo-political tensions, disinformation, climate change, cyberattacks, and the COVID-19 pandemic present unprecedented, and adverse conditions for supply chain risk managers. Due to simultaneous occurrence, these drivers may create significant levels of deep uncertainty and inconceivable levels of stress, which threaten the resilience of supply chain ecosystems and national security. For instance, mutations of the Covid-19 pandemic and escalating geo-political tensions constrain the efficacy of practitioners and empirical researchers to estimate (at a point in time) the extent these new conditions undermine existing models and assumptions underpinning managerial decision making under conditions of uncertainty and risk. Towards these ends, we employ QDA Miner 6 software to analyse 632 articles on supply chain uncertainty retrieved from the Web of Science database. The results indicate a sharp increase in research attention on supply chain uncertainty from 2015 to 2022, consistent with the period when the global economy was facing broad supply chain disruptions from cyberattacks and the COVID-19 pandemic. Our results indicate that the field of supply chain deep uncertainty requires urgent attention from managers and researchers to broaden existing accounting and finance, statistics and mathematics, among other business analytics models in risk management to value factors such as states of nature, states of knowledge, social-psychology traits, and every source of deep uncertainty, when making supply chain risk management decisions. In addition to findings from the analysis, we rely on real world examples, secondary sources of information, the authors’ expertise in the field, hindsight, and decision theory to underpin discussions and managerial implications presented in this chapter.

Primarily, the disruption risks observed in the supply chain network (SCN) of any product are pertinent to external events, demand variability, instability in supply, processing time, and asymmetry in information dissemination. These disruptions lead to uncertainty across the supply chain, causing deleterious impacts on its operation by impacting SCN entities, namely, external suppliers, production units, distribution units, demand zones, and logistics. Managing the disruptive events mentioned above requires the formulation of a robust operational model for risk and disruption management operational model that facilitates an accurate assessment of demand disturbance and coordination of supply chain actors with true information exchange with an innovation adoption and boundary-spanning theoretical perspectives. In addition, a better understanding of disruptive impact renders quick responsiveness and cost optimization. This draws the attention towards real-time information flow among supply chain stakeholders in a secure, immutable, and trustworthy channel that can be established with the intervention of state-of-the-art emerging digital technologies, namely, Internet of Things (IoT), Big Data Analytics (BDA), Blockchain Technology (BT), Artificial Intelligence (AI), and 5G network communication because of their capability to efficiently identify the root cause of disruption and offer data-driven decision-making based on better real-time visibility, control mechanism, and process coordination. Therefore, the study offers an extant view on the aforementioned technological intervention along with a functional process overview describing the integrated strength of individual digital technologies in risk control and mitigation practices. The study covers two different brief analyses, one elaborating the role of blockchain in real-life scenarios through a secondary case study highlighting the role of the emergent technologies in managing supply chain risk and disruption, whereas the other focuses on role of AI in various stages in a supply chain using the data gathered from experts and industry practitioners. Both studies ardently indicated the promiscuous presence of IT tools in practice and pointed out the great potential ahead. The study has several interesting theoretical and practical implications related to supply chain risk and disruption management (SCRM).

Retailers must routinely contend with difficulties in managing the supply of their products due to disruptions in the supply chain. For new retailers, the challenge is how to design a resilient supply chain network; for existing retailers, the challenge is to adapt the supply chain network to satisfy customer demands. Generally, global retailers set up retail outlets in different areas to support specific customer zones and distribution centers (DCs) to manage the inventory for a cluster of retail shops. The supply chain network is usually highly exposed to external uncertainties like human-made and natural disasters. Therefore, disruptions to any of the supply chain nodes may result in the disconnection of the network and, ultimately, an interruption in the regular operations of the retailer. In this chapter, we consider an extended four-echelon centralized supply chain (CSC) consisting of the following echelons: (I) raw-materials suppliers, (II) manufacturers, (III) DCs, and (IV) retailers and their customer zones. We consider the retail business organization as the key stakeholder in this supply chain, as it owns the commercial outlets and the DCs, in addition to centrally controlling the supply operations of the four echelons. In developing our CSC, we review several resilience strategies that can be used to design or redesign a resilient retail supply chain. In doing so, we present the definition, advantages, and shortcomings of each strategy in the surveyed literature, and we also review the models that have been developed utilizing these strategies. Finally, we propose additional resilience strategies that can be adopted to improve supply chain operations when faced with major events or uncertainties, such as the disruptions caused by the COVID-19 pandemic.

Blockchain technology is still being widely adopted in real-world supply chains. The chapter describes the most recent trends and fills knowledge gaps in blockchain technology. It will help both researchers and practitioners better understand the landscape and trends of blockchain technology. It also emphasizes the value of blockchain technology for enhancing trust, time, and cost-effectiveness within the supply chain, and enhancing the overall supply chain’s resilience during disruptions such as the COVID-19 pandemic. It then investigates the role of blockchain technology in the resilience key components such as visibility, digitization, and provenance, and then investigates the role of blockchain technology in minimizing pandemic-induced supply chain risks, as well as the advantages and managerial challenges of blockchain technology implementation.

A blockchain refers to a digital ledger of transactions that is duplicated and distributed across the network of computers in blocks. This study attempts to present Blockchain Technology (BCT) as an effective tool for managing risks inherent in supply chain. Based on extant literature and experts’ opinion collected through in-depth interviews, a general impression is drawn on the current state of BCT as an application in supply chains of organizations. A qualitative study based on Interpretivism theory was conducted where experts from related domain were interviewed on various themes related to BCT and its role in Supply Chain Risk Management (SCRM). It was discovered that the concept of Blockchain is relatively new and is mostly unexplored in the Supply Chain Management (SCM). Moreover, there exists confusion among people regarding the distinction between blockchain and bitcoin. This leads to unwillingness to adopt BCT in managing risks in supply chain. All the experts collectively agreed that traceability, immutability, and transparency features of blockchain can improve the risk management of supply chains.

The economic policies of developing nations have always highlighted the importance of raising farmers’ income through product value addition and productivity growth. There is a potential for increasing the production of agricultural commodities like food grains, fruits, and vegetables. Besides, the supply chain demands infrastructure facilities for primary processing, packaging, storage, etc. The facilities create market linkage opportunities backed by solid market intelligence. In recent times, ASC has become complex and driven by many risks. This chapter aims to assess the risks and their management strategies in an agriculture supply chain. The study is based on a literature review and qualitative data through interviews with progressive farmers worldwide. The study explores that ASC needs to overcome the consistent risks. It is time for the need for affiliation at various levels with technology partners for access to a new and appropriate choice of strategy for risk management. The experts for knowledge and support on a production activity and climate can also help manage the ASC risks. An enabling ecosystem that enhances farmers’ market power must be created for small landholders to take advantage of the risk-managing strategies in the ASC.

In a world impacted by disruptive events, the importance of incorporating resilience into supply chain design has become paramount. Especially, the risks associated with food supply chains can cause severe consequences directly impacting the health and well-being of societies. Though the Australian food supply chains are notably efficient and profitable, they can no longer narrowly focus on the conventional “triangle” of time, cost, and quality. Rather, they need to consider an additional, new triangle of design attributes: resilience, sustainability, and trust to assure food accessibility and availability during unprecedented events. This chapter aims to analyze different types of risks (health, natural disasters, drought, geopolitics, and technology) threatening Australian food commodities (grain, horticulture, dairy, red meat, seafood, and wine) and explore the potential role of digital technologies as enablers of resiliency in food supply chain.

The diverse nature of the Pharmaceutical Supply Chains induces many uncertainties and complications in the development and production process. The various risks have put the Pharmaceutical Industry under severe pressure since the Research & Development costs are spiraling, and the entire Supply chain is becoming increasingly complex. This calls for the development of a supply chain model with greater flexibility, responsiveness, and resilience. Therefore, risk identification, classification, and prioritizing are essential for risk mitigation, which in turn is vital for industry performance and consumer satisfaction. This paper discusses different risks in the Pharmaceutical supply chain and then prioritizes them using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach. The results obtained through TOPSIS have been discussed and their implications for the industry stakeholders have been concluded.

Several global disasters have been experienced before and will be experienced inevitably in the future. Unexpected events cause failures and disruptions in supply chain (SC) systems. Compared to other industries, disruptions in medical supply chains have sudden and significant impacts on human life and safety. Considering the scale, complexity, and dynamic nature of SCs, discovering disruptions, evaluating their impact, and recovering from them become a significant challenge. We need to use the benefit of emerging information technologies to deliver medicines and personal protective materials in a secure and timely manner and establish resilient systems to respond to catastrophic events. Based on the existing literature, this chapter first specifies five risk categories associated with medical SC disruptions: (i) production and delivery of fake (counterfeit, falsified) and substandard medicines, (ii) delivery of medicines by unauthorized parties, (iii) Breakage of cold chains, (iv) Receiving inaccurate information from various medical SC components, and (v) Leakage of sensitive patient data, data manipulation, and data theft. It later explores the opportunities of using blockchain technology to minimize or proactively eliminate these risks and improve resiliency.

The development of resilient and sustainable supply chains is perceived as the ultimate ideal to enhance supply chain performance. To cope with the increasing frequency and severity of supply chain disruptions, organizations are developing crucial capabilities to manage disruptions effectively. Most literature would suggest that a supply chain with high resilience would be more sustainable. However, others argue that sustainability and resilience objectives could be conflicting with each other. This chapter discusses the relationship between strategies employed by a supply chain to build resiliency against disruption and the impact of those practices on the sustainability of the supply chain, in particular, the environmental performance. In addition, this chapter reviews modeling approaches that are utilized to control costs, service levels, sustainability performance, and create resiliency in the supply chain. This book chapter could be used as a reference for researchers who are interested in the general management approach to the sustainable and resilient supply chain in addition to integrating resilient and sustainability factors in the supply chain modeling.