Abstract While technologies enable better observation and control over supply chain dynamics through visibility and real-time data analytics, the COVID-19 pandemic has intensified disruption-related challenges to supply chain network dynamics. Thus, these increased uncertainties and risks make it impossible to proactively predict the areas and sizes of surges in COVID-19 infections without limiting people’s freedom of movement. This notion implies that we may need to focus on reactive planning to transfer COVID-19 treatment between hospitals and/or hospital systems. We introduce an optimization model for reactive short-term vehicle routings for such transfers. The optimization model proposed in this study can simultaneously grasp vehicle movement and cargo location information while minimizing the total travel time of vehicles, which can handle the urgency of treatment transfers by changing the value of the limited travel time of vehicles. Although the model does not include every condition that can be considered in the treatment transfers between hospitals, it shows the potential of the model we proposed in the transfer of treatment in case of shortages.KeywordsRoutingSchedulingDomestic/local logisticsOptimizationTreatment for COVID-19

Abstract Global supply chains have been facing severe disruptions for the last decade. Large-scale disruptions are imposing unknown risks across the supply chain networks. These types of risks are unpredictable to assume the complexity, timing, and location of the occurrence and its simultaneously happening as businesses are challenged to operate in a volatile, uncertain, complex, and ambiguous (VUCA) environment. The COVID-19 pandemic has drastically disrupted the global supply chains, the impact of which is yet to know. Due to the time-to-time lockdown, shutdown, and border closure, global supply chains faced supplier failure, production capacity degradation, restrictions in transportations, and lack of sufficient inventory to meet the extra demand of the essential products. On the other hand, those manufacturers involved in producing luxury and low-demand products faced a huge demand fall. As a result of this, they struggled to continue their business. The long-established supply chains have been unable to manage large-scale supply chain disruptions caused by the COVID-19 pandemic. This study, thus, aimed to understand the uncertainties in supply chains in the wake of large-scale disruptions and to figure out the implications of reconfigurable strategies to manage uncertainties in supply chains due to large-scale disruption.KeywordsSupply chainRiskUncertaintyLarge-scale disruptionStrategyResilience

Abstract The purpose of this chapter is to describe how the dynamic requirements and behaviors of supply chains and their associated complex challenges can be and have been addressed by the tools and protocols of the collaborative control theory, CCT. These tools and protocols have been developed, tested, and implemented by the PRISM Center at Purdue University and by other researchers and industries around the world. In particular, collaborative control and collaboration engineering are important for successful coordination of supply activities and interactions, due to the multiple parties involved in the supply processes and services, all subjected to disruption, errors, conflicts, and dynamic many changes. In this chapter, we describe key relevant research, methods, and tools and illustrate case studies of successful implementation.KeywordsCollaborative control theory (CCT)Cyber collaborative protocolsDisruptionsSupply networksTask administration protocols

Abstract The highly interconnected and global supply chains have faced tremendous challenges since 2019. Global conflicts, natural disasters, wars, and the COVID-19 pandemic repeatedly cause supply chain disruptions and pose major challenges for the globalized supply networks in regard to robustness and resilience. The increasing interconnectivity makes supply chains more vulnerable to disruption and it seems that the proverbial stone that falls into the water actually causes a flood at the other end of the supply chain. This enhances the requirement for an effective risk management. Based on a survey of 216 supply chain risk managers of European production firms, this study introduces the collaborative sharing of production and human resources as a method to recover from disruptions. Thereby, trust and commitment are identified as the core values for collaborative resource sharing to increase supply chain resilience. We propose a framework to explicate the main drivers for collaborative human resource and production sharing and give first practical recommendations for supply chain risk managers to support the process of the development of mitigation strategies to recover from supply chain disruptions.KeywordsCollaborative resource sharingSupply chain risk managementRational view theorySupply chain resilienceIntertwined supply network