Impacts of severe disruptions on cross-border supply chain configuration

Abstract

This thesis investigates impacts of changes in the business environment on cross-border centralized supply chains during severe disruptions, such as the COVID-19 pandemic and trade conflicts. These disruptions necessitate modifications in the supply chain configuration (SCC) decisions concerning suppliers, inventory, logistics, and orders (SILO). To analyze the impacts and decisions, a modeling framework is proposed for four supply chain scenarios, each characterized by three dimensions: business environment factors, SCC decisions, and levels of SILO integration. Mixed integer programming (MIP) models are employed to identify how and how much severe disruptions affect cross-border SCC decisions. Scenario I investigates the consequences of trade conflicts that involve tariffs and export restrictions on cross-border SCC. Using a profit-maximizing MIP model, this study finds that firms engaged in upstream procurement and downstream assembly processes are vulnerable to tariffs, which results in replacement risks and high inventory expenses. Multiple sourcing alleviates the adverse impacts of tariffs, especially in these stages. Moreover, the simultaneous implementation of tariffs and export restrictions substantially affects the resilience of SCC, which may lead to disconnections between the supply chain and countries implementing these measures. Scenario II explores the impacts of social distancing measures (SDMs) on cross-border SCC. The study develops a MIP model to integrate business environment changes in lead time and cost for transportation and processing, market size, and the number of countries imposing the SDMs. It shows that supply chain losses and disruptions primarily depend on the number of countries imposing SDMs, followed by restricted transportation, market size, and processing limitations. The propagation impacts become significant when the SDMs, especially restrictions on transportation, are implemented in downstream echelons. The fixed-demand supply chain, such as the pharmacies supply chain, suffers more significantly with stringent SDMs and high holding costs compared to elastic-demand supply chains. Scenario III examines the multi-period effects of SDMs on high-tech products' SCC. A multi‐period MIP model is developed to incorporate changes in production capacity, market potential, propagation effect of new products, processing time and cost with SDMs’ implementation. The results suggest that during new products’ life cycle, early SDMs significantly lead to low profits and suppliers switching due to limited capacity and higher processing cost, while late SDMs reduce profits mildly because of unsatisfied demands. This scenario finds that international cooperation results in demand fluctuation and higher inventory, but early cooperation could increase profits and production output. Scenario IV diagnoses and optimizes order fulfillment cycle time (OFCT) during severe disruptions. An OFCT-minimization MIP model is established to integrate product architecture and supply chain networks. A failure mode and effect analysis (FMEA) framework is proposed to identify critical paths and bottleneck nodes. This framework further diagnoses the rationality of internal option decisions based on historical and optimal configurations. An industrial case is introduced for diagnosis and results show that approximate pre-positioned inventory and the number of suppliers in each node are effective in shortening the OFCT and the proportion of delayed orders during disruptions. Improving the versatility of parts or components also effectively reduces the OFCT.