Current research on automotive supply networks predominantly examines single-type entities connected through one relationship type, resulting in oversimplified, single-layer network structures. This conventional approach fails to capture the complex interdependencies that exist among mineral resources, intermediate components, and finished products throughout the automotive industry. To overcome these analytical limitations, this study implements a multilayer network framework for examining global automotive supply chains spanning 2017 to 2023. The research particularly emphasizes the identification of critical risk sources through both static and dynamic analytical perspectives. The static analysis employs multilayer degree and strength centralities to illuminate the pivotal roles that countries such as China, the United States, and Germany play within these multilayer automotive supply networks. Conversely, the dynamic risk propagation model uncovers significant cascade effects; a disruption in a major upstream supplier can propagate through intermediary layers, ultimately impacting over 85% of countries in the finished automotive layer within a short temporal threshold. Furthermore, this study investigates how individual nations’ anti-risk capabilities influence the overall resilience of multilayer automotive supply networks. These insights offer valuable guidance for policymakers, enabling strategic topological modifications during disruption events and enhanced protection of the most vulnerable risk sources.
Yue et al. (Thu,) studied this question.
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