  In the rapidly evolving automotive industry, Systems-on-Chips (SoCs) are
playing an increasingly crucial role in enhancing vehicle intelligence,
connectivity, and safety features. For enterprises whose business encompasses
automotive SoCs, the sustained and stable provision and receipt of SoC relevant
goods or services are essential. Considering the imperative for a resilient and
adaptable supply network, enterprises are concentrating their efforts on
formulating strategies to address risks stemming from supply chain disruptions
caused by technological obsolescence, natural disasters, and geopolitical
tensions. This study presents an open supply knowledge extraction and
complement approach and build a supply chain network of automotive SoC
enterprises in China, which incorporates cross-domain named entity recognition
under limited information, fuzzy matching of firm entities, and supply relation
inferring based on knowledge graph. Subsequently, we exhibit the degree and
registered capital distribution across firms, and analyze the correlations
between centrality metrics in the supply chain network. Finally, based on
recovery capacity and risk transfer, two interaction disruption models (IDMs)
are developed to elucidate the adaptive behaviors and effect of network
disruptions under various business and attack strategies. This research not
only aids in exploring the complexities of Chinese automotive SoC supply chain
but also enriches our understanding of the dynamics of firm behavior in this
crucial industry sector.
