Research on the Impact Factors of New Energy Vehicle Supply Chain Resilience under Industrial Interconnection

Abstract

With the deepening evolution of industrial internet, the supply chain of new energy vehicles (NEVs) is undergoing a transformation from closed vertical manufacturing to an open, collaborative multidimensional ecosystem. The risk characteristics and resilience demands faced by this sector are being profoundly reshaped. Existing literature predominantly focuses on the general resilience of traditional manufacturing, with limited systematic analysis of resilience influencing factors and transmission mechanisms in the digital interconnection context of NEVs’ technology-intensive industry. To address this, this paper proposes an unstructured data mining and analysis framework integrating Latent Dirichlet Allocation (LDA) and Interpreted Structural Model (ISM). Using policy documents and industry reports from 2020 to 2025 as the corpus, the study extracts six core themes influencing systemic resilience through LDA: digital collaboration and platform services, core component supply and R&D, logistics networks and transportation support, risk early warning and emergency response, macro-environment and policy guidance, and partnerships and ecosystem co-construction. Building upon this, DEMATEL and ISM methods are employed to construct a multi-layered structural model revealing the inherent hierarchical logic among elements. Results demonstrate that macro-environment and policy guidance serve as fundamental driving forces; digital platforms and ecosystem co-construction act as pivotal enabling mechanisms; component supply and logistics networks provide intermediate support at the physical entity level; while risk early warning and emergency response directly manifest resilience capabilities at the top tier. This study expands the measurement dimensions of supply chain resilience from the perspective of massive text, providing a solid theoretical basis for leading enterprises in the new energy vehicle industry chain to optimize risk resistance strategies and for policy-making departments to improve top-level design in the digital ecosystem.