The new energy vehicle industry is of great significance to the implementation of the “dual-carbon” policy in China. To identify the risk spillover mechanism of China’s new energy automobile industry chain under crisis events, DCC-GJR-GARCH-MES model, complex network analysis and interpretable machine learning are introduced to identify the tail risk spillover mechanism and time-varying drivers of new energy automobile firms from the industry chain perspective. It is found that: (1) The risk spillover of enterprises in different links of the industrial chain is heterogeneous, with upstream enterprises having higher systemic risk than midstream and downstream enterprises. (2) Different links in the industrial chain, risk transmission paths, and core transmission nodes vary across crisis events. (3) Risk drivers in the industrial chain exhibit significant time-varying characteristics. During the entire sample period, enterprise size, interconnectedness, and investor attention were the key drivers of systemic importance. The conclusion of the study reveals the unique vulnerability and coping mechanism of each link in China's new energy automobile industry chain in the face of external shocks, which provides an important basis for further optimizing the risk management strategy of the new energy automobile industry chain.
Zheng et al. (2026) studied this question.