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Intelligent-driven resilience enhancement: Nonlinear impacts and spatial spillover effects of AI penetration on China’s NEV industry chain

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  • Yang, Qiong
  • Liu, Haibin

Abstract

As a key representative of China’s strategic emerging industries, the new energy vehicle (NEV) industry has demonstrated resilience in addressing global industrial risks and external shocks. Against the backdrop of a new technological revolution, the penetration of Artificial Intelligence (AI) plays a vital role in strengthening industrial chain resilience and ensuring stable economic operations. This paper, through theoretical deduction and empirical analysis using data from 563 listed companies between 2015 and 2023, systematically examines the nonlinear impact of AI penetration on NEV industry chain resilience, further exploring its spatial spillover effects. The findings indicate that AI penetration exerts an inverted U-shaped influence on the resistance, recovery, renewal capacities, and overall resilience of the NEV industry chain, with the average effect not yet surpassing the inflection point. This influence exhibits significant heterogeneity across different levels of economic development, pandemic stages, firm ownership, and industry chain segments. The dynamic spatial Durbin model confirms that the impact of AI penetration on the resilience of the NEV industry involves complex spatial spillover effects and spatial heterogeneity. The study provides policy recommendations for guiding AI application, fostering regional collaborative development, and optimizing industrial chain layouts, thereby enhancing the industry’s capacity to withstand external risks and promoting the high-quality development of China’s NEV sector.

Suggested Citation

  • Yang, Qiong & Liu, Haibin, 2025. "Intelligent-driven resilience enhancement: Nonlinear impacts and spatial spillover effects of AI penetration on China’s NEV industry chain," Technology in Society, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:teinso:v:81:y:2025:i:c:s0160791x2500017x
    DOI: 10.1016/j.techsoc.2025.102827
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