Research on the innovation performance of NEV enterprises driven by AI technology: an empirical study based on China’s NEV industry

Purpose This paper aims to empirically test the impact and mechanisms of artificial intelligence (AI) technology on the innovation performance of new energy vehicle (NEV) enterprises, using data from A-share listed companies in China’s NEV industry. It also explores the role of dynamic capabilities, particularly innovation, absorptive and adaptive capacities, in mediating this relationship. Design/methodology/approach The study establishes indicators to measure the drive of AI technology and employs empirical analysis to examine its effect on the innovation performance of NEV enterprises. The research employs heterogeneity tests to assess the differentiated impact of macro-environmental factors and micro-enterprise characteristics on the innovation performance of NEV companies. Findings The study finds that AI technology significantly enhances the innovation performance of NEV enterprises. Dynamic capabilities, particularly innovation capability, play a crucial mediating role in this relationship. Among the dynamic capabilities, innovation capability has the most significant mediating effect, followed by absorptive capacity, while adaptive capacity has the least effect. Heterogeneity tests reveal that macro-environmental factors (e.g. market elements) and micro-enterprise characteristics (e.g. R&D backgrounds of directors, senior management and property rights attributes) differentially impact the innovation performance of NEV enterprises driven by AI. Originality/value This paper provides both theoretical explanations and empirical evidence on how AI technology enhances the innovation performance of NEV enterprises. It offers valuable insights for policymakers on promoting intelligent transformation and achieving high-quality sustainable development within the NEV industry.