Research on the impact of core enterprises' artificial intelligence on risk-taking levels of upstream and downstream enterprises: A transaction cost theory perspective

Against the backdrop of artificial intelligence technologies' integration into supply chain management, examining the technological spillover effects of core enterprises’ artificial intelligence capabilities can provide critical support for risk management across the supply chain. Based on panel data from Chinese listed companies between 2010 and 2023, this empirical study investigates the impact of core enterprises' artificial intelligence capability on the risk-taking levels of upstream and downstream firms, along with the underlying mechanisms and heterogeneity. The results indicate that strong artificial intelligence capabilities in core enterprises enhance the risk-taking propensity of associated firms, with information asymmetry, coordination cost of supply and demand, and bargaining power within the supply chain serving as mediating factors. Heterogeneity analysis reveals that the positive effect of core enterprises’ artificial intelligence on elevating risk-taking is more pronounced when market competition is less intense, and when the core enterprise interacts with non-state-owned suppliers or state-owned customers. From a holistic supply chain perspective, this effect is stronger under conditions of higher supply chain transparency and shorter geographical distance among entities. Grounded in transaction contingency theory, this research elucidates the technological spillover role of core enterprises’ artificial intelligence from a micro-level supply chain viewpoint, offering practical insights for supply chain risk management.