How Generative Artificial Intelligence Adoption Enhances Firm-Level Supply Chain Resilience: Empirical Evidence from Chinese A-Share Listed Firms
DOI:
https://doi.org/10.62051/ijgem.v10n6.03Keywords:
Generative artificial intelligence, Supply chain resilience, Technological innovation, Supply chain concentration, Organizational reconfigurationAbstract
Escalating global supply chain risks and rapid AI diffusion have elevated supply chain resilience (SCR) to a critical strategic imperative, yet whether and how generative artificial intelligence (GAI) adoption enhances firm-level SCR remains underexplored. Drawing on a panel dataset of Chinese A-share listed firms spanning 2017–2024, we quantify GAI adoption through systematic text analysis of annual reports, construct a composite SCR index via the entropy weight method, and estimate a two-way fixed effects model incorporating Bartik shift-share instrument and lagged province-by-industry mean instrumental variables to address endogeneity concerns. We find that GAI adoption significantly enhances firm-level SCR. Mechanism analysis reveals three positive transmission pathways: technological innovation, organizational investment intensification, and downstream customer structure optimization. It also uncovers a suppression effect operating through upstream supplier concentration, exposing an inherent trade-off between flexibility gains and coordination stability losses. Collectively, these findings indicate that GAI's SCR-enhancing effect is not automatic, but depends critically on the alignment between technological deployment and organizational adaptation, offering actionable implications for firms' GAI investment strategies in supply chain management.
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