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Artificial Intelligence Development and Corporate Supply Chain Restructuring: Evidence from China
Applied Economics. 2026. P. 1–20.
In press
Whether artificial intelligence (AI) can enable firms to break free from supply chain path dependence and achieve diversification remains a critical question for reconciling efficiency and security. Using data from Chinese listed firms (2012–2024) and a staggered difference-in-differences model, we find that the AI pilot policy significantly promotes supply chain diversification. Drawing on Transaction Cost Economics and Agency Theory, we show that AI disrupts supply chain lock-in by mitigating internal agency costs, reducing external switching costs, and intensifying market competition. This effect is more pronounced in firms with fewer non-local subsidiaries, a robust internal digital foundation, and those in highly marketized regions. Furthermore, we demonstrate that AI-driven diversification fosters “strategic resilience”, it simultaneously boosts total factor productivity and alleviates perceived disruption risks. Our findings offer novel evidence of how digital governance empowers the real economy, underscoring AI’s role in harmonizing supply chain resilience and efficiency.
Research target:
Economics and Management
Political Science, International Relations, and Public Administration
Language:
English
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