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Artificial Intelligence for Sustainable Manufacturing: Governance Models and Supply Chain Resilience in China

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  • Jun, Shen

Abstract

The rapid advancement of artificial intelligence (AI) presents transformative opportunities for sustainable manufacturing, particularly in China, where industrial decarbonization and supply chain resilience have become critical priorities under the "dual-carbon" policy framework. However, current research lacks a comprehensive examination of how AI-enabled governance models can simultaneously enhance green manufacturing practices and strengthen supply chain resilience in emerging economies. This study addresses this gap by investigating the interplay between AI adoption, institutional governance, and resilience-building mechanisms within China's manufacturing sector. Employing a mixed-methods approach that combines policy text analysis, case studies of smart factories, and qualitative comparative analysis, the research identifies three predominant governance models: government-led regulatory frameworks, market-driven incentive systems, and technology-enabled collaborative platforms. Key findings indicate that AI-powered dynamic monitoring and decision-support systems substantially reinforce supply chain resilience, with empirical evidence showing a 23-41% improvement in order fulfillment rates among AI-integrated green manufacturers. Furthermore, the study proposes a "smart-ecological co-governance" framework that aligns technological innovation with institutional adaptation. This research contributes to the theoretical discourse on sustainable supply chain management by integrating digital governance theory with principles of industrial ecology. Practically, it offers policymakers actionable insights for promoting AI-driven green transitions, emphasizing the importance of adaptive regulatory sandboxes and cross-industry data-sharing platforms. The findings provide significant implications for developing nations seeking to reconcile economic growth with environmental sustainability through intelligent manufacturing systems.

Suggested Citation

  • Jun, Shen, 2025. "Artificial Intelligence for Sustainable Manufacturing: Governance Models and Supply Chain Resilience in China," Simen Owen Academic Proceedings Series, Scientific Open Access Publishing, vol. 2, pages 22-32.
    • Handle: RePEc:axf:soapsa:v:2:y:2025:i::p:22-32
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