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人工智能应用与制造业企业供应链韧性提升OACHSSCD

Artificial Intelligence Applications and Enhancing Supply Chain Resilience in Manufacturing Enterprises

中文摘要英文摘要

提升制造业企业供应链韧性是推动制造业企业高质量发展的重要举措,而人工智能的创新应用为实现该目标提供了新路径.基于2011-2023 年制造业A股上市公司数据,以国家人工智能创新应用先导区设立为准自然实验,采用多期双重差分法,实证检验人工智能应用对制造业企业供应链韧性的影响.研究发现:先导区政策能够显著提升制造业企业供应链韧性,该结论经过稳健性检验后依然成立;该政策通过促进企业数字化转型、提高企业全要素生产率和创新水平三条传导路径来提升制造业企业供应链韧性;异质性分析显示,该政策效果在非国有企业、高市场竞争企业、高技术制造业企业中更突出.

Enhancing the supply chain resilience of manufacturing enterprises constitutes a crucial measure for advancing their high-quality development,with innovative applications of artificial intelligence offering novel pathways to achieve this objective.Drawing upon data from A-share listed manufacturing companies spanning 2011 to 2023,this study employs a natural experiment defined by the establishment of national artificial intelligence innovation pilot zones.Utilizing a multi-period difference-in-differences approach,it empirically examines the impact of AI adoption on supply chain resilience within manufacturing firms.The findings reveal that the pilot zone policy significantly enhances supply chain resilience in manufacturing enterprises,a conclusion that remains robust after stability testing.This policy improves supply chain resilience through three transmission channels:accelerating digital transformation,elevating total factor productivity,and strengthening innovation capabilities.Heterogeneity analysis indicates that the policy effect is more pronounced among non-state-owned enterprises,highly competitive markets,and high-tech manufacturing firms.Further analysis reveals that the policy significantly enhances both supply chain resilience and supply chain efficiency in manufacturing enterprises.Recommendations include deepening the integration of artificial intelligence with supply chains,implementing targeted policy support,and strengthening supply chain risk-resistance capabilities.

吕康银;张恒瑞;刘乐乐

东北师范大学 经济与管理学院,吉林 长春 130117东北师范大学 经济与管理学院,吉林 长春 130117东北师范大学 经济与管理学院,吉林 长春 130117

管理科学

人工智能制造业企业供应链韧性企业数字化转型企业全要素生产率企业创新

artificial intelligencesupply chain resilience in manufacturing enterprisesenterprise digital transformationtotal factor productivity of enterprisescorporate innovation

《经济与管理》 2026 (2)

28-35,8

教育部人文社科研究规划基金项目(24YJAZH103)

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