智能制造与供应链韧性提升OACHSSCD
Intelligent Manufacturing and Enhancement of Supply Chain Resilience:Based on the Quasi-Natural Experiment of Intelligent Manufacturing Pilot Demonstration
在全球经济格局深度调整、国内外高度不确定经济环境下,强化供应链韧性有助于产业链供应链稳定运行,为制造业高质量发展筑牢安全底线.基于智能制造试点准自然实验,利用2011-2023年沪深A股制造业公司数据,研究智能制造对供应链韧性影响与作用机制.实证结果显示,智能制造显著提升制造业企业供应链韧性,该提升作用可通过缓解信息不对称及推动突破性创新来实现.异质性分析发现,智能制造对于高科技企业、成长期与成熟期企业、处于市场竞争程度相对较低行业和数字基础设施相对完善地区的企业具有更为显著的供应链韧性赋能效果.基于以上研究结论,从政策制定与企业层面,为推进智能制造政策深化、智能制造转型与供应链韧性增强提供参考.
Against the backdrop of profound adjustments in the global economic landscape and a highly uncertain domestic and international economic environment,strengthening supply chain resilience is crucial for ensuring the stable operation of industrial chains and supply chains,and for safeguarding the high-quality development of the manufacturing industry.This study leverages the quasi-natural experiment of intelligent manufacturing pilots and uses data from manufacturing companies listed on the Shanghai and Shenzhen A-share markets between 2011 and 2023 to explore the impact of intelligent manufacturing on supply chain resilience and its underlying mechanisms.Empirical results confirm that intelligent manufacturing significantly enhances the supply chain resilience of manufacturing enterprises,primarily by alleviating information asymmetry and promoting breakthrough innovation.Heterogeneity analysis reveals that intelligent manufacturing exerts a more pronounced effect on supply chain resilience for high-tech enterprises,enterprises in growth and mature stages,enterprises in industries with relatively low market competition,and those located in regions with relatively complete digital infrastructure.Based on these findings,this study provides references for deepening intelligent manufacturing policies,advancing intelligent manufacturing transformation,and enhancing supply chain resilience from both policy-making and enterprise perspectives.
戚孟强;何卫红
南京邮电大学 管理学院,江苏 南京 210003南京邮电大学 管理学院,江苏 南京 210003
管理科学
智能制造供应链韧性政策效果评估双重差分模型
intelligent manufacturingsupply chain resiliencepolicy effect evaluationdifference-in-differences(DID)model
《科学与管理》 2026 (3)
26-34,9
江苏省研究生科研与实践创新计划项目(KYCX25_1251)
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