Guo Xiaochuan, Chen You, Xie Jiaping, Wang Huiyan, Lei Xue
Shanghai University, Shanghai, China.
Shanghai University of Finance and Economics, Shanghai, China.
Sci Rep. 2025 Aug 25;15(1):31177. doi: 10.1038/s41598-025-17138-3.
Artificial intelligence (AI) is fundamentally reshaping supply chain operation modes and innovation paths, which has a significant impact on the development of supply chain resilience. This study utilizes panel data of Chinese A-share listed manufacturing companies from 2013 to 2022 to measure the application of AI through textual analysis and construct firm-level supply chain resilience indicators using factor analysis. The main findings suggest that AI greatly enhances supply chain resilience in the Chinese manufacturing industry, and this result holds in a series of robustness tests. Second, AI improves supply chain resilience through changes in organizational structure and improvements in internal control systems. Further, the impact of AI on supply chain resilience varies by industry characteristics and firms' position in the supply chain. Finally, the technological maturity and depth of AI application within a firm also affects supply chain resilience differently. This study contributes to the research on the application of AI in supply chain management and the theory of supply chain resilience, as well as provides a theoretical foundation and practical insights for manufacturing firms to enhance their own resilience in the face of increasing global uncertainty and complexity.
人工智能（AI）正在从根本上重塑供应链运营模式和创新路径，这对供应链弹性的发展具有重大影响。本研究利用2013年至2022年中国A股上市制造业企业的面板数据，通过文本分析来衡量人工智能的应用情况，并使用因子分析构建企业层面的供应链弹性指标。主要研究结果表明，人工智能极大地增强了中国制造业的供应链弹性，这一结果在一系列稳健性检验中均成立。其次，人工智能通过组织结构的变化和内部控制系统的改进来提高供应链弹性。此外，人工智能对供应链弹性的影响因行业特征和企业在供应链中的地位而异。最后，企业内部人工智能应用的技术成熟度和深度也对供应链弹性产生不同的影响。本研究为人工智能在供应链管理中的应用研究和供应链弹性理论做出了贡献，同时也为制造企业在面对日益增加的全球不确定性和复杂性时增强自身弹性提供了理论基础和实践见解。
