Artificial Intelligence and Supply Chain Disruption Risks of Chinese Outward-Oriented Enterprises

JiaoYun Jiang

doi:10.63313/EBM.9179

Authors

JiaoYun Jiang Foshan University of Economics and Trade, Foshan 528000, China Author

DOI:

https://doi.org/10.63313/EBM.9179

Keywords:

Artificial Intelligence, Chinese Overseas Enterprises, Supply Chain Disruption Risk

Abstract

Against the backdrop of increasing uncertainty in the global economic and trade environment, exploring the role of artificial intelligence in reshaping the supply chain resilience of overseas enterprises and mitigating disruption risks is of great significance. Drawing on information asymmetry theory, supply chain dynamic capabilities theory, and co-evolutionary theory, this study systematically investigates the impact of AI on supply chain disruption risks of Chinese overseas enterprises using a sample of Chinese listed overseas enterprises from 2012 to 2023, employing text mining and ordinary least squares methods. The results show that AI significantly reduces supply chain disruption risks for Chinese overseas enterprises. This finding remains robust after a series of robustness checks, including instrumental variable method and Heckman two-stage estimation. The conclusions of this study help Chinese overseas enterprises develop more precise risk warning and response strategies, offering managerial insights for leveraging AI to prevent supply chain risks and ensure stable international operations.

References

[1] Zhang JD, HuoZF, Liu D, et al. Enhancing Corporate Supply Chain Resilience Driven by Artificial Intelligence[J]. Journal of Yunnan University of Finance and Economics, 2025, 41(09): 72-94.

[2] Wang SY, Liu D. Two-Sided Spillover of Artificial Intelligence and the Enhancement of Supply Chain Resilience[J]. Finance & Economics, 2025, (11): 57-72.

[3] Hu HG, Liu HJ, Zhou FK. The “Chain-Stabilizing” Effect of Artificial Intelligence: Empirical Evidence from Supply Chain Volatility[J]. Journal of Quantitative and Technical Economics, 2025, 42(10): 90-111.

[4] Xin DL, Qiu Y. Artificial Intelligence, Industrial and Supply Chain Stability, and Firm Export Resilience[J]. Economic Theory and Business Management, 2025, 45(02): 37-54.

[5] Zhang J, Zhang QL. Artificial Intelligence and Supply Chain Stabilization[J].Finance Research Letters, 2026, 109322.

[6] Li Z, Liu Q, Zhang LY. How Artificial Intelligence Innovation Reduces Supply Chain Disruption Risk[J]. China Business and Market, 2025, 39(12): 58-76.

[7] Di Vaio A, Palladino R, Hassan R, et al. Artificial intelligence and business models in the sustainable development goals perspective: a systematic literature review[J]. Journal of business research,2020,121:283-314.

[8] Li YH, Lin YX, Li DD. How the Application of Artificial Intelligence Technology Affects Firm Innovation[J]. China Industrial Economics, 2024, (10): 155-173.

[9] Choudhary V，Marchetti A, Shrestha Y R, et al. Human-AI Ensembles: When Can They Work[J]. Journal of Management,2025,51(2):536-569.

[10] Zeng DJ, Zhang Z, Liang JQ, et al. Theories and Methods of Machine Behavior and Human-Machine Collaborative Decision-Making[J]. Journal of Management Science, 2021, 34(06): 55-59.

[11] Jiang W, Wang N, Cao SP. Measurement and Application of Supply Chain Disruption Risk: An Analysis Based on Word Embedding Models[J]. Nankai Business Review, 2025, 28(04): 109-120.

[12] Yin ZF, Cao AJ, Guo JB, et al. Research on the Employment Effect of Artificial Intelligence Based on Patent Data: Microscopic Evidence from Zhongguancun Enterprises[J]. China Industrial Economics, 2023, (05): 137-154.

[13] Ren YH, Liu YZ, Li HT. Artificial Intelligence Technology Innovation and Total Factor Productivity of Firms[J]. Economic Management, 2023, 45(09): 50-67.

[14] Han Y, Xu XL. Artificial Intelligence Technology and the Upgrading of Human Capital Structure: Internal Mechanism and Empirical Test[J]. Journal of Jiangxi University of Finance and Economics, 2024, (02): 13-26.