Enhancing Cross-Border Logistics Resilience through AI Investment: A Cost Optimization Perspective
Abstract
Global supply chains face increasing cross-border disruption risks from geopolitical uncertainty, congestion, customs delays and
trade restrictions. This study examines how artificial intelligence, or AI, investment improves cross-border logistics resilience under disruption. Based on supply chain resilience and logistics cost optimization theories, a cost optimization model is developed in which AI investment
reduces delay costs and disruption-related losses with diminishing marginal returns. Numerical simulation shows that AI investment lowers
total logistics cost, but excessive investment may be inefficient. The optimal AI investment level increases with disruption probability, suggesting that firms should adopt dynamic and risk-oriented AI investment strategies to improve logistics visibility, disruption response and supply chain resilience.
trade restrictions. This study examines how artificial intelligence, or AI, investment improves cross-border logistics resilience under disruption. Based on supply chain resilience and logistics cost optimization theories, a cost optimization model is developed in which AI investment
reduces delay costs and disruption-related losses with diminishing marginal returns. Numerical simulation shows that AI investment lowers
total logistics cost, but excessive investment may be inefficient. The optimal AI investment level increases with disruption probability, suggesting that firms should adopt dynamic and risk-oriented AI investment strategies to improve logistics visibility, disruption response and supply chain resilience.
Keywords
Artificial Intelligence; AI Investment; Cross-Border Logistics; Supply Chain Disruption; Cost Optimization; Supply Chain Resilience
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DOI: http://dx.doi.org/10.70711/frim.v4i6.9684
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