Artificial Intelligence and Supply Chain Resilience: Implications for Organizational Performance
Keywords:
artificial intelligence, supply chain resilience, organizational performance, predictive analytics, logistics automation, digital infrastructure capabilityAbstract
Purpose: This study examines how Artificial Intelligence enhances Supply Chain Resilience and influences Organizational Performance in disruption-prone business environments between 2020 and 2025. The research focuses on Predictive Analytics Capability, AI-driven Inventory Optimization, and Intelligent Logistics Automation in improving operational continuity, disruption management, and strategic adaptability. The study also evaluates the moderating role of Digital Infrastructure Capability.
Methods: A quantitative explanatory research design is adopted using a structured panel dataset from manufacturing and logistics firms. Moderated regression analysis is applied based on Dynamic Capability Theory and Organizational Resilience Theory.
Findings:The findings reveal that AI-enabled predictive analytics improves forecasting accuracy and disruption detection, while inventory optimization and logistics automation strengthen operational efficiency, delivery reliability, and cost reduction.The study further finds that Digital Infrastructure Capability significantly strengthens the relationship between Artificial Intelligence and Organizational Performance by improving system integration and real-time decision-making. Diagnostic and correlation analyses confirm strong positive relationships among AI capabilities, resilience measures, and organizational outcomes.
Value: The study contributes to supply chain resilience literature by presenting an integrated AI-resilience-performance framework. The findings provide managerial and policy implications for organizations seeking sustainable competitive advantage through AI-driven supply chain transformation.
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