An Empirical Examination of the Novel Approach to Increase Supply Chain Resilience and Performance with a Disruption due to the Flowing Effect on Demand Using technology Platform Developed for Artificial Intelligence-driven Innovation

Abstract

In this age of growing global competition, supply chain resilience and efficiency cannot be compromised. The study contributes new knowledge by exploring the role of artificial intelligence (AI) driven innovations to improve both supply chain resilience and performance, particularly under dynamic conditions in a connected network. The study applies empirical research to explore ways in which 3 AI technologies - machine learning, predictive analytics and autonomous systems can help alleviate the effects of supply chain disruptions, thus improving overall effectiveness. The research benchmarks the deployment of AI tools into real-time supply chain management, risk assessment and decision-making processes by leading companies in different industrial sectors. Results show that the magnitude of improvement in predictive power, response time and operational agility could empower a supply chain to operate with confidence while also enjoying diminutions in service disruptions. In short, the results of this research show that AI could be a powerful lever for sustainable supply chain strategies upon which SHM researchers and policymakers can now start to act.