Optimizing Supply Chain Management with AI-Driven Predictive Analytics: A Case Study Approach

Authors

  • Wei-Han Liu Department of Accounting, Hsinchu University of Management, Taiwan Author
  • Mei-Ling Chen Faculty of Business Information Systems, Hsinchu University of Management, Taiwan Author

DOI:

https://doi.org/10.5281/

Keywords:

AI-driven predictive analytics, supply chain management, demand forecasting, inventory management, predictive maintenance, route optimization.

Abstract

In the rapidly evolving business environment, optimizing supply chain management (SCM) is crucial for maintaining competitive advantage. This paper explores the application of artificial intelligence (AI)-driven predictive analytics in optimizing SCM processes. Using a case study approach, we examine how AI-powered predictive analytics can enhance decision-making, improve efficiency, and reduce costs in supply chains. The findings demonstrate the potential of AI to revolutionize SCM by providing actionable insights and enabling proactive management strategies.

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Published

2024-08-30

Issue

Vol. 2 No. 1 (2024): First Issue

Section

Articles

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