The Role of Artificial Intelligence in Supply Chain Efficiency for Manufacturing Firms

关键词:

摘要

This study explores the impact of artificial intelligence (AI) applications on supply chain efficiency in manufacturing firms. As global markets become more volatile, manufacturers are increasingly adopting AI technologies to optimize operations, reduce costs, and enhance responsiveness. Using data from 120 medium-to-large manufacturing companies across Europe and Asia, we analyze the effects of AI-driven predictive analytics, demand forecasting, and inventory management systems on key efficiency metrics: order fulfillment rate, inventory turnover, and lead time. The results show that firms integrating AI into supply chain processes achieve 28% higher inventory turnover, 19% shorter lead times, and 15% higher order fulfillment rates compared to non-adopters. Predictive analytics for demand forecasting emerges as the most impactful AI tool, reducing stockouts by 32%. Additionally, the benefits of AI are more pronounced in firms with complex, global supply chains. These findings highlight that strategic AI implementation can serve as a critical competitive advantage for manufacturers seeking to navigate market uncertainties.

文献引用

• 4.Davenport, T. H., & Kalakota, R. (2019). The potential of artificial intelligence in supply chain management. MIT Sloan Management Review, 60(4), 53–62. 5.Wang, Y., Gunasekaran, A., & Ngai, E. W. T. (2021). Artificial intelligence for supply chain resilience: A systematic literature review. International Journal of Production Economics, 232, 107921. 6.Fosso Wamba, S., & Queiroz, M. M. (2019). Big data analytics and supply chain performance: A systematic literature review. Annals of Operations Research, 274(1), 235–254.