Predictive Lead Time Compression in Multi-Tier Retail Networks: A Machine Learning Framework for Supplier Synchronisation

Authors

  • Carlos Murillo Professor of Industrial Engineering, Universidad Nacional Autónoma de México

Keywords:

predictive lead time compression, multi-tier retail networks, machine learning framework, supplier synchronisation

Abstract

Modern retail has embraced fast-moving fashions and new lifestyles by sequentially updating seasonal collections. In doing so, retailers are faced with increasing urgency in responding to fluctuations in demand drivers such as regional and localized fashion, weather, and new trends. Consequently, retail supply chains continue to be optimized to focus on reducing lead times, as they play a crucial role in enhancing customer satisfaction.

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Published

31-12-2025

How to Cite

[1]
“Predictive Lead Time Compression in Multi-Tier Retail Networks: A Machine Learning Framework for Supplier Synchronisation”, Blockchain Tech. & Distributed Sys., vol. 5, no. 2, pp. 26–36, Dec. 2025, Accessed: Jun. 05, 2026. [Online]. Available: https://thesciencebrigade.com/btds/article/view/861