AI-Powered Supply Chain Optimization: Enhancing eCommerce Logistics through Machine Learning
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V2I2P103Keywords:
AI, Machine Learning, Supply Chain Optimization, eCommerce Logistics, Demand Forecasting, Inventory Management, Route Planning, Predictive MaintenanceAbstract
The growth of the internet has made a large impact on prolonged distribution, leading to the evolution of the supply chain with the aim of satisfying this increased demand for faster delivery services. AI and ML are two advanced technologies that can help enhance supply chain management by automating different supply chain decisions and even reducing errors expected in traditional decision tools. In the paper, the author discusses the application of AI technologies in the specific aspects of e-commerce: demand forecasting and supply management, delivery routes optimization, and predictive maintenance. This paper explains how machine learning models can help increase supply chain efficiency and response by reviewing the current literature and the case analysis. Besides, it includes a framework for AI supply chain solutions applications and the performance of the operational consequences. Thus, the result of the study proves the efficacy of AI and ML in minimizing several operational costs, increasing shipment precision, and positively transforming the customers’ shopping experience for the e-commerce logistics industry
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