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This research article explores the optimization of e-commerce supply chains through demand prediction for new products using machine learning techniques. It discusses the design and implementation of a machine learning model that integrates survey data and hypothesis-based inputs to enhance demand forecasting accuracy, ultimately guiding supply chain decisions. The study highlights the potential of machine learning to improve operational efficiency and customer satisfaction in the rapidly evolving e-commerc

Author

jaimld.urfpublishers

Language

EN