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Khan, Rana Shehbaz (2024) AI-Powered Improvement in Inventory Management for E-Commerce Supply Chains. Masters thesis, Dublin, National College of Ireland.
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Abstract
Global supply chain issues are a major challenge today given that it is complicated to achieve strategic inventory control, cost and efficient delivery. Many times, conventional approaches can be very much ineffective when it comes to such issues, putting the operation in many problems and added expenses. In line with the research questions, this thesis seeks to determine how AI technologies such as machine learning algorithms like Random Forest and Support Vector Machine (SVM) can be implemented in improving inventory management in e-commerce supply chains. This paper aims to address this argument by pointing out that aspects such as inventory control procedures, lead time, and logistical processes can be addressed through the use of AI to cut carrying costs, improve cash flow, boost delivery effectiveness, and satisfaction levels. Based on the theoretical background and practical applications, as well as the description of specific cases and the results of experiments in the field of the use of artificial intelligence in SCM, this research offers the reader a complete understanding of the opportunities and risks associated with this process. In line with these findings, this paper reveals that AI has significant potential to revolutionize inventory management in contexts pertinent to the current context of small and medium enterprises in the emerging e-commerce market.
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