Innovative Supplier Selection Strategies in E-commerce with Machine Learning

Abstract

Enhancing Supplier Selection in E-commerce Supply Chains Using Machine Learning Supplier selection is a critical decision-making process in e-commerce supply chains, directly affecting cost, quality, and lead time. This research reviews how machine learning algorithms, including decision trees, neural networks, and clustering techniques, are used to evaluate suppliers based on performance metrics like reliability, quality, and cost. However, existing models often overlook non-traditional data sources, such as social media sentiment or geopolitical risks, which can influence supplier reliability. Moreover, little research has been conducted on using machine learning to dynamically adjust supplier relationships in response to changing market conditions.