Intelligent Decision-Making for Smart E-Commerce

The rapid transformation of conventional e-commerce into intelligent, adaptive, and data-driven environments has fundamentally changed how digital businesses make decisions. In Smart E-Commerce, the increasing availability of customer, product, transaction, and market data creates new opportunities for Artificial Intelligence (AI) to support and automate complex decision processes. However, the value of these data depends not only on analytical capabilities but also on the ability of intelligent systems to translate heterogeneous and continuously changing information into timely and effective business decisions. Intelligent Decision-Making therefore represents a critical foundation for the development of next-generation e-commerce platforms. This review examines the evolving role of intelligent decision-making in Smart E-Commerce, with particular emphasis on AI-driven prediction, personalization, recommendation, optimization, and adaptive decision processes. The review discusses the contribution of machine learning, deep learning, reinforcement learning, generative AI, and large language models to different stages of the e-commerce decision-making process. Key applications, including intelligent product recommendation, customer behavior prediction, personalized customer experiences, dynamic pricing, demand forecasting, and business optimization, are comparatively examined. The review further identifies major research challenges associated with data heterogeneity, model generalization, computational efficiency, rapidly changing customer preferences, and effective human-AI collaboration. Finally, emerging paradigms such as generative AI, multimodal intelligence, AI shopping agents, and increasingly autonomous decision-making are discussed as important directions for future Smart E-Commerce systems. Overall, the literature indicates a gradual transition from predictive and recommendation-oriented systems toward adaptive decision architectures capable of continuously learning from changing market and customer contexts and supporting more intelligent business decisions.

کلیدواژه ها:

Smart E-Commerce ، Intelligent Decision-Making ، Artificial Intelligence ، Intelligent Recommendation