Enhanced e-commerce decision-making using iot and machine learning

This master's thesis explores the integration of Machine Learning (ML) and Internet of Things (IoT) in e-commerce decision-making, emphasizing their potential to improve customer satisfaction and revenue. It categorizes prior research in the field, addresses challenges in data quality, privacy, and algorithmic bias, and conducts empirical experiments with various ML and Deep Learning models. This work not only contributes to the existing literature by categorizing prior research but also showcases the practical applicability of ML and IoT in e-commerce decision-making, paving the way for future advancements in this domain.