From Data to Desire: How Machine Learning Shapes Consumer Decisions

This study aims to examine how purchase decisions in e-commerce are influenced by machine learning-driven personalizing recommendations and their impact on user shopping intention and shopping behavior. This study uses quantitative data which is form and gathered 257 respondents in Jabodetabek region, aged from 18 to 51 years old, these respondents have experience in shop online. This quantitative analysis uses partial least square structural equation modelling (PLS-SEM). The data was gathered by using Google Form questionnaires. Therefore, using the result of this study it reveals the machine learning in e-commerce for understanding and predicting user preferences has a significant impact on shopping behaviour which there is intention-related factors, such as online shopping experience, price, product quality, reputation and credibility, service quality, and customer engagement where it optimizes customer experience, understands behavior, and enhances business performance. These findings highlight that machine learning in e-commerce for understanding and predicting user preferences has a significant impact on shopping behavior.