Personalized recommendation information services in e-commerce platforms can help users get the information they need faster. Still, users also worry about the risk of privacy disclosure and illegal use. Users' willingness to adopt personalized recommendation information on e-commerce platforms and its influence mechanism is unclear. This paper explores how users weigh the conflict between convenience and privacy risks brought by personalized recommendation, builds an influencing factors model of the willingness to adopt personalized recommendation information on ecommerce platforms, and uses structural equation modeling (SEM) for analysis and verification. The results show that the perceived privacy risk negatively influences the adoption willingness, but the impact level is lower than expected. The adoption willingness of personalized recommendation information is more influenced by its usefulness.