[目的/意义]个性化算法是当代互联网电商平台推动购买转化的一种重要形式,但算法驱动的高用户参与度带来的信息过载、信息茧房等又对购买转化带来了负向影响。[方法/过程]本研究基于技术接受模型、计划行为理论等建立了个性化算法强度对高校学生购买转化的影响模型,并构建假设。采用AMOS、层次回归、Bootstrap抽样等方法探究用户参与度对高校学生购买转化产生的中介效应以及用户隐私关注度的调节效应。[结果/结论]研究发现,个性化算法强度的提升显著增强了高校学生的用户参与度;用户参与度和高校学生购买转化之间存在倒U型关系;用户参与度在个性化算法强度对高校学生购买转化影响之间起中介作用;用户隐私关注度在个性化算法强度对用户参与度的影响中起调节作用。[Purpose/Significance] Personalised algorithms are an important form of contemporary Internet e-commerce platforms to promote purchase conversion, but algorithm-driven high user engagement brings information overload, information cocoon and so on, which in turn has a negative impact on purchase conversion. [Methods/Process] This study models the influence of personalised algorithm intensity on purchase conversion of college students based on pressure interaction theory, self-control theory, etc., and constructs hypotheses. AMOS, hierarchical regression, Bootstrap sampling and other methods are used to explore the mediating effect of user engagement on purchase conversion of college students and the moderating effect of user privacy concern. [Results/Conclusions] It is found that the increase of personalisation algorithm strength significantly enhances the user engagement of college students;there is an inverted U-shaped relationship between user engagement and purchase conversion of college students;user engagement mediates the effect of personalisation algorithm strength on purchase conversion of college students;user privac
