Abstract: [Purpose/Significance] The phenomenon of algorithmic malpractice causes general algorithmic anxiety and even algorithmic crisis. Understanding the occurrence process and formation mechanism of user algorithmic coping behavior is helpful to the healthy development of artificial intelligence. [Design/Methodology] Based on the the coping theory, this study constructs a U-shaped influence model of algorithmic anxiety on algorithmic avoidance among intelligent recommendations users. A total of 351 valid questionnaires are collected through a survey, and data analysis and hypothesis testing are conducted using hierarchical regression analysis and the MEDCURVE macro program. [Findings/Conclusion] There is a U-shaped relationship between algorithmic anxiety and algorithmic avoidance, as well as between algorithmic resistance and algorithmic avoidance; algorithmic resistance plays a mediating role in the U-shaped relationship between algorithmic anxiety and algorithmic avoidance; algorithmic awareness positively moderates the relationship between algorithmic anxiety and algorithmic avoidance, making the U-shaped curve steeper when users have higher algorithmic awareness, and flatter when they have lower algorithmic awareness; algorithmic awareness does not moderate the effect of algorithmic anxiety on algorithmic resistance. [Originality/Value] This study clarifies the complex dynamic relationship between algorithmic anxiety and algorithmic coping behavior, providing a theoretical foundation and practical guidance for optimizing platform algorithmic services, implementing differentiated user management, and enhancing users' algorithmic adaptability, and thereby contributing to the development of the algorithmic application ecosystem.

Keywords: Algorithmic anxiety, Algorithmic resistance, Algorithmic avoidance, Algorithmic awareness, Intelligent recommendation, Coping theory