When algorithms fail us: perceived algorithmic ineffectiveness, psychological reactance, and implicit personality as drivers of algorithm aversion behavior on short-form video platforms

Abstract While extensive research has identified the drivers of algorithm aversion, the influence of users’ subjective perceptions remains largely underexplored. This study investigates the psychological mechanisms linking perceived algorithmic ineffectiveness to algorithm aversion behavior, proposing psychological reactance as a mediator and implicit personality as a moderator. Data were collected from 733 users of a Chinese language short-form video platform called Douyin, known as TikTok in other regions. The results show that (1) perceived algorithmic ineffectiveness positively predicts algorithm aversion behavior, (2) psychological reactance partially mediates this relationship, and (3) implicit personality moderates the link between perceived algorithmic ineffectiveness and psychological reactance, with the effect being stronger for incremental theorists than for entity theorists. These findings establish perceived algorithmic ineffectiveness as a key driver of algorithm aversion, contributing to the current literature on the psychological underpinnings of algorithm aversion behavior.