Abstract This study systematically reviews the related research on users’ algorithm aversion to artificial intelligence products. The existing literature mainly focuses on the definition and measurement of algorithm aversion, including analyzing the influencing factors of algorithm aversion from algorithm attributes, task types and individual differences, and discussing the mechanism and coping strategies of algorithm aversion. Moreover, they usually propose their own theoretical explanations for algorithm aversion based on self-serving bias, social identity theory and ordinary people theory. Accordingly, in the future, the researches on algorithm aversion can be further expanded from four aspects: the boundary exploration of algorithm aversion, the psychological root mining of algorithm aversion, the coping strategy of algorithm aversion, and the dynamic evolution of algorithm aversion.
LI You,LIANG Zhehao,CHANG Yaping. Consumers’ Algorithm Aversion to AI Products: A Literature Review and Prospect[J]. Chinese Journal of Management, 2022, 19(11): 1725-.
