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As an emerging application, AI shopping has received increasing attention from both enterprises and users. Based on the push–pull–mooring (PPM) model, this research examined user switching intention from traditional online shopping to AI shopping. We conducted an online survey to collect 422 valid responses and adopted a mixed method of structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The results show that choice overload and perceived inefficiency lead to online shopping fatigue, while perceived convenience, perceived anthropomorphism, and perceived coolness affect AI shopping attractiveness. Online shopping fatigue, AI shopping attractiveness, and inertia determine user switching intention. These results provide a comprehensive understanding of the mechanism underlying user switching from traditional online shopping to emerging AI shopping. They also imply that e-commerce platforms need to mitigate online shopping fatigue and increase AI shopping attractiveness in order to expand their user base and maintain a competitive advantage.
Zhou et al. (Tue,) studied this question.