Examining user switching intention between generative AI platforms: A push-pull-mooring perspective

被引:0
|
作者
Zhou, Tao [1 ]
Li, Songtao [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Management, Hangzhou 310018, Peoples R China
关键词
generative AI; switching intention; PPM; privacy risk; perceived interactivity; ONLINE PRIVACY; SERVICES; EXPERIENCE; MIGRATION; BEHAVIOR; ADOPTION;
D O I
10.1177/02666669241306735
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Due to the intense competition among generative AI platforms, users may switch from a platform to an alternative one. This may lead to user attrition and undermine the competitive advantage. The purpose of this research is to examine user switching intention between generative AI platforms based on the push-pull-mooring (PPM). Push factors include information hallucination, privacy risk, and dissatisfaction, while pull factors include perceived interactivity, perceived anthropomorphism, perceived personalization, and user experience. Mooring factor is switching costs. Both structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were used to conduct data analysis. The results validate the hypotheses. The fsQCA found that dissatisfaction is a common core condition triggering switching intention.
引用
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页数:13
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