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

Abstract

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.

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