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Abstract
As a passive behavior, intermittent discontinuance may lead to user defection and undermine the continuous development of generative artificial intelligence. From a cognition-affect-conation perspective, this research examined the enablers and inhibitors of generative AI user intermittent discontinuance. We adopted a mixed method of structural equation modeling and fuzzy-set qualitative comparative analysis. The results indicated that privacy concern and information hallucination influence cognitive dissonance, which further leads to intermittent discontinuance. In contrast, perceived intelligence, anthropomorphism, and personalization influence affective commitment, which prevents intermittent discontinuance. The results imply that generative AI companies need to be concerned with both cognitive dissonance and affective commitment in order to prevent user intermittent discontinuance.
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Tao Zhou
Tao Zhou is a professor at School of Management, Hangzhou Dianzi University. His work has been published in Decision Support Systems, Information Systems Management, Internet Research, Electronic Commerce Research, Computers in Human Behavior, and several other journals. His research interests include information systems and user behaviour.
Chunlei Zhang
Chunlei Zhang is a graduate student at School of Management, Hangzhou Dianzi University. He has published in Journal of Hangzhou Dianzi University. His research interests include generative AI and user behaviour.