Understanding user switch of information seeking: From search engines to generative AI

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Abstract

Generative AI products such as ChatGPT have changed the way people seek and obtain information. Users may gradually switch from search engines to generative AI for information seeking. This may lead to their defection from search services. Based on the push-pull-mooring (PPM) model, this research examined user switch intention from search engines to generative AI. The results indicated that low information-task fit and information overload lead to user dissatisfaction, whereas AI generated content (AIGC) information quality and perceived interactivity affect perceived value. Dissatisfaction, perceived value, and social influence determine user switch intention. The fsQCA identified three configurations leading to switch intention. The results suggest that search service providers need to enhance information-task fit and reduce information overload in order to retain users and achieve a sustainable development.

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APA

Zhou, T., & Li, S. (2026). Understanding user switch of information seeking: From search engines to generative AI. Journal of Librarianship and Information Science, 58(1), 696–708. https://doi.org/10.1177/09610006241244800

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