Explaining loyalty to generative AI: Extending the theory of planned behavior with AI anxiety and perceived risk

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Taylor & Francis

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info:eu-repo/semantics/closedAccess

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Yönetim Bilimleri Fakültesi, İşletme Bölümü
Küresel rekabete ayak uydurmak ve sürdürülebilir olmak isteyen tüm şirketler ve kurumlar, değişimi doğru bir şekilde yönetmek, teknolojinin gerekli kıldığı zihinsel ve operasyonel dönüşümü kurumlarına hızlı bir şekilde adapte etmek zorundadırlar.

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As generative artificial intelligence (GenAI) use grows, continuance intention does notnecessarily imply loyalty. Drawing on the Theory of Planned Behavior (TPB), this studydistinguishes continuance intention from loyalty, operationalized as affective attach-ment and personal significance, and examines AI anxiety and perceived risk as predic-tors of attitude. Competing deterrence and contextual salience expectations arespecified for the risk–attitude relationship. Using PLS-SEM, we analyze data from 1,050Generation Z users in Turkey in an AI-assisted travel-planning context. AI anxietyrelates negatively to attitude, whereas perceived risk relates positively, supporting itspredicted direction without establishing contextual salience as the underlying process.Both effects are modest and explain little variance in attitude. Attitude shows thestrongest relationship with continuance intention among TPB predictors, while con-tinuance intention is strongly linked to loyalty. The study advances GenAI post-adop-tion research by distinguishing continuance intention from loyalty and contrasting theroles of AI anxiety and perceived risk.

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Generative Artificial Intelligence, User Loyalty, AI Anxiety, Perceived Risk, Theory of Planned Behavior

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International Journal of Human–Computer Interaction

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Arpacı, İ., Şahin, A., Tatoğlu, E., & Şahin, A. (2026). Explaining loyalty to generative AI: Extending the theory of planned behavior with AI anxiety and perceived risk. International Journal of Human–Computer Interaction. http://doi.org/10.1080/10447318.2026.2721886

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