This study aims to investigate how ethical considerations—including security, privacy, non-deception, and fulfillment—in generative artificial intelligence (GenAI) affect users’ intentions to continue its usage. We developed a theoretical framework using a mixed-methods design that integrates “partial least squares structural equation modeling” (PLS-SEM) and “fuzzy-set qualitative comparative analysis” (fsQCA) to understand this impact. The PLS-SEM findings indicate that the ethical aspects of GenAI (security, privacy, non-deception, and fulfillment) positively influence users’ perception of GenAI identity, which in turn positively affects their intentions for continued usage. Additionally, fsQCA identifies three configurations that lead to users’ continued usage of GenAI. This study enriches the AI ethics framework by comprehensively analyzing ethical perceptions in GenAI, focusing on security, privacy, non-deception, and fulfillment. Moreover, by exploring GenAI’s ethical impact on user behavior, this study offers important insights for the responsible adoption of GenAI.
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