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Despite the growing integration of AI in education, students often lack awareness of specialized tools, which limits their adoption and effective use. Using partial least squares structural equation modeling (PLS-SEM) and Fuzzy-set qualitative comparative analysis (fsQCA), this study aimed to investigate behavioral intentions toward DeepSeek adoption among university students. The conceptual framework of the research combines key factors from the Unified Theory of Acceptance and Use of Technology (UTAUT). A survey using a five-point Likert scale was administered to students from Pakistani universities. The study’s findings show that DeepSeek awareness has a significant impact on DeepSeek adoption, which is moderated by perceived ease of use and mediated by facilitating conditions, social influence, and performance expectancy. fsQCA further reveals configurations of factors that jointly lead to high adoption, highlighting multiple pathways rather than single causal effects. This study intends to benefit companies, academic institutions, and the global community by providing insight into how students perceive the DeepSeek services in an educational setting. The study contributes theoretically by integrating awareness into the UTAUT framework and applying fsQCA, providing a novel perspective on AI adoption in education. Finally, the conclusions of this study will help AI developers improve their product and service delivery, as well as regulators manage the usage of AI-powered bots.
Gao et al. (Thu,) studied this question.