Background and Aim: This study investigates the key factors influencing the adoption and continued use of smart classroom technology among higher education faculty members. Grounded in the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT2), and Expectation-Confirmation Model (ECM), this research examines the relationships between Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Social Influence (SI), Facilitation Conditions (FC), Personal Innovativeness in Information technology (PIIT), Satisfaction (SAT), and Continuance Intention (CI). Theoretically, it extends the application of technology adoption models in the higher education context by confirming the mediating role of satisfaction and the moderating influence of social and institutional factors. Practically, the findings offer actionable insights for policymakers, university administrators, and technology developers to design more user-friendly smart classroom systems, enhance faculty training, and develop policies that foster long-term engagement with technology-enhanced teaching. This study seeks to investigate the key elements impacting the adoption of smart classroom technologies among university educators, offering substantial value for advancing the integration of digital transformation outcomes in education. Materials and Methods: A quantitative research design was employed, collecting data from university faculty members with experience using smart classrooms. The study was grounded in the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT2), and Expectation-Confirmation Model (ECM). Key variables examined included Perceived Ease of Use, Perceived Usefulness, Social Influence, Facilitation Conditions, Personal Innovativeness, Satisfaction, and Continuance Intention. The data were analyzed utilizing SPSS and AMOS software, with confirmatory factor analysis (CFA) and structural equation modeling (SEM) applied to evaluate construct validity, reliability, and inter-construct relationships. Results: The findings reveal that PEOU and PU significantly influence faculty satisfaction, which in turn plays a mediating role in continued use intentions. Furthermore, SI and FC positively impact CI, emphasizing the importance of institutional support and peer collaboration in sustaining technology adoption. PIIT was also found to be a critical predictor of CI, highlighting the role of individual technological adaptability. This study provides both theoretical and practical contributions. Conclusion: This research examined a sample of faculty members and identified the primary determinants of their engagement with smart classroom tools. Overall, this study achieved its objectives by verifying that Perceived Ease of Use, Perceived Usefulness, Social Influence, Facilitation Conditions, Personal Innovativeness, and Satisfaction are the key determinants of faculty members’ willingness to continue using smart classrooms. These findings provide valuable insights for educators, administrators, and technology developers, offering practical guidelines for optimizing digital teaching strategies and institutional policies.
Yuan et al. (Thu,) studied this question.