ANALISIS PENGARUH INSTITUTIONAL SUPPORT TERHADAP JOB SATISFACTION MELALUI AI-ENHANCED INNOVATION MENGGUNAKAN STRUCTURAL EQUATION MODELING - muhammad galih wonoseto; Imam Riadi; Rusydi Umar (LPPM Universitas Abdurrab, 2026)
Lecturers are at the forefront of implementing Artificial Intelligence in higher education. Although research on AI adoption continues to grow, most studies are still dominated by the Technology Acceptance Model, which primarily focuses on technology acceptance. Research examining the role of AI-Enhanced Innovation as a mechanism linking institutional support and work-related outcomes remains limited. Moreover, previous studies have largely focused on primary and secondary school teachers, leaving the application of AI among university lecturers underexplored. Lecturers’ readiness to utilize AI is a critical factor in the digital transformation of higher education. This study aims to examine the effect of Institutional Support on Job Satisfaction through AI-Enhanced Innovation among university lecturers. Partial Least Squares Structural Equation Modeling was employed to analyze data collected from 32 lecturers representing 17 higher education institutions in Indonesia. The results indicate that Institutional Support has a positive and significant effect on AI-Enhanced Innovation (β = 0.411; p = 0.019), while AI-Enhanced Innovation has a positive and significant effect on Job Satisfaction (β = 0.569; p < 0.001). However, the direct effect of Institutional Support on Job Satisfaction is not significant (β = 0.137; p = 0.337). These findings suggest that institutional support does not directly enhance lecturers’ job satisfaction but does so indirectly by fostering AI-based innovation in teaching and learning. AI-Enhanced Innovation fully mediates the relationship between Institutional Support and Job Satisfaction. This study contributes to the literature by integrating Institutional Support, AI-Enhanced Innovation, and Job Satisfaction into a single research model.