Transformational Leadership and Innovative Work Behaviour: Unveiling the Mediating Roles of Job Satisfaction and Employee Engagement - F Jonathan Lucky Sasmitha; A Sobandi; Edi Suryadi; Rofi Rofaida (Journal Evaluation in Education (JEE), 2026)
Purpose of the study: This study investigates the influence of transformational leadership on innovative work behaviour among higher education lecturers, utilizing job satisfaction and employee engagement as dual mediating variables. The study aims to provide a comprehensive framework explaining how leadership stimulates innovation through motivational and psychological pathways in academic settings. Methodology: A quantitative research design was employed involving 206 lecturers selected through purposive sampling. Data were collected using a structured questionnaire and analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the structural relationships. Validity and reliability tests were conducted to ensure the robustness of the instrument. Main Findings: The results reveal that transformational leadership significantly enhances job satisfaction, employee engagement, and innovative work behaviour. Crucially, the analysis confirms that both job satisfaction and employee engagement act as significant mediators. These findings imply that transformational leaders foster innovation not only directly but effectively by boosting lecturers’ psychological well-being and engagement. Novelty/Originality of this study: This study contributes to the literature by establishing a dual-mediation model that simultaneously integrates job satisfaction and employee engagement. Unlike previous studies that often examine these mediators separately, this research offers a holistic view of the psychological mechanisms linking leadership to innovation in the higher education context. The study relies on cross-sectional data from a specific higher education sector, which limits the ability to draw causal inferences over time. Future research is encouraged to employ longitudinal designs and expand the scope to diverse geographical regions to enhance generalizability.