THE INFLUENCE OF TRANSFORMATIONAL LEADERSHIP AND AGILE LEARNING ON LECTURERS’ INNOVATION PERFORMANCE AT MERCU BUANA UNIVERSITY, JAKARTA, INDONESIA

Abstract

Amid accelerating digital transformation in Indonesian higher education, this study examines how transformational leadership and agile learning jointly shape lecturers’ innovation performance. Adopting a quantitative design with Structural Equation Modeling–Partial Least Squares (SEM-PLS), we surveyed 199 permanent lecturers at Universitas Mercu Buana to test a model in which transformational leadership exerts both direct and indirect effects on innovation through agile learning. Transformational leadership is theorized to build a compelling vision, stimulate intellectual curiosity, and provide individualized support; agile learning is framed as an adaptive capability that promotes rapid sense-making, experimentation, and continuous improvement. The analysis indicates that transformational leadership significantly enhances innovation performance and also strengthens agile learning, which in turn positively predicts innovation, evidencing partial mediation. The findings advance theory by integrating agile learning into innovation performance models for higher education and by clarifying the mechanism through which leadership translates into innovative work outcomes. Practically, the results suggest that university leaders should pair vision-driven leadership with learning architectures that enable flexibility—such as iterative curriculum development, micro-credentialing, and data-informed feedback loops to help lecturers respond effectively to technological and pedagogical change. Investment in leadership development and structured agile learning opportunities can therefore foster resilient, adaptive, and innovative academic cultures. Overall, by demonstrating the complementary roles of transformational leadership and agile learning, this study offers an actionable pathway for Indonesian universities seeking to accelerate innovation during digital transformation initiatives while maintaining academic quality and relevance. Future research should expand to multi-institution samples across regions and mixed-methods designs to validate and enrich insights.