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R. Kurniasih

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Conference Open access Aug 2026

Driving Employee Innovation Through Transformational Leadership: The Roles of Leader Member Exchange and Knowledge Sharing Behavior

Employee innovation has become a critical factor for organizational sustainability and competitiveness, particularly in the banking sector, which faces increasing demands for service excellence, digital transformation, and operational efficiency. This study aims to examine the influence of transformational leadership on innovative work behavior and investigate the mediating roles of leader member exchange and knowledge sharing behavior. Drawing upon Social Exchange Theory, the study proposes that transformational leaders foster high-quality relationships with employees and encourage knowledge sharing practices, which subsequently enhance employees’ innovative work behavior. A quantitative research design was employed using a survey method. Data were collected from employees of Bank BJB Tegal Branch through structured questionnaires, and the proposed relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS SEM). The findings indicate that transformational leadership contributes to the development of innovative work behavior both directly and indirectly through leader-member exchange and knowledge sharing behavior. Furthermore, the mediating mechanisms provide a deeper understanding of how leadership practices stimulate employee innovation within the banking context. This study extends the literature on leadership and innovation by integrating relational and behavioral perspectives into a single framework. The findings also offer practical implications for banking organizations seeking to strengthen employee innovation through effective leadership, supportive workplace relationships, and a culture of knowledge sharing.

Winanti Dwi Utari, R. Kurniasih, Daryono Daryono et al. · 0 citations
Conference Open access Aug 2026

THE ROLE OF AI SELF-EFFICACY IN ACTUAL AI TOOL USE: EVIDENCE FROM AN EXTENDED TECHNOLOGY ACCEPTANCE MODEL

The findings reveal that AI self-efficacy has a positive and significant effect on perceived ease of use and perceived usefulness, and perceived usefulness significantly influence behavioral intention, which subsequently has a positive effect on the actual use of AI tools.

Alfionita Mariska Saputri, R. Kurniasih, Siti Zulaikha Wulandari et al. · 0 citations