Impact of transformational leadership on employees’ affective commitment and intention to support change: Mediation role of innovative behavior

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Given the dynamic business world and influential trends shaping how companies function, resulting in resistance, anxiety, and confusion, thereby affecting employees’ performance and well-being, it is crucial to adopt an effective leadership approach. This study aims to explore how transformational leadership impacts employees’ affective commitment and their intentions to support change, considering the role that innovative behavior can play in this relationship. A quantitative approach was used based on an online survey of 401 employees working in marketing consulting, business consulting, transportation, and IT service companies in Hungary. These employees had to go through different organizational changes, such as transformation in structure and emergence of new technology innovation. The hypotheses were tested using structural equation modeling.
The study unveiled that transformational leadership significantly and positively impacts employees’ affective commitment toward organizational change but does not have any significant relationship with their intention to support it. However, overall, transformational leadership is a catalyst for employees’ responses to change situations. In addition, the intermediary role of employees’ innovative behavior in the association between transformational leadership and employees’ responses to change was confirmed as transformational leadership positively affects employees’ innovative behavior, affective commitment, and intentions to support change. With innovative behavior, the significant positive relationship between leadership and employees’ reactions to change remained effective. Transformational leadership and active team member engagement in innovation can facilitate the acceptance of change initiatives, alleviate business complexity, and foster collective efforts for individual and organizational success.

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    • Figure 1. Research model
    • Figure 2. Model estimations
    • Figure 3. Direct relationships
    • Table 1. Sample characteristics
    • Table 2. Convergent validity, measurement models, and reliability
    • Table 3. Discriminant validity (Fornell-Larcker criterion)
    • Table 4. Heterotrait-monotrait ratios (HTMT)
    • Table 5. Model analysis
    • Conceptualization
      Khadija Aya Hamza
    • Investigation
      Khadija Aya Hamza, Ildiko Rudnak
    • Methodology
      Khadija Aya Hamza, Ayman Alshaabani
    • Project administration
      Khadija Aya Hamza, Ildiko Rudnak
    • Resources
      Khadija Aya Hamza, Ayman Alshaabani, Ildiko Rudnak
    • Validation
      Khadija Aya Hamza, Ayman Alshaabani, Ildiko Rudnak
    • Visualization
      Khadija Aya Hamza, Ayman Alshaabani, Ildiko Rudnak
    • Writing – original draft
      Khadija Aya Hamza
    • Writing – review & editing
      Khadija Aya Hamza, Ayman Alshaabani, Ildiko Rudnak
    • Data curation
      Ayman Alshaabani
    • Formal Analysis
      Ayman Alshaabani
    • Software
      Ayman Alshaabani
    • Funding acquisition
      Ildiko Rudnak
    • Supervision
      Ildiko Rudnak