Transformational leadership and employee voice: a model of proactive motivation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Drawing on the model of proactive motivation, the purpose of this paper is to examine how transformational leadership influences followers’ voice behavior through three proactive motivation states, namely, “reason to,” “can do” and “energized to.” It also examines the moderating role of followers’ proactive personality in the relationship between transformational leadership and employee voice. Design/methodology/approach The online survey was distributed through Qualtrics using a two-wave design. In total, 1,454 participants completed the survey at Time 1, of those 447 also completed the survey at Time 2. Findings Transformational leadership influences employee voice via followers’ promotion focus, role-breadth self-efficacy and affective commitment. Followers’ proactive personality attenuates the impact of transformational leadership on voice, supporting the substitute for leadership hypothesis. Research limitations/implications Self-reported data are the main limitation of the present study. Other limitations include treating employee voice as a unidimensional construct and oversimplifying the impact of positive affect on voice. Practical implications The present study suggests that training managers to demonstrate more transformational leadership behavior, enhancing employees’ proactive motivation and hiring proactive individuals are strategies to facilitate employee voice. Originality/value The present study contributes to a better understanding of employee voice from a proactive motivation perspective. It also demonstrates that followers’ proactive personality is important “boundary condition” to transformational leadership.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it