The Effect of Transactional Leadership on Innovative Work Behavior: Testing the Role of Knowledge Sharing and Work Engagement as Mediation Variables
Bibliographic record
Abstract
This study, in detail, aims to explore and examine the effect of (1) transactional leadership on knowledge sharing, work engagement, and innovative work behavior; (2) knowledge sharing on innovative work behavior; (3) work engagement on knowledge sharing and innovative work behavior; and (4) knowledge sharing and work engagement in mediating the relationship between transactional leadership and innovative work behavior. The population in this study includes line managers, supervisors, and functional staff working in four stone milling companies in Central Java, Indonesia. This research is quantitative in nature, where the research data that has been collected will be processed and analyzed using structural equation modeling (SEM) based on SmartPLS 3.0 version. By analyzing 107 respondents, the results of this study conclude that (1) transactional leadership has a significant effect on knowledge sharing and work engagement, but not on innovative work behavior; (2) work engagement not only has a significant effect on knowledge sharing but also on innovative work behavior; (3) knowledge sharing has a significant effect on innovative work behavior; and (4) knowledge sharing and work engagement fully mediates the relationship between transactional leadership and innovative work behavior. This study gives a comprehensive understanding that knowledge sharing and work engagement become essential variables in linking transactional leadership and innovative work behavior.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".