Transformational Leadership Facilitates Innovation Capability: The Mediating Roles of Interpersonal Trust
Bibliographic record
Abstract
Innovation capability is widely accepted as an important means to attain sustain competitive advantage for firms before the rapidly changing of business environment and increasingly competitive pressure. The main goal of this study is to explore an effective way to successfully improving innovation capability for firms based on examining the relationship between transformational leadership style, interpersonal trust, and innovation capability of Vietnamese firms. The authors apply Structural Equations Modeling (SEM) to test the impacts of transformational leadership, interpersonal trust on innovation capability by using data collected from 195 participants in Vietnamese firms. The result revealed that transformational leadership and interpersonal trust significantly affect innovation capability. In addition, interpersonal trust mediates the relationship between transformational leadership and innovation capability. The findings highlights the need of practicing transformational leadership to foster employee trust and finally to enhance innovation capability for firms. The findings of this study contribute to filling the theoretical gaps which call for research on antecedent factors of innovation capability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".