Participative leadership and team creativity: the role of team intellectual capital and colleague social support
Bibliographic record
Abstract
While previous research has explored participative leadership’s impact on creativity through various mechanisms, they have largely overlooked the role of knowledge. Drawing on the input-process-output (IPO) framework, this study proposes that team intellectual capital (TIC) is a novel key knowledge mechanism explaining the relationship between participative leadership and team creativity. Moreover, the relationship between participative leadership and TIC is moderated by colleague social support, i.e. when the levels of colleague social support is high, the relationship is greater (vs. lower). Data was collected using supervisor-subordinate paired questionnaires with a multi-source, three-wave time-lagged approach, resulting in a final sample of 735 employees and their 150 supervisors from 150 teams in China. Data analysis was conducted using path analysis in Mplus 8.3, and the results strongly supported the hypothesized relationships. Overall, this study deepens the understanding of how participative leadership influences team creativity from the perspective of knowledge (TIC), which is crucial for organizations to gain a competitive advantage.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".