Leader–member participation! Shared leadership, organizational support and employee positive behaviors in higher educational institutions (HEIs)
Bibliographic record
Abstract
Purpose This study examines the direct and indirect effects of shared leadership on job crafting and knowledge sharing, in turn, on employee performance, commitment and creativity via organizational support among Pakistani HEI faculty members. Design/methodology/approach Drawing on shared leadership theory, data from 311 faculty members were collected. Structural equation modeling (SEM) was employed to test the hypotheses. Findings The findings revealed a significant positive influence of shared leadership on job crafting and knowledge sharing among faculty members. Job crafting and knowledge sharing also significantly and positively influenced employee performance, commitment and creativity. Shared leadership includes support dynamics, so organizational support with shared leadership failed to influence job crafting and knowledge sharing. Practical implications Institutions promoting collaborative and innovative educational environments should consider strategies to nurture shared leadership practices, facilitate job crafting and bolster knowledge-sharing. Originality/value This study underscores the importance of fostering a shared leadership culture in HEIs, emphasizing the role of job crafting and knowledge sharing in employee performance, commitment and creativity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".