The impact of leadership styles on project success: The mediating role of team collaboration
Bibliographic record
Abstract
This study investigates the impact of different leadership styles on project success, specifically examining the mediating role of team collaboration. This study utilized a diverse sample of 202 respondents representing five distinct national contexts: Jordan, Saudi Arabia, China, Australia, and the United Arab Emirates. PLS-SEM were employed to analyze the relationships between transformational leadership, transactional leadership, laissez-faire leadership, team collaboration, and project success. Our findings reveal that both transformational and transactional leadership styles are positively associated with project success. Conversely, laissez-faire leadership demonstrated a negative relationship with team collaboration but did not directly predict project success. Importantly, team collaboration was found to mediate the relationship between both transformational leadership and project success, as well as between transactional leadership and project success. However, the hypothesized mediating role of team collaboration between laissez-faire leadership and project success was not supported. These findings underscore the critical role of leadership style and team collaboration in achieving project success, offering valuable insights for organizations and project managers seeking to optimize leadership practices and foster collaborative work environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.019 |
| 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 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".