Impact of inclusive leadership on project success through mediating role of project citizenship behavior: Project complexity as a moderator
Bibliographic record
Abstract
In today's dynamic business landscape, projects are crucial for organizational success, leading to a greater emphasis on project-based operations. While traditional measures of project success, such as cost, time, and budget, remain relevant, they are increasingly recognized as insufficient. This study investigates the influence of inclusive leadership on project success within Pakistan's construction industry, focusing on the mediating role of project citizenship behavior (PCB) and the moderating effect of project complexity. Data were collected from 644 employees across various public and private construction projects in Pakistan using a cross-sectional survey. Partial least squares structural equation modeling (PLS-SEM) was employed using SmartPLS 4 software for data analysis. The results indicate that inclusive leadership has a positive and significant impact on project success. Furthermore, project citizenship behavior positively and significantly mediates the relationship between inclusive leadership and project success. Finally, project complexity negatively and significantly moderates the relationship between inclusive leadership and project success, but not the relationship between inclusive leadership and project citizenship behavior. This study contributes to the project management literature by highlighting the importance of inclusive leadership and PCB in driving project success. It also provides practical implications for managers in construction SMEs, emphasizing the need to cultivate inclusive leadership styles and foster a supportive environment that encourages PCB. The study concludes with limitations and directions for future research, including exploring other leadership styles, moderators, and mediators, utilizing longitudinal designs, and examining smaller-scale construction subsectors.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".