Enhancing project management performance through green innovation, quality planning and strategic leadership
Bibliographic record
Abstract
This study investigates the impact of green innovation strategy on project management performance in the food sector of Saudi Arabia, examining the mediating roles of strategic quality planning and strategic leadership. Using a cross-sectional quantitative approach, data were collected in January 2025 from 341 employees through a convenience sampling technique. Structural equation modeling via SmartPLS was employed to analyze the data. Results indicate that green innovation strategy positively influences strategic quality planning (β = 0.655) and strategic leadership (β = 0.541), which in turn significantly enhance project management performance (β = 0.566 and β = 0.657, respectively). Additionally, strategic quality planning (β = 0.456) and strategic leadership (β = 0.505) partially mediate the relationship between green innovation strategy and project management performance. These findings highlight the critical role of green innovation and strategic management practices in improving project outcomes within Saudi Arabia’s food industry.
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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 | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".