The empirical relationship between success factors and dimensions
Bibliographic record
Abstract
Purpose The purpose of this paper is to report on a PhD thesis that examined the empirical relationship between a specific set of critical success factors (CSFs), project success, and success dimensions (criteria) from the perspectives of World Bank project supervisors (task managers or task team leaders) and project managers (the national project coordinators). Also, the PhD thesis author's journey and motivation are explained. Design/methodology/approach Data were collected by web questionnaires addressed to 1,421 World Bank task team leaders and paper‐based questionnaires delivered to 600 national project coordinators in 26 different countries in Africa. Principal component and confirmatory factor analyses, multiple correlation and regression analyses, as well as structural equation models were used for data analysis in this study. Findings First, research findings highlight a specific set of World Bank project CSFs (monitoring, coordination, design, training) and the existence of a second‐order latent CSF, that is World Bank project supervision. Second, they suggest that World Bank project supervision has differing significant influences on the two project success dimensions and that the first (project management (PM) success) does not significantly affect the second (deliverable success). Third, consistent with theory and practice, they suggest that the most prominent CSFs for both World Bank project supervisors and managers are design and monitoring. Fourth, they suggest that for the national project coordinators, project success is insensitive to the level of design efforts but a significant correlation does exist between monitoring efforts and project “profile”, a success dimension which is an early pointer of long‐term deliverable success (impact). Originality/value This study offers insights into the relationship between success factors and dimensions for ID projects with the perspectives of both the World Bank project supervisors and managers. The thesis calls for further research on PM in the ID industry sector.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".