A contemporary vision of project success criteria
Bibliographic record
Abstract
Goal: The objective of this research is to provide researchers and project management professionals with a contemporary view of the measurement of project success. Design/Methodology/Approach: After a dense literature review, a research-based study analyzes the project success criteria perspectives of 264 Brazilian project managers and provides a ranking of the most widely used measures in practice in Brazilian organizations. Results: The study analyzes contemporary literature on project success criteria and discusses overlaps and trends. One of the important findings of this research is the identification of mismatches between academic perspectives and those of project managers in regard to project success as well as real success criteria used in organizations. Limitations of the investigation: As the sample covered was comprised exclusively of Brazilian project managers, cross-cultural success criteria research is, therefore, encouraged. Practical implications: The proposed performance criteria can be used in future research and for professional proposes in success criteria assessment. Originality/Value: Given the diversity of success criteria measures, authors can have difficulty in finding the one that better fits their needs; alternatively, they can create their own scale. The reliability of several studies can be questioned due to their subjectivity and, in some cases, weakly defined measures. The present study can therefore provide project professionals with guidelines for success assessment that make measuring and comparing different projects possible.
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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 | 0.045 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.018 | 0.014 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".