Determining Critical Project Success Criteria for Public Housing Building Projects (PHBPS) in Ghana
Bibliographic record
Abstract
Successive Public Housing Building Project (PHBP) attempts have been unsuccessful due to a number of reasons. Among these is the lack of clearly defined success criteria which guides and measures PHBP success from inception to closure. The adoption and application of project management practice and project success criteria is to deliver projects successfully, attain enhanced output, develop framework to help track key project results and to enable the appropriate allocation of resources. This paper aimed to establish critical success criteria for PHBPs in Ghana. A questionnaire survey was employed to elicit the views of experienced professionals on 13 project success criteria identified from literature. Mean score analysis and factor analysis were conducted on the data collected. The results showed that PHBP practitioners perceive ‘cost of individual houses’ and ‘extensive use of local materials’ as the most critical success criteria with ‘risk containment’ emerging as the least critical criteria. It also revealed the following as the major underlysing factors for critical project success criteria for public housing projects in Ghana;‘Time, Cost and Quality Management’, ‘Satisfaction, Health and Environmental Safety’, ‘User Affordability and Design Consideration’ and ‘Cost of Individual Units and Technology’. These two findings are essential for developing a framework which will enable project managers involved in PHBPs in Ghana to channel appropriate efforts and behaviours towards ensuring the attainment of success on their projects.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".