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Record W2144194965 · doi:10.5539/emr.v1n2p122

Determining Critical Project Success Criteria for Public Housing Building Projects (PHBPS) in Ghana

2012· article· en· W2144194965 on OpenAlexvenueno aff
Emmanuel Adinyira, Edward Ayebeng Botchway, Titus Ebenezer Kwofie

Bibliographic record

VenueEngineering Management Research · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCritical success factorProject managementBusinessQuestionnaireClosure (psychology)Quality (philosophy)Operations managementProcess managementEngineeringEconomics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.377
GPT teacher head0.512
Teacher spread0.136 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations25
Published2012
Admission routes1
Has abstractyes

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