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Record W2760534475 · doi:10.5539/jsd.v10n5p234

Cost and Time Overruns in Building Projects Procured Using Traditional Contracts in Nigeria

2017· article· en· W2760534475 on OpenAlexvenueno aff
Dele Samuel Kadiri, Babajide O. Onabanjo

Bibliographic record

VenueJournal of Sustainable Development · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicConstruction Project Management and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementScheduleCost overrunBusinessCost estimateFinanceOperations managementEngineeringMarketingEconomicsConstruction industryConstruction engineeringManagement

Abstract

fetched live from OpenAlex

The traditional contract procurement system is reported to be the most preferred in Nigeria for the execution of construction projects. However, the system has been criticised to be ineffective in terms of both cost and time performances. Owing to scanty empirical evidence to support this claim, this study assessed cost and time overruns in building projects executed in Nigeria using the system. Schedule and cost data of building projects were accessed from randomly selected frontline quantity surveying firms in the study area. These comprised schedule data on 51 public and 41 private building projects as well as cost data on 42 public and 33 private building projects. The data were analysed using frequency, percentage and mean. The findings from the study revealed that both public and private building projects executed in the study area using traditional contract system experienced cost and time overruns to varying degrees. However, the system was more effective in terms of cost performance than time performance.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.091
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.131
GPT teacher head0.362
Teacher spread0.231 · 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 teacher head, 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

Citations4
Published2017
Admission routes1
Has abstractyes

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