Assessment of Contractors’ Mitigating Measures for Cost Overrun of Building Projects in South-Western Nigeria
Bibliographic record
Abstract
The study examined the mitigating measures employed by contractors in southwest of Nigeria for cost overrun of building projects with a view to determining its adequacy and effectiveness. A mix of qualitative and quantitative research methods was adopted where data pertinent to the study were obtained through questionnaire survey on a sample of 32 project managers of medium sized construction firms selected from the list of 125 contractors on the register of Federation of Building and Civil Engineering Contractors located in South-West Nigeria using Simple Random Sampling method. Additional information was obtained from contracts bills of quantities and programme schedule to complement the data obtained from the questionnaire survey. Contract sums and final sums of building projects between 200 million Naira – 1.7 billion Naira handled by respondents were also collected as secondary data. Statistical Package for Social Scientists (SPSS) was employed to analyse the data for descriptive statistics while manual approach was adopted for inferential statistics of t-test. The results obtained revealed that effective site management and supervision with the highest relative importance index (RII) for adequacy of the mitigation measures was at average level and the (RII) for the effectiveness of mitigation measures adopted by contractors was very low. It also revealed that there is significant difference between initial sums and final sums of building projects at 5% significance level where the mitigation measures were taken in to consideration. The study concluded that mitigation measures adopted by contractors have not been adequate and effective in curbing cost overrun of building projects in southwest Nigeria.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".