Evaluation of Contractors’ Financial Ability: A Remedy for Performance of Road Construction Infrastructural Projects for Sustainable Cities
Bibliographic record
Abstract
Construction of roads in Kenya, particularly done by local contractors, has adversely been faced with serious issues to do with cost overruns, longer periods in completion and above all poor quality upon completion. However, performance of roads in the post-delivery or post construction stage has not keenly been assessed or studied despite poor workmanship. Although financial aspect has been associated with completion road construction projects, studies have not used this predictor variable to study performance. The aim of the study was to establish the influence of financial ability of contractors and performance of road construction infrastructural projects in Nairobi County, Kenya. Both descriptive survey research and correlation research designs were adopted in this study. A target population of 460 comprising all public service vehicle drivers plying Eastern Bypass, and Outer-ring roads in Nairobi, as well as the contractors and engineers from the construction firms in Nairobi County. A sample of 210 was drawn from both categories of respondents and served with interview schedules out of which 153 were returned representing 72.8%. Results from the simple linear regression model revealed that contractors’ financial ability, explains 44.7% total variation in the performance of road construction infrastructural projects. This relationship was established to be lineally positive and strong (r=0.669) and also significant (P=0.000<0.05). The study findings play a vital role in construction project management during evaluation process of selecting effective contractors for better road performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".