APPRAISING THE STATE OF PROCUREMENT OF MECHNICAL AND ELECTRICAL SERVICES ON SELECTED PUBLIC BUILDING PROJECTS IN DELTA STATE, NIGERIA
Bibliographic record
Abstract
Failure to select an appropriate procurement option and assess the inherent challenges facing selected options can impact negatively on the achievement of the project objectives. This has been the bane of services procurement in Delta State. Thus, the research appraised the procurement of mechanical and electrical services installations in selected building projects in Delta State, with a view to determining the common procurement methods adopted by clients and identifying the factors affecting the choice of procurement methods. Two selected public institutions and some selected approved private buildings in Uvwie local government area of Delta state formed the study area/projects. The research was carried out through a structured questionnaire on sectional basis in consonance with the objectives of the study. Both purposive sampling was applied on a population of 91 professionals in the study area. Data collected were analyzed with statistical package for social sciences (SPSS) version 16 via frequencies, percentages and mean score. Results from the analysis showed that design and install followed by traditional method are the procurement methods mostly used by clients for M&E services in the study area while short project duration, quality of end product, and cost effectiveness constitute major reasons why clients use procurement methods. In addition to this, technical complexity of the project, financial capacity of the client, the financial requirement of the project, economic factors and size or magnitude of the project are key factors that influence the choice of procurement method for M&E services, although at varying degrees. It was concluded and subsequently recommended since that design and install method of procurement is mostly adopted by clients for M&E services in building projects and thus should be adopted by clients since they lead shorter project delivery time, better quality of end products and are cost effective.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".