Modeling of organizing function management in Vietnam’s public construction works
Bibliographic record
Abstract
Organizing function is the significant component of management guaranteeing the success of construction works. Many studies have been emphasizing on the topic of critical success factors (CSFs) within construction works, yet the results have rarely emphasized examining organizing behaviors within public construction work management; these less researched topics were the aims of this study. To fulfil this research aim, a regression analysis design was employed. Data were collected using questionnaires conducted from 139 professionals involved in public construction works management in Vietnam. The structural equation modelling (SEM) technique with partial least-squares estimation (PLS) was utilized to analyze the data. The results revealed 6 behavioral dimensions (i.e., structure organizing (OR1), authorization organizing (OR2), coordination organizing (OR4), human resource organizing (OR3), job organizing (OR5), responsibility organizing (OR6) to assess organizing function in terms of public construction work management. The study also reveals that structure organizing (OR1), authorization organizing (OR2), coordination organizing (OR4) have significant effects on management effectiveness (ME). In addition, coordination organizing (OR4) acts as the mediator of Human resource organizing (OR3), job organizing (OR5); while responsibility organizing (OR6) indicates an indirect influence through the mediator of OR5. The success of this approach is expected to reinforce the contribution of organizing function and suggest a useful tool for supporting the professionals in enhancing public construction work management.
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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 | 0.001 | 0.001 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".