A case study of multi‐team communications in construction design under supply chain partnering
Bibliographic record
Abstract
Purpose The increasing “globalisation” and complexity of construction design implies that the project team may involve subcontractors in the construction supply chain from widely distributed geographic areas. Thus communication is a vital process for the design. The aim of the present work is to investigate how construction design under supply chain partnering can be improved through a study of communication issues and problems. Design/methodology/approach A questionnaire survey is initially conducted to investigate communication issues and problems in construction design. Based on the survey results, a case study is carried out to gain further insights into these issues and problems, exploring how the procurement like supply chain partnering influences the multi‐team communications in construction design. Findings The paper finds that partnering can eliminate many communication barriers and has a positive impact on social collaboration in the design process. It could have a negative impact on the team communications if proper procedures have not been put in place. In addition, co‐location can increase the degree of interaction, communication and technical collaboration in the partnership. Originality/value This paper may help construction project practitioners to focus their attention on the necessary respects of multi‐team communications between supply chain partners in construction design, leading to high cooperation and ultimately improving the quality of the design outcomes.
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".