Enhancing construction project supply chains and performance evaluation methods: a case study of a bridge construction project
Bibliographic record
Abstract
Construction supply chain management (cSCM) requires planning such that construction stages and logistics are coordinated and integrated to reduce costs, improve productivity, and generate a win–win situation for different parties. The supply chain operations reference (SCOR), which has been widely applied in other industries, is a standardized operational modeling methodology for analyzing supply chain processes. This study considers construction industry characteristics in applying the SCOR model to develop a dynamic cSCM model using computer simulation. Furthermore, this study developed a novel cSCM performance evaluation method using the SCOR method to evaluate cSCM performance and identify and solve cSCM problems. This study uses a bridge construction project as a case study, which determines the relationships among supply chain participants to enhance communication efficiency and identify problems related to materials management. The case study results demonstrate that the proposed hybrid modeling methodology helps construction supply chain participants identify their roles and communicate easily, helps project managers identify bottlenecks in a supply chain, and significantly improves cSCM 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".