Identification of critical risks in international engineering procurement construction projects of Chinese contractors from the network perspective
Bibliographic record
Abstract
International engineering procurement construction (IEPC) is a complex subject interconnected with risk transfer. In-depth understanding of risks in IEPC projects is essential for effective risk management and managerial strategies. Most related studies focus on the critical risks based on the perceptions of stakeholders or their direct “contribution” to the project loss. This study aims to investigate risk interconnection in IEPC projects through social network analysis, with a focus on the critical risks, risk interactions, and risk mitigation strategies. Three approaches were employed. First, the risk register and interconnection between IEPC projects were identified through a literature review. Second, the risk register and interrelationships were investigated using a questionnaire to formulate theoretical risk-interdependent networks. Third, practical IEPC projects were analyzed using network metrics to identify mitigation strategies for the associated critical risks. From the obtained results, we concluded that controlling security and contract risks in project management can reduce the occurrence or impact of other risks. Moreover, environmental issues related to contractors are also critical in international construction projects. Investigating relationships between risks has uncovered different risk-propagation mechanics within IEPC projects, thus extending the theoretical knowledge for international construction and risk management.
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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 | 0.002 |
| 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 | 0.000 |
| 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".