An analytic hierarchy process based model for risk and opportunity assessment of international construction projects
Why this work is in the frame
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Bibliographic record
Abstract
Risk assessment of international projects is a complicated task because of the sensitivity of project success related to country specific risks as well as project risks. Decision makers face the difficulty of weighing project opportunities against risks and determining attractiveness of projects while giving bidding decisions. The aim of this paper is to propose a methodology for risk and opportunity assessment of international projects. The proposed model uses an analytic hierarchy process for calculation of risk and opportunity ratings. A risk breakdown structure, specific to international construction projects, is proposed as well as a list of factors that affect the ability of construction companies to manage risk. An application of the proposed methodology is demonstrated by using real data supplied by a construction company that is experienced in international markets. Ranking of project options is made according to the opportunity and risk ratings that are calculated by using the proposed methodology based on the judgments of company professionals.Key words: international construction, risk assessment, analytic hierarchy process.
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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 | 0.001 | 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 it