ArticleHeliyon2024
Risk analysis in underground tunnel construction with tunnel boring machines using the Best-Worst method and data envelopment analysis.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The use of tunnel boring machines is continuously increasing; however, this activity faces many risks, resulting in negative events. Methods: A novel approach using the best-worst method and a data envelopment analysis model was proposed to analyze the risks of underground tunnel construction with tunnel boring machines. The proposed approach was validated using a realistic case study of metro construction in Thailand. Results: The proposed approach efficiently analyzed the risks and produced more solid findings. The most critical and least affected risks can be identified according to risk scores in descending order. Implication: This study contributes a new method of risk analysis that benefits project managers and stakeholders who design risk management plans to reduce the occurrence and mitigate the severity of metro works. Originality: The new risk analysis can obtain the best compromise ranking of risks based on decision-makers' preferences, probabilities, and various consequences under different circumstances.
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Registered trials
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