Multi-Factor superposition influence analysis in engineering projects: a Bayesian network approach
The existing studies rarely examine whether multiple risk factors superimposed on a particular activity result in superposed or non-superposed effects. To some extent, these effects may influence the accuracy of project managers’ decision-making when handling risks. This research addresses this gap...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-06-01
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| Series: | Journal of Asian Architecture and Building Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/13467581.2025.2513064 |
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| Summary: | The existing studies rarely examine whether multiple risk factors superimposed on a particular activity result in superposed or non-superposed effects. To some extent, these effects may influence the accuracy of project managers’ decision-making when handling risks. This research addresses this gap by applying Bayesian Network (BN) to multi-factor superposition influence on project schedule uncertainty. The methodology involved constructing and implementing a Bayesian Network diagram for project schedule risk. And a Bayesian network-based engineering schedule risk detection model was developed. This model was then used to examine whether the combined influence of superimposed risk factors equals the sum of their individual influences. The results demonstrated through engineering examples, show that the model not only clearly expresses project schedules but also has all the functions of a Bayesian Network, serving as a platform for processing uncertain data. The case study revealed that the combined impact of multiple risk factors on the project schedule is not superimposed. These findings provide policymakers with a more comprehensive understanding of how to respond to risk. |
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| ISSN: | 1347-2852 |