Quantitative Analysis of Risk Influential Factors of Evacuation Accidents for Passenger Ships
With the increasing use of passenger ships in passenger transport and tourism sighting, the risk of evacuation accidents is higher. To prevent such accidents and reduce casualties, a quantitative analysis method for identifying and evaluating risk influential factors (RIFs) of evacuation accidents is developed by integrating complex network (CN), decision-making trial and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) methods. Firstly, 27 RIFs are identified by extracting accident casual chain from global emergency evacuation reports of large passenger ships, and a network model for evacuation accidents is constructed. Secondly, CN is used to conduct a topological analysis of these identified RIFs from a global perspective, and robustness analysis under different attack modes is used to validate the ranking of these RIFs. Finally, DEMATEL and ISM are used to establish a multilayer structure model, 12 key RIFs are identified from causal relationship and structural perspectives, and countermeasures are proposed to mitigate these RIFs. By identifying these key RIFs, this study aims to deepen the understanding of evacuation risk management, provide a theoretical basis for emergency decision makers, optimize the evacuation process, and reduce casualties.
Authors
- Sean Loughney (ORCID: https://orcid.org/0000-0003-0217-5739)
- Jiashi Wang (ORCID: https://orcid.org/0000-0002-5581-9035)
- Xinjian Wang (ORCID: https://orcid.org/0000-0002-7469-6237)
- Siming Fang (ORCID: https://orcid.org/0000-0003-2340-0923)
- Zhongyuan Liu (ORCID: https://orcid.org/0000-0002-3641-5094)
- Wenjie Cao
Institutions
- Jimei University (CN)
- Dalian Maritime University (CN)
- Liverpool John Moores University (GB)
Publication Details
- Journal
- ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part A Civil Engineering
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1061/ajrua6.rueng-1454
- Citations
- 2
- Primary Topic
- Marine and Coastal Research
- Type
- article
- Field-Weighted Citation Impact
- 0.67
Funders
- National Natural Science Foundation of China
- Dalian Maritime University