@article{Wan_Qi_Wang_Yang_Wu_Zhang_Yan_2026,
	author = {Wan, Cheng Peng and Qi, Junze and Wang, X.B. and Yang, Zhisen and Wu, Bing and Zhang, Di and Yan, Xin Ping},
	title = {Analysing Risk Influencing Factors for the Navigational Safety of Hazardous Cargo Vessels Using Bayesian Networks},
	journal = {TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation},
	volume = {20},
	number = {1},
	pages = {3-10},
	year = {2026},
	url = {./Article_Analysing_Risk_Influencing_Factors_Wan,77,1631.html},
	abstract = {Enhancing navigational safety of hazardous cargo vessels constitutes a critical imperative for sustaining maritime transportation system stability and fostering sustainable industry development. Based on the developed database containing 106 accident reports involving hazardous cargo vessels collected from the International Maritime Organization (IMO), this study aims to analyze the key risk influencing factors (RIFs) contributing to the maritime traffic accidents. Utilizing text analysis, the research first identifies critical RIFs across five primary domains, which are human, vessel, cargo, environment, and management. A Bayesian network model is subsequently developed to map out the interrelationships among these identified navigational safety RIFs. The findings suggest that factors such as "insufficient personnel training," "inadequate safety inspections," "flammable and explosive cargo," "inadequate hazardous goods management," and "pollutant and toxic cargo" exert the most pronounced influence on maritime traffic accidents. Based on these pivotal RIFs and their evolutionary trajectories, this paper can offer theoretical support for enhancing the navigational safety of hazardous cargo vessels.},
	doi = {10.12716/1001.20.01.01},
	issn = {2083-6473},
	publisher = {Gdynia Maritime University, Faculty of Navigation},
	keywords = {Risk Assessment, Maritime Safety, Safety Management, Bayesian Networks, Accident Analysis, Maritime Human Factors, Hazardous Cargo Transport, Probabilistic Modelling}
}