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Economic Loss Analysis of Fishing Boat Collisions Considering Spatial-Temporal Interaction Effects

Published online by Cambridge University Press:  31 March 2020

Jinxian Weng Open the ORCID record for Jinxian Weng [Opens in a new window]  and
Guorong Li
Jinxian Weng*
Affiliation:
(College of Transport and Communications, Shanghai Maritime University, Shanghai201306, China)
Guorong Li
Affiliation:
(College of Transport and Communications, Shanghai Maritime University, Shanghai201306, China)
*
(E-mail: [email protected]; [email protected]; [email protected])
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Abstract

Considering unobserved spatial-temporal interaction effects, this study proposes a Bayesian spatial-temporal interaction model for predicting economic loss from fishing boat collisions using 10-year (2004–2014) collision records from six different areas in the waters of Fujian, China. Results show strong spatial heterogeneity and correlation effects in fishing boat collisions, while the economic loss from boat collisions gradually decreases with the time trend. Collision time, collision location, visibility and the involvement of LNG/LPG/chemical-carrying ships show similar marginal effects on the economic loss for the two collision types: fishing boat collisions and collisions involving no fishing boats. Navigational status and the involvement of cargo ships exhibit much bigger effects in fishing boat collisions compared with collisions involving no fishing boat. Unlike collisions involving no fishing boat, fishing boat collisions are associated with reduced economic loss in poor weather conditions characterised by strong wind/waves because in Fujian waters additional safety measures are adopted for fishing boats in such conditions. The proposed model is useful for policymakers in adopting safety enhancement strategies to decrease the economic loss resulting from fishing boat collisions.

Keywords

Ship CollisionModellingSafetyUncertainty
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 5 , September 2020 , pp. 1069 - 1086
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Copyright
Copyright © The Royal Institute of Navigation 2020

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