Deciphering spatial heterogeneity of maritime accidents considering impact scale variations
Journal article, 2024

Ensuring maritime safety has ascended as a preeminent concern within the global maritime sector. Understanding how factors affect maritime accidents’ consequences in different water areas would be of great benefit to preventing the occurrence or reducing the consequences. This study thus employed a multi-scale geographically weighted regression (MGWR) model on the accident dataset from Fujian waters in the East China Sea, to quantify the influences of different factors as well as the spatial heterogeneity in the effects of key factors on maritime accident consequence. The performances of MGWR are compared with multiple linear regression (MLR) and GWR. As expected, MGWR outperforms the other two models in terms of its ability to clearly capture the unobserved spatial heterogeneity in the effects of factors. Results reveal notably distinct influences of some factors on maritime accident consequences in different locations. An intuitive indication by MGWR is that approximately 50% of the accidents present positive coefficients of good visibility while other locations are negative, which are failed to recognize by MLR. The outcomes provide insights for making appropriate safety countermeasures and policies customized for different water areas.

Maritime accident

spatial heterogeneity

geographically weighted

bandwidth

influencing factors

Author

Guorong Li

Shanghai Maritime University

Student at Chalmers

Kun Gao

Chalmers, Architecture and Civil Engineering, Geology and Geotechnics

Jinxian Weng

Shanghai Maritime University

Xiaobo Qu

Tsinghua University

Maritime Policy and Management

0308-8839 (ISSN) 14645254 (eISSN)

Vol. In Press

Subject Categories

Transport Systems and Logistics

Economics

DOI

10.1080/03088839.2024.2347893

More information

Latest update

5/22/2024