TY  - JOUR
PY  - 2018//
TI  - A zero-inflated negative binomial regression model to evaluate ship sinking accident mortalities
JO  - Transportation research record
A1  - Chai, Tian
A1  - Xiong, De-qi
A1  - Weng, Jinxian
SP  - 65
EP  - 72
VL  - 2672
IS  - 11
N2  - Sinking accidents are a seafarer's nightmare. Using 10 years' of worldwide sinking accident data, this study aims to develop a mortality count model to evaluate the human life loss resulting from sinking accidents using zero-inflated negative binomial regression approaches. The model results show that the increase of the expected human life loss is the largest when a ship suffers a precedent accident of capsizing, followed by fire/explosion or collisions. Lower human life loss is associated with contact and machinery/hull damage accidents. Consistent with our expectation, cruise ships involved in sinking accidents usually suffer more human life loss than non-cruise ships and there is be a bigger mortality count for sinking accidents that occur far away from the coastal area/harbor/port. Fatalities can be less when the ship is moored or docked. The results of this study are beneficial for policy-makers in proposing efficient strategies to reduce sinking accident mortalities.<p />  <p>Language: en</p>
LA  - en
SN  - 0361-1981
UR  - http://dx.doi.org/10.1177/0361198118787388
ID  - ref1
ER  -