A Zero-Inflated Negative Binomial Regression Model to Evaluate Ship Sinking Accident Mortalities. Issue 11 (December 2018)

• Record Type: Journal Article
• Authors: Chai, Tian; Xiong, De-qi; Weng, Jinxian
• Is Part Of: Transportation research record. Volume 2672:Issue 11(2018)
• Page Start: 65
• Page End: 72
• Publication Date: 2018-12
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198118787388
• Languages: English
• ISSNs: 0361-1981

Abstract

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.