Analysis of the injury-severity outcomes of maritime accidents using a zero-inflated ordered probit model

Abstract

This study provides an empirical analysis of the injury severity outcomes of maritime accidents by exploring the influential factors for two underlying injury severity states: the injury-free state and the injury-prone state. The former may reflect the generation mechanism of accidents with limited potential to result in injury outcomes, whereas, the latter may represent injury severity when the accident falls into the injury-prone category. To account for the possible presence of these two underlying regimes, a zero-inflated ordered probit (ZIOP) model is employed using injury-severity data extracted from 1,128 maritime accident investigation reports between 2000 and 2019. The results indicate that on one hand, capsizing/sinking, hull/machinery damage and other accident type, adverse sea state, poor education background and short period of holding the present rank are more likely to be injury-prone. On the other hand, gross tonnage and water depth, distance from the coast, flag state of convenience, and accident type impact the likelihood of severe injuries if the accident is in the injury-prone category. The marginal effect analysis highlights some interesting effects caused by sea state, ship manning and gross tonnage, as well as accident type and location. The results of Akaike's information criteria (AIC), Bayesian information criteria (BIC) and Vuong's test show that the ZIOP model outperforms the traditional ordered probit model and can serve as an alternative to study the injury severity of maritime accidents.