Evaluation of Shipping Accident Casualties using Zero-inflated Negative Binomial Regression Technique

Abstract

This study develops a Zero-Inflated Negative Binomial (ZINB) regression model to evaluate the factors influencing the loss of human life in shipping accidents using ten years' ship accident data in the South China Sea. The ZINB regression model results show that the expected loss of human life is higher for collision, fire/explosion, contact, grounding, hull damage, machinery damage/failure and capsizing accidents occurring in adverse weather conditions during night periods. Sinking can cause the highest loss of life compared to all other accident types. There are fewer fatalities and missing people when the ship involved in an accident is moored or docked. The results also reveal that the loss of human life is associated with shipping accidents occurring far away from the coastal area/harbour/ports. The results of this study are beneficial for policy-makers in proposing efficient strategies to reduce shipping accident casualties in the South China Sea. K E Y WO R D S 1. Zero Inflated Negative Binomial Model.2. Safety.

Evaluation of Two-Ship Collision Severity using Ordered Probit Approaches

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Analyses of determinants of hiking tourism demands on the Jeju Olle hiking trail using zero-truncated negative binomial regression analysis

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

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