Maritime Casualties Through the Bosporus

Huang

2015

J. Navigation

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.

Section: Literature Reviewmentioning

confidence: 99%

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

Huang

2015

J. Navigation

“…Many other studies have been conducted to investigate the relationship between the contributory factors and ship accident risks considering all ship types. For example, many researchers estimated the occurrence probability and consequence of ship accidents in different waters such as U.S. coast area ( 4 , 9 , 14 ), Istanbul Strait ( 1 , 19 , 20 ), Singapore Strait ( 21 , 22 ); UK coast area ( 13 ), South China Sea ( 10 ), and Gulf of Bothnia ( 23 ). The estimation of human life loss and accident severity has been the major study object in these studies.…”

Section: Literature Reviewmentioning

confidence: 99%

Bayesian Regression Model for Estimating Economic Loss Resulting from Two-Ship Collisions

Transportation Research Record: Journal of the Transportation R

Liao

2019

This study aims to develop a Bayesian regression model to evaluate the economic loss resulting from two-ship collisions using ten years’ ship collision data for occurrances in Fujian waters. The model results show that the involvement of passenger/cruise ships could cause the largest increment on economic loss in ship collisions. Interestingly, it is found the involvement of fishing ships could greatly increase the ship collision consequence in terms of economic loss. Results also reveal that the higher economic loss is associated with the collisions in the straits/sea areas, under the strong wind/wave conditions, during nighttime period, and in poor visibility conditions. The impact analysis results highlight that judgment errors play a decisive role in increasing the economic loss as compared with the other two types of human errors: lookout failure and operation errors. The results of this study are useful for policy-makers in proposing efficient strategies to mitigate the economic loss from two-ship collisions. The developed model is also beneficial for insurance companies in determining the appropriate ship insurance rates.

“…Many other studies have been conducted to investigate the relationship between the contributory factors and shipping accident risks considering all ship types (Hänninen and Kujala, 2012; Hänninen et al, 2014a; 2014b). For example, some researchers (Akten, 2004; Ozsoysal and Ozsoysal, 2006; Birpinar et al, 2009; Aydogdu et al, 2012) analysed shipping accidents and proposed navigation safety enhancement strategies for the Istanbul Strait. Debnath and Chin (2010) explored the factors influencing shipping collision risks in Singapore Port waters.…”

Section: Literature Reviewmentioning

confidence: 99%

“…There is also some work focusing on crew injuries in container ship accidents (Zheng et al, 2016). Considering all ship types, some researchers have investigated the relationship between contributory factors and ship accident risk (Akten, 2004; Ozsoysal and Ozsoysal, 2006; Birpinar et al, 2009; Aydogdu et al, 2012). Nevertheless, data sources used for analysis were for specific water areas.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Two-Ship Collision Severity using Ordered Probit Approaches

Chai

et al. 2018

J. Navigation

This study develops an ordered probit model to evaluate the factors influencing two-ship collision severity using ten years’ ship collision accident data from Fujian sea areas. The model results show that the involvement of big ships has the largest impact in increasing the probability of a serious or very serious accident, followed by the involvement of fishing vessels. There will be a bigger probability of a serious accident if both ships involved in the collision are cargo ships. We found that the season of spring, poor visibility and night time periods are more likely to be factors in high severity levels of ship collision. The results also reveal that lookout failure plays a decisive role in increasing serious accident risk compared with other types of human errors. The results of this study may be beneficial for policy-makers in proposing efficient strategies to reduce the likelihood of serious ship collisions.