Classification of the Most Influential Maritime Accident Types using Grey Theory

Abstract

In recent years, the number of maritime accidents in Korean waters has been increasing dramatically. Fishing vessel accidents account for around 70% of all accidents. However, there have been limited studies on fishing vessel accidents relative to non-fishing vessel accidents. The government has announced maritime plans to reduce both the frequency of these accidents, as well as the fatalities resulting from them. The purpose of the research is to identify the influential accident types on accident frequency and fatality. We accordingly classify the major accident types leading to fishing vessel accidents into two categories, frequency and fatality, using grey relational analysis which is an efficient ranking technique to determine the most influential accident types. For this study, data from nine types of fishing vessel accidents over the last 5 years (2014 to 2018) are used. The results show that for frequency category, engine failure, others, collision, and safety precautions were the most influencing types, whereas touching and sinking were shown to be the least influencing accident types. For fatality category, safety precautions, collision, and grounding were the most influencing accident types whereas touching, engine failure, and others were the least influencing accident types. The findings demonstrate that more attention should be paid to engine failure and safety precautions to reduce maritime accidents.