Investigation of coinciding shipping accident factors with the use of partitional clustering methods

Abstract

Aim of this paper is to investigate how a series of different factors are coexisting in shipping accidents. We analyzed 355 shipping accident reports from the European Maritime Safety Agency (EMSA), which are publicly available from the official EMSA website. For this purpose we used the K-means clustering method with 15 a priori defined clusters. Our results indicated that human factors often coexist with parameters related to the condition of the ship and other external factors (i.e. bad weather). Our investigation aims to contribute to the better understanding of underlying factors so that more targeted staff training, manning and shipping maintenance measures can be taken to prevent future events.