A Content Analysis of Human Factor in Maritime Accident

Creative Commons License

Yurt A., Şakar C.

4th International Eurasian Conference on Science, Engineering and Technology (EurasianSciEnTech 2022), 14 - 16 December 2022, pp.95

  • Publication Type: Conference Paper / Summary Text
  • Page Numbers: pp.95
  • Dokuz Eylül University Affiliated: Yes


A considerable amount of research has indicated human error plays a significant role in maritime accidents. The study's objective is to perform a content analysis of the most cited of 30 publications in the English version that discuss how the human element impacts maritime accidents, published between 1975 and 2022.On October 10, 2022, data was extracted from the Web of Science. The primary findings were as follows: The most cited year was 2021, and the most cited article belonged to 2013 with 279 citations, despite the fact that it is clear that the number of referenced publications increased after 2008. Only one of the published articles is not open access, making 96.6% of them so. Following the analysis, it was discovered that Elsevier held the top rank in the comparison of the article publishers with 66.6%, followed by Taylor & Francis with 10%, and Cambridge University Press Wiley with 10% in third position. In terms of the journal indexes, SCI-E makes up 73.3% of the total, followed by SSCI (20%) and ESCI (6.6%). The category quartile of the journals reveals that 33.3% of them are in the Q1 category, 50% are in the Q2 category, 10% are in the Q3 category, and 6% are in the Q4 category. In that order, industrial engineering covers up 50% of the publications' WOS categories, followed by transportation (26.6%) and marine engineering (16.6%). With a percentage of 73.3%, it was seen that quantitative approaches were applied in the context of statistical marine accident data, developed in techniques. Researchers can benefit from the findings of this study by conducting their research with the appropriate journals and regions in consideration. Future research can be more comprehensive by expanding the data set used.