## 6 Conclusions  
This study conducted a bibliometric analysis by reviewing the current state and future research directions related to fishing vessel safety, utilizing relevant literature. For data collection, the Scopus database was used, and Boolean syntax was employed to create the query strings. As a result, 285 relevant documents were identified, and a bibliometric analysis was performed using the Biblioshing app from the bibliometrix package in R software, along with VOSviewer. Biblioshiny was used to generate an authors' cooperation network, three-field plot, and keyword Thematic map, which were used for citation analysis. VOSviewer was used to create networks between journals, articles, affiliations, countries, and keywords, through which bibliographic coupling was performed. Research on fishing vessel safety has been steadily increasing. The journal with the highest number of publications was _Ocean Engineering_. The most cited paper was [PERSON] et al. (2017) [14]; however, despite its high citation count, it was found to have fewer or no connections in the network plot due to its lower relevance to the themes of the 285 documents considered. The author with the most publications was [PERSON], with nine papers. [PERSON]'s network plot showed clustering with co-authors who conducted research around the same period. The characteristic author clusters were divided into two groups: those who started research in the early 2000s and those who began after 2020. The institution with the highest number of publications was NTNU, and the country with the most publications was China. The institutions and countries contributing to fishing vessel safety research were primarily those with active fishing industries. Using the three-field plot, the relationships between journals, keywords, and countries were observed, revealing that _Ocean Engineering_ hosted a wide variety of topics. It was also confirmed that most countries covered diverse topics related to fishing vessel safety. Through bibliographic coupling, the keywords of the 285 documents were grouped into four main clusters: _Accident/Risk Analysis_, _Human errors_, _Stability_, and _Operation_. These clusters represented different aspects of accidents and prevention measures, categorized based on situations and technology. Moreover, _Accident/Risk analysis_ was further subdivided into _Accident analysis_ and _Risk analysis_ depending on whether the focus was on analyzing past incidents or studying factors for accident prevention. To perform a detailed review of the selected literature, 148 documents categorized in the Thematic map were prioritized based on publication year and citation count for the initial screening. Additionally, other documents not included in the Thematic map were evaluated for their relevance based on the titles and the prominence of the authors. Through this process, 37 documents were finally selected for a detailed review within each cluster. The first cluster, _Accident_/_Risk Analysis_, can be divided into two subcategories: _Accident Analysis_ and _Risk Analysis_. _Accident analysis_ focuses on investigating the causes of fishing vessel accidents that have occurred worldwide and proposes safety measures based on these findings. This subcategory mainly uses statistical methods or BN to quantitatively estimate the probability of accidents and incorporates qualitative factors through approaches like FTA and FSA. In contrast, _Risk Analysis_ is more prevention-oriented, focusing on defining risk factors and calculating the probability of accidents. Strategies such as risk selection using checklists and RBM are commonly employed. Techniques like RAw tools and FMEA are used to predict accident likelihood. The second cluster, _Human Factors_, addresses the impact of human error in maritime accidents, with a focus on analyzing the diverse factors contributing to human error. Various models are proposed to assess these influencing factors.