## 1 Introduction
### Literature Review  
In this section, we identify the limitations of linear accident analysis, compare the trends of marine accident investigation methods and accident analysis studies, and investigate research on FRAM. The following are literature reviews performed at various stages. First, we investigated the limitations of a simple linear accident analysis method based on the results of previous studies. Considering the limitations of a simple linear accident analysis method, it is essential to analyze the causes of accidents to prevent the occurrence of similar accidents and reduce repeated loss of capital. According to [PERSON] et al. [8], early accident analysis systems such as domino and fault-tree models reinforce safety by identifying and eliminating system problems based on simple linear causalities. Despite being one of the most understandable and clearest theories for defining thought processes, domino theory has the limitation of emphasizing individual responsibility and faults while condensing numerous probable causes into one. [PERSON] et al. [9] highlighted the necessity of combining the domino model with a Bayesian network or machine-learning algorithms to discover potential evolutionary patterns of thinking. Fault-tree analysis (FTA) is a representative method in system safety engineering [10] that uses logical symbols to create a fault tree, which is analyzed deductively, quantitatively, and probabilistically to express the cause of an accident [11]. However, FTA cannot perform a composite analysis of the relationship with other functions or systems, scalability, and variability of accident causes, although it is suitable for identifying the root cause of an accident [12]. The final causes of accidents in FTA, domino models, event tree analysis (ETA), failure modes, and effects analysis (FMEA) models have been attributed to people and equipment [13]. Moreover, they have the same limitation, that is, the nonlinear complexity of the system cannot be sufficiently explained [14]. Second, a review of marine accident investigation trends found that many studies have used the International Maritime Organization (IMO) Casualty Investigation Code (2008), published by the IMO on 1 January 2010, as a general approach to human factors in marine accident investigations and a systematic way to identify accident causes [15]. The accident investigation and analysis method of the casualty investigation code has the limitation of simple linear thinking analysis because the goal (1 st), aspects (2 nd), and criteria (3 rd) are connected in a simple linear fashion. Moreover, [PERSON] highlighted that research on human error is limited, although most of the primary causes of marine accidents are related to human error [16]. Although emphasis on the importance of human factors has recently increased, there have been cases wherein finding the cause of accidents lies solely upon the actions of job performers. [PERSON] et al. predicted that ship accidents would occur in the future owing to system complexity and automation, human errors, potential design-based failures, and human-centered system designs [17]. Recently, the system development and complexity of ships and ports, such as smart ships, digital ships, maritime autonomous surface ships, and automated ports, has increased rapidly. [PERSON] et al. predicted that a systematic investigation and analysis of marine accidents considering the relationships between human factors and complex and diverse systems would be required [1]. Third, the results of a review of previous studies on marine accident analysis showed that they focused on improving the limitations of linear accident analysis and explored various methods to analyze the causes of human factors in a systematic and visual way. Figure 1: Research question and design. For example, [PERSON] proposed the Accimap approach, an accident analysis method that visually represents decision makers and their decisions involved in creating a system that allows the occurrence of accidents [18].