## 4 Discussion
### Results and Their Significance  
The results of experts' elicitation indicate their opinions by definition, not necessarily facts. It is, however, the long-lasting paradox of performing research on the safety of innovative systems. With only few prototypes in operation, autonomous merchant vessels are characterized by the lack of quantitative data regarding their operational performance and features. Therefore, experts remain one of the most reliable sources of information [40], in the presence of other sources. To this end, the experts evaluated the influence that human factors can have on each other and thus, on the safety of remotely controlled merchant vessels. Looking at Figure 7, one can easily recognize the Condition of operator(s) (IV-A) as the most prominent node of the net of mutual influences. It is both strongly influenced by upper-level causal categories, but also strongly impacts lower level, the one being the last line of defense-in-depth. Similarly, Failure to correct known problem (III-C) has a relatively strong influence on its lower-level causal categories. This indicates that the experts appreciate the significance of recognizing and mitigating issues that have been found hazardous within the system. This causal category is of a particular importance for the safety of the entire system. This is because it consists of acknowledging that something is going wrong but not doing anything about that, or taking insufficient actions to mitigate it. In other words, it means that there is a pre-existing, known, unrectified, safety-related problem. On the contrary, the experts do not recognize Planned inappropriate operation (III-B) as particularly challenging, perhaps because they expect that failures in planning can be mitigated during the actual operations of remotely controlled vessels. Similarly, it can be noted in the relation to Inadequate supervision (III-A), perhaps because the experts found  
Figure 7: Medians of the influences. The color-coded arrows indicate that a particular influence was assessed as at least 20% stronger/weaker than the median for the stage to which it belongs. supervision to be irrelevant for real-time, remote problem-solving tasks. In this case, however, it was determined that supervision affects Liveware (IV-F) above average, indicating its strong influence on human-human relations. Notably, the experts recognized that causal factors falling within Physical environment (IV-D) and Technological environment (IV-E) categories cannot in general be easily affected by those from the Unsafe supervision (III) level. Moreover, Software (IV-B) and Hardware (IV-C) appear to affect causal categories on the Unsafe acts (V) level to a rather limited extent. It can also be found that relationships between causal factors in Unsafe supervision and Preconditions (III vs. IV), as well as in Preconditions and Unsafe acts (IV vs. V) stages are generally characterized as either stronger or weaker than those on External factors and Organizational influences (I vs. II) or Organizational influences and Unsafe supervision (II vs. III) stages. It appears that it was somewhat easier for the experts to recognize stronger/weaker relationships on the stages closer to actual operations. The experts agreed with each other the most on the Organizational influences and Unsafe supervision (II vs. III) stage, with SD = 25.64. The overall median of the experts' responses was also the greatest for this stage (ME = 40.0), which suggests that the experts recognize that a widely-understood organizational environment is important for ensuring safe operations of autonomous vessels, including the human factors present therein. While this issue has been recognized as important by various scholars [8,28,40], it has also been studied to the least extent [41] to date. The expert elicitation method proved its usefulness in assigning the magnitudes of influence of one causal factor category on another.