*3.7. Expert Weighting*

Based on the background questionnaire explained in the previous subsection, an approach to assign weights to the expert evaluations has been derived, which is summarized in Figure 6. Each expert leans on their own perception to enter their expertise in the domains aircraft design, aerostructures, aeroengines, flight mechanics and aerodynamics. The DM's abstract "total" relevant expertise is then calculated by simply adding or weighting the domain self-evaluation. Subsequently, the technology comparisons made by different experts are aggregated by applying the weighted geometric mean. The weights are calculated by normalizing the expertise of each participant with the sum of the expertise of all experts.

Weighed geometric mean

**Figure 6.** Schematic overview of expert weighting based on their self-determined expertise in relevant domains.

#### *3.8. Expert Anonymity*

The level of participant anonymity during and after the elicitation is an aspect concerning not only the experts themselves. It also serves as a potential source of social pressure biases able to influence the evaluations and therefore the final results [14]. Such biases can occur during the group discussions as well as when the experts enter their evaluations. In the first case, the group think bias might be present, representing the alteration of one's own opinion or action in order to be aligned with common positions [14]. The same effect could be observed when hierarchical structures are present in the group. In order to reduce these effects, the current workshop implements individual evaluations which are not shown to the panel. However, even such a setting hides risks of revealing the participants identity to the researcher during the data evaluation or/and to society, if the evaluations are associated with their person later on. This is connected to the impression management bias, which stands for the concern with the reaction of people not present [14].

For this reason, the workshop concept ensures the anonymity of the participants to the researchers and to the public. This is done by requiring them to log in to the questionnaire with a random identification number chosen by them. In the further data processing, the evaluations are associated solely with the identification number which cannot be related to any person.

#### *3.9. Post-Processing of the Raw Results*

The raw output from the workshop yields fuzzy comparisons of the MM options from each expert. These should be adapted to comply with the input format of the AMA process in order to analyze the final solution space. The conducted steps for that purpose are depicted in Figure 7 and explained in the following:

**Figure 7.** Schematic steps of the data post-processing.
