## 3 Proposed Methodological Approach
### Electre Tri
We specify that \(\delta(A_{i},P_{j})\) is assumed as equal to the aggregated concordance index \(C(A_{i},P_{j})\) When no veto threshold has been established in the stage of input data collection, implying that no specific criterion has been set to denote a level of incompatibility beyond which an alternative is entirely unacceptable. The absence of a veto threshold must be contemplated by the analyst as it means that all the alternatives can be considered potentially viable, even if they do not fully meet certain criteria. This approach allows for a more inclusive consideration of alternatives and can prevent premature elimination of potentially valuable options. It can be useful in various scenarios, e.g., when decision-makers seek flexibility, face uncertainty in preferences, need to conduct exploratory analysis or aim to reduce computational complexity [39]. * Deciding on a particular type of outranking relation using the cutting level \(\lambda\). Essentially, \(\lambda\) serves as the threshold for \(\delta(A_{i},P_{j})\) to confirm that \(A_{i}\) outranks reference profile \(P_{j}\) towards the final assignment to a specific class. The value of \(\lambda\) falls between 0.5 and 1, as specified before, and must exceed the quantity equivalent to \(1-(\)_highest weight/total weight\()\)_[40; 41]. This step concludes the application of the first phase of ELECTRE TRI. Once the first phase is concluded, we will briefly explain how to carry out the second phase of the ELECTRE TRI procedure. This phase aims to produce the final assignment of alternatives to classes, which can be performed by means of two distinct procedures, namely the pessimistic and the optimistic procedures. The pessimistic (or conjunctive) procedure determines the classification of alternative \(A_{i}\) by verifying the condition where \(A_{i}\) outranks \(P_{j}\) to assign it to class \(C_{h}\). This procedure consists of two steps:  
* successively comparing each alternative \(A_{i}\) with the profile limits of classes until the condition that \(A_{i}\) outrank \(P_{j}\) is met;
* assigning alternative \(A_{i}\) to class \(C_{h+1}\). The pessimistic procedure is generally preferred over the optimistic one, as it is grounded in the desire for more conservative results. By favoring results obtained via the pessimistic procedure, the method tends to assign alternatives to classes defined by lower profiles. This means that alternatives are categorized based on stricter criteria, which increases the likelihood of selecting options that perform well across all criteria. This approach is particularly valuable in decision-making contexts where risk aversion or the desire to avoid overly optimistic assessments is important [42]. The optimistic (or disjunctive) procedure determines the classification of alternative \(A_{i}\) by verifying the condition where \(P_{j}\) outranks \(A_{i}\) to assign it to class \(C_{h}\). This procedure consists of two steps:  
* successively comparing each alternative \(A_{i}\) with the profile limits of classes until the condition that \(P_{j}\) outrank \(A_{i}\) is satisfied;
* assigning alternative \(A_{i}\) to class \(C_{h}\). The optimistic procedure might be favored over the pessimistic one when decision-makers prioritize exploring the upper bounds of potential outcomes or when they are more risk-tolerant. Additionally, in contexts where the consequences of errors are relatively low, the optimistic approach allows for a broader consideration of alternatives based on their best possible performance [43]. For the above-mentioned reasons, in the next case study, we will prioritize results obtained using the pessimistic procedure.