According to the theoretical foundations of Decision Theory and Multicriteria Decision Analysis (MCDA), the evaluation criteria that frame a decision problem must be independent and non-redundant to each other. However, this is unavoidable in many modelling instances and the decision problems can be characterized by complex criteria dependences, which can hamper the development of an efficient and technically sound decision model. In these cases, the dependences, called criteria interactions, are addressed with various methodological frameworks that usually require for their quantification specific preference statements by the decision maker (Bottero et al. 2018).
The different kinds of criteria interactions that have been identified in the literature include mutual strengthening, mutual weakening and antagonistic relationships, for the case of pairs, triplets or more complex groupings of criteria.Several intricate decision problems, such as the evaluation of electricity supply sustainability and resilience or the assessment of risk in energy investments and climate policy making, include such interacting criteria, which, without the appropriate modelling processing and treatment, can endanger the validity of the model and its results.
The modern practical challenge in the MCDA scientific community lies in the facilitation of decision making in a real context, and the construction of accurate and robust models, when interactive criteria exist. Recent work in this direction has been advanced by (Siskos and Burgherr, 2021 and Angilella et al. 2018 among others). In these cases, criteria interactions are mostly approached:
- with the elimination of criteria overlaps and synergistic effects, right at the modelling stage. This is performed by searching for more consistent and cleaner data and indicators or by merging interacting dimensions to reduce the possible side effects in the application of a multi-criteria method
- with the application of MCDA methods, such as the Choquet integral, which account and address criteria interactions but require additional and often more demanding preference input by the decision maker.
Angilella, S., Catalfo, P., Corrente, S., Giarlotta, A., Greco, S., Rizzo, M. (2018), Robust sustainable development assessment with composite indices aggregating interacting dimensions: The hierarchical-SMAA-Choquet integral approach, Knowledge-Based Systems, 158, pp. 136-153.
Bottero, M., Ferretti, V., Figueira, J.R., Greco, S., Roy, B. (2018). On the Choquet multiple criteria preference aggregation model: Theoretical and practical insights from a real-world application, European Journal of Operational Research, 271(1), pp. 120-140.
Siskos, E., Burgherr, P. (2021), Multicriteria decision support for the evaluation of electricity supply resilience: Exploration of interacting criteria, European Journal of Operational Research, under review.