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The evaluation of sustainable development - and, in particular, ruraldevelopment - through composite indices requires taking into account aplurality of indicators, which are related to economic, social andenvironmental aspects. The points of view evaluated by these indices arenaturally interacting: thus, a bonus has to be recognized to units performingwell on synergic criteria, whereas a penalization has to be assigned onredundant criteria. An additional difficulty of the modelization is theelicitation of the parameters for the composite indices, since they aretypically affected by some imprecision. In most approaches, all these criticalpoints are usually neglected, which in turn yields an unpleasant degree ofapproximation in the computation of indices. In this paper we propose amethodology that allows one to simultaneously handle these delicate issues.Specifically, to take into account synergy and redundancy between criteria, wesuitably aggregate indicators by means of the Choquet integral. Further, toobtain recommendations that take into account the space of fluctuation relatedto imprecision in nonadditive weights (capacity of the Choquet integral), weadopt the Robust Ordinal Regression (ROR) and the Stochastic MulticriteriaAcceptability Analysis (SMAA). Finally, to study sustainability not only at acomprehensive level (taking into account all criteria) but also at a locallevel (separately taking into account economic, social and environmentalaspects), we apply the Multiple Criteria Hierarchy Process (MCHP). Weillustrate the advantages of our approach in a concrete example, in which wemeasure the rural sustainability of 51 municipalities in the province ofCatania, the largest city of the East Coast of Sicily (Italy).

Robust sustainable development assessment with composite indices aggregating interacting dimensions: the hierarchical-SMAA-Choquet integral approach