LAUSR

The paper proposes the use of a multiple criteria decision aiding (MCDA) nominal classification method to tackle a dramatic current social problem: the accommodation system for refugees. In recent years, the number of people in need of protection and assistance as a consequence of forced displacement has drastically increased. As many other European cities, Turin (Italy) offers to refugees temporary places for a limited time span, but they are insufficient and often inadequate. Meanwhile, there are several underused buildings that can potentially be used to cover the refugees’ needs of housing and facility. Combining these two aspects, this study aims at contributing to the definition of an urban strategy and improve the decision aiding process related to the accommodation system in Turin. We adopt a recently developed MCDA method to tackle the problem of accommodation of migrants, that is, the Cat-SD (Categorization by Similarity–Dissimilarity) method. We face a nominal classification problem where underused buildings located in the city of Turin are assigned to categories (i.e., three migrant status). A decision model is constructed based on the judgments of the experts. Thus, the application of the method allows to identify an adequate category (or categories) of migrant status for each building.