Abstract
A multidimensional unfolding technique that is not prone to degener-ate solutions and is based on multidimensional scaling of a complete data matrix isproposed. We adopt the strategy of augmenting the data matrix, trying to build acomplete dissimilarity matrix, by using Copulas-based association measures amongrankings (the individuals), and between rankings and objects (namely, a rank-orderrepresentation of the objects through tied rankings). The proposed technique leads toacceptable recovery of given preference structures.