La complessità strutturale dei distretti industriali: un approccio basato sulle similarità multi-dimensionali Structural complexity in industrial districts: a multi-dimensional similarity approach. This study analyses spatial agglomerations starting from the premise that their intrinsic socio-economic complexity is a crucial factor in the shaping of local development paths. With the help of a family of artificial neural networks known as Self-organising Maps (SOM), the study obtains an original mapping of productive agglomerations in Italy, and thereby a characterization that goes beyond the notion of specialization and rests on the idea of multi-dimensional similarity in the distribution of resources.
