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La complessit? strutturale dei distretti industriali: un approccio basato sulle similarit? multi-dimensionali

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  • Pierluigi Sacco
  • Vittorio Carlei
  • Massimiliano Nuccio
  • Massimo Buscema

Abstract

La complessit? strutturale dei distretti industriali: un approccio basato sulle similarit? 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.

Suggested Citation

  • Pierluigi Sacco & Vittorio Carlei & Massimiliano Nuccio & Massimo Buscema, 2008. "La complessit? strutturale dei distretti industriali: un approccio basato sulle similarit? multi-dimensionali," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2008(2), pages 55-86.
    • Handle: RePEc:fan:scresc:v:html10.3280/scre2008-002003
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    Cited by:

    1. colantonio emiliano & perrucci antonella, 2015. "The Eu In The Knowledge Era: An Exploratory Analysis," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 189-197, December.
    2. V. Carlei & E. Colantonio & D. Furia & N. Mattoscio, 2011. "Economic patterns of sustainable development: an analysis of absolute ecological footprint through self-organizing map," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(1), pages 157-171, January.

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