The paper presents a new approach based on Self-Organizing Maps (SOM) and a new index called Relative Industrial Relevance (RIR) to discover, track and analyze spatial agglomeration of economic activities. By comparing patterns of local employment, this methodology shows how the local supply of human capital can explain the advantages generating spatial agglomerations. The reference case for this research is Italy, which has developed one of the most remarkable and studied example of spatial agglomerations, the Industrial Districts (IDs). IDs are traditionally identified by indexes which measure the physical concentration of firms belonging to a given industry, but are unable to seize the overall productive structure of the local economy. Employing the Italian Clothing Industry as test bed, the approach proposed in this paper identifies spatial agglomerations in terms of industry patterns and not of industry concentration. This methodology can offer a new basis to analyze the multiple pattern of local development.
|Journal||Pattern Recognition Letters|
|Early online date||14 Dec 2013|
|Publication status||Published - 15 Apr 2014|
- self-organizing maps
- pattern recognition
- spatial agglomeration
- industrial districts