Mapping industrial patterns in spatial agglomeration: A SOM approach to Italian industrial districts
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In: Pattern Recognition Letters, Vol. 40, 15.04.2014, p. 1-10.
Research output: Journal contributions › Journal articles › Research › peer-review
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TY - JOUR
T1 - Mapping industrial patterns in spatial agglomeration
T2 - A SOM approach to Italian industrial districts
AU - Carlei, Vittorio
AU - Nuccio, Massimiliano
PY - 2014/4/15
Y1 - 2014/4/15
N2 - 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.
AB - 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.
KW - Culture and Space
KW - industrial districts
KW - pattern recognition
KW - self-organizing maps
KW - spatial agglomeration
UR - http://www.scopus.com/inward/record.url?scp=84891720439&partnerID=8YFLogxK
U2 - 10.1016/j.patrec.2013.11.023
DO - 10.1016/j.patrec.2013.11.023
M3 - Journal articles
AN - SCOPUS:84891720439
VL - 40
SP - 1
EP - 10
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
SN - 0167-8655
ER -