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 -