TITLE

PATTERN RECOGNITION FROM DATA COLLECTION ON INDUSTRY NETWORKS

AUTHOR(S)
CAROLEO, BRUNELLA; TAURINO, TERESA; ANTONELLI, DARIO
PUB. DATE
March 2007
SOURCE
Systems Science;2007, Vol. 33 Issue 1, p81
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
The paper proposes different approaches for the analysis of data and for the performance evaluation of the organization and management inside industry clusters all over Europe. The models adopted for the analysis of the data are derived from different disciplines ranging from statistic multivariate analysis to operational research. The data collection was gathered as an outcome for the European Project CODESNET devoted to the research in the domain of the demand and supply networks. Industry clusters belong to a wide number of European countries and were chosen without any limitations to the kind of activity carried on by the participating industries. Data were collected in the framework of a meta-model of the cluster organization which includes three macro areas: Operation Structure. Organization Arrangement and Interaction with Socio-Economic Environment. After a description of a logical arrangement of available information, a pattern recognition procedure useful to fully analyse an industrial network, using both data/information from existing SME networks and technical/scientific reports, is presented.
ACCESSION #
37837490

 

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