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Article type: Research Article
Authors: Pilotti, Luciano
Affiliations: Department of Economics “M. Fanno”, Padua University, 35122 Padua, Italy. E-mail: pilotti@decon.unipd.it
Abstract: This work is the last part of a unitary framework of analysis, the first part of which was published in HSM, Special Issue, Vol. 18, No. 2. The principal aim of the analysis is the pattern of transformation of local production systems. They are discussed as a complex institutional form of the division of labour and knowledge between firms by means of institutions and meta-organisers as actors of a post-Fordist local economy. A specific production system is defined as a peculiar governance form of interrelations, mediated by cognitive resources such as internal/external competencies of a population of firms localised in a sharing context. In this way there emerges a process of internalisation of competencies through evolutionary networking in which efficiency is not simply an output but a fundamental input for both growth and innovation. Our aim is to describe the peculiarity of the institutional networking system in the Italian case of Northeast industrial districts, assuming that a specific industrial economy evolves on the basis of differentiated learning capacities according to a complex system of economic and social relations, encouraging the circulation of useful knowledge and information for the economic enlargement based on industrial leadership and firm networks: they form a complex and dynamic Multilevel Neural Network. Two main types of district emerge: the evolutionary district (e.g., Montebelluna, specialised in ski-boot production) and non evolutionary static and adaptive districts (e.g., Maniago, specialised in knife production), where we find limited leadership and limited division of labour between firms.
Keywords: Local production system, district, institution, learning, knowledge, network corporate governance, meta-organizer
DOI: 10.3233/HSM-2000-19206
Journal: Human Systems Management, vol. 19, no. 2, pp. 121-133, 2000
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