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Using collaborative management in industrial clusters – case study of Italian energy cluster

Taurino T.

Management and Production Engineering Review

2018

Vol. 9, No. 4

138--149

In the current industrial scenarios those involved in production and services distribution are called to deal with a plurality of stakeholders, considering different interests, readings and positions. This paper exploits the concept of collaboration in this fast changes and flexible scenario by describing the characteristics of collaboration among enterprises and their scope. In this context, the purpose of all managers to maximize utility, to save cost or to minimize of transaction costs is hard to be reached. Under this prospective, to collaborate with other firms is a logical way to work and to pursue the previous objectives. The purpose of this paper is to define all the aspects of collaboration, mainly among enterprises, and the reasons that can drive a manager to stipulate a collaboration agreement. Two different ways, through collaboration can rise, have been described: collaboration induced by external body (top-down collaboration) or born in a spontaneous way (bottom-up). The management of the collaboration and the identification of key performance indicators, able to control the development of the network system, is addressed by exploiting the Italian network contract and the case study of the energy cluster.

Pattern recognition from data collection on industry networks

Caroleo B., Taurino T., Antonelli D.

Systems Science

2007

Vol. 33, no 1

81-89

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 on 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.