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Analysis the factors for clusters of small and medium sized technology-based enterprises: a study of multiple cases

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Author(s):
Aline Bellintani Calligaris Delbem
Total Authors: 1
Document type: Doctoral Thesis
Press: São Carlos.
Institution: Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD)
Defense date:
Examining board members:
Luiz Cesar Ribeiro Carpinetti; Edmundo Escrivão Filho; Renato de Castro Garcia; Fábio Müller Guerrini; Ana Lúcia Vitale Torkomian
Advisor: Luiz Cesar Ribeiro Carpinetti
Abstract

The literature specialized in clusters of small and medium-sized enterprises (SMEs) shows that, when companies take joint actions, they may gain competitive advantages, besides other benefits. Studies in clusters have identified important aspects involving themes such as typology, governance, evolutionary stages, collective efficiency, external economies, cooperation, and competition. These studies, however, do not carry out a comparative analysis regarding the interference of certain factors in the success of technology-based clusters, considered to be a particular type of companies\' agglomeration. With the objective of identifying the main success factors that can interfere significantly in the development of this kind of cluster, a study of multiple cases was carried out, involving three clusters in the interior of the State of São Paulo, situated in important technology parks located in the cities of Campinas, São Carlos and São José dos Campos. Initially, a bibliographical review on the important success factors of clusters in general was carried out. Based on this data, a research framework was established in order to be applied in the interviews conducted in the companies. The data collected were analyzed with the aid of the software Qualitative Solutions and Research, which enables the insertion and analysis of qualitative data. Based on the results obtained, a group of 5 success factors was identified; the incidence of each of these factors was also analyzed in each of the clusters studied, showing that the factors company profile and management were the most important. (AU)