Approach for analysis, characterization and evolution of the clusters competitiveness

• Grant number: 13/20735-5
• Support Opportunities: Regular Research Grants
• Start date: May 01, 2014
• End date: April 30, 2016
• Field of knowledge: Applied Social Sciences - Administration - Business Administration
• Principal Investigator: Luiz Carlos Di Serio
• Grantee: Luiz Carlos Di Serio
• Host Institution: Escola de Administração de Empresas de São Paulo (EAESP). Fundação Getúlio Vargas (FGV). São Paulo , SP, Brazil
• Associated researchers: Reinaldo Belickas Manzini

Abstract

Over the past twenty years, the study of the cluster phenomenon has attracted increasing attention from both academic and those responsible for public policy development. In Brazil, research on this phenomenon and its application as a tool for regional development, have gained more room since early 1990's by major research projects conducted by prominent authors. Such was the recognition of this issue, that the same has been incorporated under the Planos Plurianuais since 2004 as the preferred approach for the development of small and medium enterprises. Given the current characteristics of the global economy, researchers around the globe have focused on studying the functioning of the clusters and how these benefits for firms, regions and countries. However, little has been produced on their evolution. Therefore, our primary objective of this project is to assist in filling this gap by proposing an approach to analysis, identification and characterization of stages of development of clusters competitiveness, as well as the key factors that influence each. The proposed methodology comprises four stages, namely: (a) The different conceptual perspectives about the industry concentration with specific emphasis on Clusters, (b) The identification and characterization of the industry concentration ,integrating the use of exploratory analysis tools and spatial data exploratory analysis.(c) longitudinal analysis, industry segmentation and choice of industry clusters , (d) longitudinal case studies that were selected in the previous phase c. (AU)