(Georgia Institute of Technology, 2008-09)
Couto Soares, Maria Clara; Cassiolato, José Eduardo
The main objective of this paper is at analyzing how innovation process can contribute
to improve equality in highly unequal societies, taking the example of Brazil. Using as
analytical framework the Innovation System approach and the Latin American
Structuralism perspective, it proposes that besides current broad recognition of science
technology relevance for promoting economic development and competitiveness, it
becomes imperative to advance in such debate in order to include their role for fighting
inequality and promoting social inclusion.
(Georgia Institute of Technology, 2008-09)
Stallivieri, Fabio; Cassiolato, José Eduardo; Campos, Renato Ramos; Britto, Jorge Nogueira de Paiva
The analysis developed aims at identifying patterns regarding the innovative dynamics of
enterprises which comprise Local Innovation and Production Systems (LIPS) in the State of Santa
Catarina (South of Brazil), with basis on a set of 298 interviews made with enterprises from five
LIPS involving the following activities: electrical and metal-mechanical industry, in the region of
Joinville; furniture and wood, in the regions West and Itaguaçu Valley; plastics industry in the
southern region of the state (around Criciuma City); fishing in the estuary of Itajai River. From an
evolutionary theoretical perspective, methodological procedures were adopted for building
indicators that allow for identifying clusters of enterprises that share common patterns of learning,
cooperation and innovation in the scope of the LIPS surveyed. The patterns of innovative effort,
external learning-cooperation and innovative performance are discussed with basis on the results of
cluster analysis techniques applied to groups of enterprises in the sample, which share similar
characteristics regarding chosen factors. Subsequently, a model for categorizing new enterprises
according to identified patterns is suggested. The analysis enabled us to identify three clusters with
similar patterns regarding the characteristics of innovative performance, innovative efforts and
external learning based on cooperative actions. The suggested model for classification obtained a
percentage of accuracy of 96.31%. It is suggested that the innovative dynamics of each LIPS would
be strongly influenced by the relative participation of the enterprises in each of these clusters.