Suchergebnisse

O artigo visa analisar as capacidades de inovação predominantes em startups, com base no modelo de capacidades de Zawislak et al. (2013), que compreende as capacidades de desenvolvimento, de operação, de gestão e de transação. Para tanto, realizou-se um estudo do tipo exploratório com seis empresas: quatro stratups e duas firmas, sendo que essas iniciaram as suas respectivas trajetórias como startups. Os resultados revelam, primeiramente, que as startups possuem apenas as capacidades de desenvolvimento e de transação, enquanto as firmas possuem as quatro capacidades desenvolvidas. As capacidades de operação e de gestão, além de serem inexistentes ou incipientes nas startups, passam a integrar as suas rotinas apenas na medida em que elas se consolidam e crescem como organização. Além disso, destaca-se também que a rede de relacionamentos das startups é um dos fatores de maior importância nos primeiros anos da startup, tendo em vista a necessidade de obter acesso a investidores e potenciais clientes. Palavras-chave: Startup. Capacidades de Inovação. Brasil.

Purpose
The purpose of this paper is to propose a new typology to leverage the different knowledge gaps existing between universities and industries. This new typology classifies interactions into training-oriented, diffusion-oriented, service-oriented, development-oriented, and research-oriented.


Design/methodology/approach
The Brazilian 2010 Census data available from the CNPq Research Group Directory were used to test the typology.


Findings
It was found that, among the five types of interactions proposed, the most frequent were the development-oriented (39 per cent), diffusion-oriented (23 per cent), and research-oriented (16 per cent) ones. These findings indicate that it is likely that university-industry (U-I) interactions have improved in terms of quality in an attempt to attain a joint higher technological development.


Originality/value
The paper provides the U-I interaction debate with a new perspective about the kinds of interactions that could effectively bridge the knowledge gaps between universities and industries, especially in a developing country context.

Abstract: This study aims to analyze technological knowledge and information flows intra and extra-cluster, as well as the cognitive roles the firms play. It was decided to investigate such flows among firms and institutions that compose the wine cluster of Vale dos Vinhedos, mountain region of Rio Grande do Sul, responsible for approximately 90% of the national wine production. The social network method was used for this article. As main results, it is highlighted: the information flow has a distinct dynamic from the technological knowledge flow established among firms; they play different cognitive roles in the identified technological knowledge network; great part of the connections established is with companies from the cluster itself; and the search for knowledge in support institutions in the area is intense, highlighting the importance of geographical proximity in the established relations.

Abstract
Entrepreneurial universities have become a key concept in debates concerning regional economic development. Yet, we still fall short of having a clear comprehension of the enablers of such localized impacts arising from academic activity. Such conditions are particularly critical for the context of developing countries, which have mostly mimicked initiatives taking place in the context of developed markets. To address these issues, we analyze the impacts generated by research-intensive universities on local innovation ecosystems. We apply a combination of econometric and case study methods for the state of São Paulo, Brazil. Results suggest that research-intensive universities, mostly public universities, positively impact their respective innovation ecosystems. Moreover, qualified research funds and the existence of a support structure (incubators and science and technology parks) significantly enhance the impacts generated by research-intensive universities. These findings highlight the relationship between the internal constraints of universities and their capacity to generate impacts on local ecosystems.