By Frank Lasch, Frank Robert, Frédéric Le Roy, Roy Thurik (auth.), João J.M. Ferreira, Mário Raposo, Roel Rutten, Attila Varga (eds.)
Cooperation and clusters became the guiding paradigms for explaining and selling local competitiveness, however the cooperation approach among organisations and universities and the move of data in guiding and nurturing local competitiveness has obtained fairly little cognizance. This publication strives to fill this hole in highlighting the relationship among inter-firm cooperation in nearby clusters, innovation and nearby networks, and the function of universities in them . It is going past the normal fiscal method of clusters and comprises ‘soft elements’ within the rationalization of local competitiveness, and connects the literature on clusters to the literature of studying and information construction as assets of neighborhood competitiveness. It goals to foster a world and interdisciplinary alternate of views through proposing present advancements, case reports, most sensible practices in addition to new built-in theoretical techniques and applications.
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Extra resources for Cooperation, Clusters, and Knowledge Transfer: Universities and Firms Towards Regional Competitiveness
They were conducted from June 2007 to August 2010 as part of my doctoral work (Hermans 2011). Drawing on them, I explore how power interactions shape the processes of knowledge creation and exchange between partners. The empirical material comprises data collected through semistructured interviews, documentation, and observation.
We find no support for H3b. H3c (private capital) tests the local private investment potential for entrepreneurship suggesting a positive relationship for richness (share of householders) and a negative one for poverty (share of population living under social minima standards). Neither measure is significant. We find no support for H3c. H3d (social diversity) uses one variable (share of foreigners) and is confirmed by the regression result. The variables for H4a (university knowledge spillovers), H4b (R&D knowledge spillovers), and H4c (geographical proximity) are all statistically significant.
2013 for more results). Our work is not free of limits that are mainly linked to the methodological choice of the level of analysis (aggregate regional level). Our findings call to be tested using variables on individual or organizational levels of analysis. A replication of this study using other sectors as control variable would in our eyes provide additional results on the stability and generalization of location factors. Surprising results, such as perverse effects for the influence of firm survival rates and educational attainment and weak results for knowledge spillovers, present other challenges for future research.