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Abstract
Analysis of business-academia (B-A) collaborations typically relies on a single method, addressing one or two major research questions. In contrast, this article tackles both RD and (ii) different types of firms have different needs. Thus, more refined policy measures are to be devised to promote B-A collaboration more effectively, better tuned to the needs of the actors, based on a relevant taxonomy of their co-operations. Evaluation criteria for academics should also be revised to remove some major obstacles, currently blocking more fruitful B-A co-operation. Several findings can be generalised beyond the cases considered, suggesting the need for a deeper understanding of the role of intermediaries in the Triple Helix and for broader comparative analysis of innovation policies. The research design to analyse B-A collaborations always needs to be tailored to the innovation system in question, just as the concomitant policy recommendations.
Highlights
Innovation has become a paramount issue to economists of all stripes, irrespective of their main research questions and preferred methods, e.g. econometrics, game theoretical models, simulations, controlled experiments or qualitative analyses
Neoclassical economics essentially abandoned research questions concerned with dynamics, and instead focused on static comparative analyses and optimisation
2.1 Linear, networked and multi-channel interactive learning models of innovation The idea that basic research is the main source of innovation was already advanced in the beginning of the twentieth century, mainly by natural scientists and managers of company labs who were comparing large firms, business sectors and national economies by their research and development (R&D) intensities in an attempt to establish the links between R&D activities and economic performance (Fagerberg et al 2011; Godin 2008)
Summary
Innovation has become a paramount issue to economists of all stripes, irrespective of their main research questions and preferred methods, e.g. econometrics, game theoretical models, simulations, controlled experiments or qualitative analyses. For evolutionary economics of innovations, in contrast, since its foundation innovation has been the central theme, and this paradigm has developed a diametrically different theoretical framework to analyse its core questions These competing schools, share some major claims: innovation contributes to enhanced productivity to a decisive extent, creates new opportunities to increase profits, and improves competitiveness at the micro level. The types and quality of links between these actors influence the performance of a given NIS, just as external linkages, that is, the internationalisation of research, technological development and innovation (RTDI) processes and the impacts of external STI policies Of these linkages, only business-academia (B-A) co-operation is discussed in this paper.
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