Confidentiala "Mode 3" Systems Approach for Knowledge Creation, Diffusion and Use: Towards a 21st Century Fractal Innovation Ecosystem. ACES Working Paper (Report) No. 4, 2007

"Mode 3" allows and emphasizes the co-existence and co-evolution of different knowledge and innovation paradigms: the competitiveness and superiority of a knowledge system is highly determined by its adaptive capacity to combine and integrate different knowledge and innovation modes via co-evolution, co-specialization and coopetition [sic] of knowledge stock and flow dynamics. What results is an emerging fractal knowledge and innovation ecosystem, well-configured for the knowledge economy and society. The intrinsic litmus test of the capacity of such an ecosystem to survive and prosper in the context of continually glocalizing [sic] and intensifying competition represents the ultimate competitiveness benchmark with regards to the robustness and quality of the ecosystem's knowledge and innovation architecture and topology.

R&D, Spillovers, Innovation Systems and the Genesis of Regional Growth in Europe. Bruges European Economic Research (BEER) Papers 5/October 2006

Research on the impact of innovation on regional economic performance in Europe has fundamentally followed three approaches: a) the analysis of the link between investment in R&D, patents, and economic growth; b) the study of the existence and efficiency of regional innovation systems; and c) the examination of geographical diffusion of regional knowledge spillovers. These complementary approaches have, however, rarely been combined. Important operational and methodological barriers have thwarted any potential cross-fertilization. In this paper, we try to fill this gap in the literature by combining in one model R&D, spillovers, and innovation systems approaches. A multiple regression analysis is conducted for all regions of the EU-25, including measures of R&D investment, proxies for regional innovation systems, and knowledge and socio-economic spillovers. This approach allows us to discriminate between the influence of internal factors and external knowledge and institutional flows on regional economic growth. The empirical results highlight how the interaction between local and external research with local and external socioeconomic and institutional conditions determines the potential of every region in order to maximise its innovation capacity. They also indicate the importance of proximity for the transmission of economically productive knowledge, as spillovers show strong distance decay effects. In the EU-25 context, only the innovative efforts pursued within a 180 minute travel radius have a positive and significant impact on regional growth performance.