The Spatio-Temporal Distribution of European R&amp;D Networks: Evidence Using Eigenvector Spatially Filtered Spatial Interaction Models

Lata, Rafael; Scherngell, Thomas

doi:10.2139/ssrn.1720945

Cited by 4 publications

(3 citation statements)

References 38 publications

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“…Despite the high variance in databases, levels of analysis and estimation methods, the economic literature on research networks financed under the EU Framework programmes (Autant-Bernard et al 2007;Balland 2012;Caloghirou et al 2004;Breschi and Cusmano 2004;Protogerou et al 2010;Lata and Scherngell 2010;Barber 2009, 2011) shows the existence of an oligopolistic structure in which a restricted number of institution localized in central, high-income regions play a major role along a core-periphery pattern. Thus, we can expect the interregional network structure also to be heavily influenced by the spatial distribution of members and coordinators in the different European regions.…”

Section: Rq1: Does Each Of the Theoretically Imposed Layouts At The Imentioning

confidence: 99%

Does intentional mean hierarchical? Knowledge flows and innovative performance of European regions

2014

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The production of scientific and technical knowledge is mostly concentrated in specific locations (high-tech clusters, innovative industry agglomerations, centres of excellence, and technologically advanced regions). Knowledge flows very easily within regions; however, scientific and technical knowledge also flow between regions. The aim of this paper was to analyse how knowledge flows between regions, and the effect of these flows on the innovative performance, measured by patent applications. We estimate a regional knowledge production function, and, using appropriate spatial econometric estimation techniques, we test the effect of both geographical and relational autocorrelation (measured by participation in EU funded research networks as part of Fifth Framework Programme). We model unobservable structure and link value of knowledge flows in these joint research networks. We find that knowledge Previous versions of this paper were presented at the 7th European Meeting on Applied Evolutionary Economics, Pisa, February 2011; Dimetic Conference on 'Regional Innovation and Growth: Theory, empirics and policy analysis', Pècs, March 2011; Eurolio Conference on the Geography of Innovation, Saint Etienne, January 2012. We thank participants for useful comments and suggestions. In depth, discussions with E. Bergman, P. Elhrost, S. Beretta, B. Dettori, K. Frenken, G. Fagiolo, E. Marrocu, S. Usai and the recommendation from three referees for a thorough revision of the paper have substantially improved its structure and the arguments. The usual caveats apply. flows within inter-regional research networks, along non-symmetrical and hierarchical structures in which the knowledge produced by network participants tends to be exploited by the network coordinator. JEL Classification

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Section: Rq1: Does Each Of the Theoretically Imposed Layouts At The Imentioning

confidence: 99%

Does intentional mean hierarchical? Knowledge flows and innovative performance of European regions

2014

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“…These studies exhibit a high degree of variation in terms of scope, definition of nodes (organization or region) and methodological choice, but they all focus on explaining the determinants of bilateral 3 cooperation based on one-mode network representations (Autant-Bernard et.al., 2007;Paier and Scherngell, 2008;Scherngell and Barber, 2009;Lata and Scherngell, 2010;Broekel and Hartog, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…Obviously, an organization makes some of its decisions simultaneously, and some at different time instances. To the best of our 26 knowledge, Lata and Scherngell (2010) and Balland (2009) addressed this issue for bilateral cooperation networks with a particular interest on the geographical dimension. In addition to that Hanneke et.…”

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confidence: 99%

Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation: Some Empirical Evidence from EU Framework Programs in Biotechnology

Hazir

Autant‐Bernard²

2012

SSRN Journal

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Spatial Econometrics of Innovation: Recent Contributions and Research Perspectives

Autant‐Bernard¹

2012

Spatial Economic Analysis

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Abstract:Preliminary introduced by Anselin, Varga and Acs (1997) spatial econometric tools are widely used in economic geography of innovation. Taking into account spatial autocorrelation and spatial heterogeneity of regional innovation, this paper analyzes how these techniques have improved the ability to quantify knowledge spillovers, to measure their spatial extent, and to explore the underlying mechanisms and especially the interactions between geographical and social distance. It is also argued that the recent developments of spatio-dynamic models opens new research lines to investigate the temporaldimensionofbothspatialknowledgeflowsandinnovationnetworks,twoissues thatshouldrankhighintheresearchagendaofthegeographyofinnovation.

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The Spatio-Temporal Distribution of European R&D Networks: Evidence Using Eigenvector Spatially Filtered Spatial Interaction Models

Cited by 4 publications

References 38 publications

Does intentional mean hierarchical? Knowledge flows and innovative performance of European regions

Does intentional mean hierarchical? Knowledge flows and innovative performance of European regions

Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation: Some Empirical Evidence from EU Framework Programs in Biotechnology

Spatial Econometrics of Innovation: Recent Contributions and Research Perspectives

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