Structural dynamics of innovation networks in German Leading-Edge Clusters

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe study the effects of a German national cluster policy on the structure of collaboration networks. The empirical analysis is based on original data that was collected in fall 2011 and late summer 2013 with cluster actors (firms and public research organizations) who received government funding. Our resultsshow that over time the program was effective in initiating new cooperation between cluster actors and in intensifying existing linkages. Newly formed linkages are to a substantial amount among actors who did not receive direct funding for a joint R&D project, which indicates an additional, mobilisation effect of the policy. Furthermore, we observe differential developments regarding clusters' spatial embeddedness. Some clusters tend to increase their localisation, whereas others increase their connectivity to international partners. The centrality of large firms increased over time, indicating their prominent role as preferred partners for R&D cooperation within the clusters while it is the opposite case for public actors.

A shot in the dark? Policy influence on cluster networks

“…We also observe an indirect effect of this policy on cohesion, in terms of mean degree and the share of actors in the main component, expressed by the number of actors (Vcount.app) (previously shown to be positively influenced by BioRegio funding). The finding on centralisation supports the views of Töpfer et al (2017), who argue that a small group of actors drives the coordination process within the cluster, which, consequently puts them in a more central position in the knowledge network. 8…”

“…Mean degree is the average number of connections in the unweighted network and Mean strength is the weighted version of mean degree, so that a higher number of common inventors (patents) implies a stronger connection in the applicant Degree centralisation (Centralisation) is a distributional measure of link concentration and is bound between 0 (all actors have the same number of links) and 1 (a star network). There are some indications that cluster policies requiring a common strategy for a large number of otherwise independent actors lead to an increase in centralisation (Töpfer et al, 2017). The proposed reason is that coordination requires a small group of highly active actors, who will be involved in more projects than other participants.…”

Subsidized to change? The impact of R&D policy on regional technological diversification

“…In contrast to subsidies for individual projects, supporting joint R&D projects has a greater potential for stimulating the exploration of new knowledge and activities, as these require collaboration between organizations. Consequently, such support is likely to change organizations' and regions' embeddedness into intra-regional and inter-regional knowledge networks (Fier et al 2006;Wanzenböck et al 2013;Broekel 2015;Töpfer et al 2017). For instance, Broekel et al (2017) measure the technological similarity of partners in subsidized projects and find these to be rather heterogeneous.…”

Effects of Cluster Policies on Regional Innovation Networks: Evidence From France

“…the behavioural additionality of these policies (e.g. Clarysse et al, 2009;Falck et al, 2010;Nishimura and Okamuro, 2011b;Giuliani et al, 2016;Rothgang et al, 2017;Töpfer et al, 2017) 1 . The main goal of this literature is to test the ability of policy interventions to stimulate learning processes that result in changes in actors' behaviour.…”

“…Questions regarding additionality at the network and/or regional level are tackled in a third strand of the cluster evaluation literature (e.g. Bellandi and Caloffi, 2010;He et al, 2013;Ter Wal, 2013;Rothgang et al 2017;Töpfer et al, 2017;Lucena-Piquero and Vicente, 2019). Studies from this strand of research start from the premise that innovation network policies are primarily designed to strengthen innovation networks and build on the theoretical work on the link between network structures and innovation performance.…”