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The development and deployment of technologies depend upon collaborations concurrently relying on proximity between partners. By employing publication data of German nanotechnology, we augment former findings on the relationship between proximity and collaboration in three ways. First, we shed light on how the various forms of proximity affect different stages of collaboration. Particularly, we split geographical proximity into pure physical and systemic proximity. By doing so, we can show that pure physical proximity plays a role early on, as it positively influences the formation of collaborations. In contrast, systemic proximity affects collaborations later on by inducing higher output. Second, innovation systems shape collaboration networks. We learn that specific features of publicly funded German research organizations influence the formation and output of collaborations via organizational proximity or a lack thereof. Third, cognitive proximity has by far the strongest magnitude of effect on both the formation and the output of collaborations. Particularly, existing partnership being cognitively diverse have a lot of potential. Therefore, research policy and university management might consider to stimulating current partnerships, being cognitively different. [ABSTRACT FROM AUTHOR]

Collaborations are particularly important for the development and deployment of technology. We analyse the influence of organizational, technological and geographical proximity on European nanotechnology collaborations with the help of a publication dataset and additional geographical information. While organizational proximity influences the output of collaborations only indirectly, geographical and technological proximity do so directly. Geographical proximity is most significant in statistical terms and technological proximity has the highest magnitude of effect. Consequently, the latter lends itself most for management and policy interventions, for example, by providing information on technological specialization of potential partners. Resumen Las colaboraciones son especialmente importantes para el desarrollo y el despliegue tecnológico. Se analiza la influencia de la proximidad organizacional, tecnológica y geográfica en colaboraciones europeas en nanotecnología, con la ayuda de un conjunto de datos publicados e información geográfica adicional. Si bien la proximidad organizacional influye en el resultado de las colaboraciones solo de manera indirecta, las proximidades geográfica y tecnológica influyen directamente. La proximidad geográfica es la más significativa en términos estadísticos y la proximidad tecnológica tiene la magnitud del efecto más elevada. Consecuentemente, esta última se presta más a las intervenciones de gestión y de políticas, por ejemplo, facilitando información sobre la especialización tecnológica de socios potenciales. [ABSTRACT FROM AUTHOR]

Studies of knowledge and innovation as driving forces of regional development and growth offer a myriad of approaches. Here, questions asked, methods used and answers given are manifold. In our overview, we cover recent developments in this research area. Moreover, we explore the question as to the extent to which approaches in this research area compete with or complement one another. It turns out that the various studies are much more complementary than competitive. However, there is still much ground to be covered before we fully understand the processes underlying the creation and dissemination of knowledge and innovation leading to regional development and growth. [ABSTRACT FROM AUTHOR]

Innovation fosters structural change and growth and drives socio-economic change. The generation and diffusion of innovation is a dynamic process, which cannot adequately be guided by static policy conceptions. In this paper we will explore the possibility of devising and implementing a ‘learning’ innovation policy. As organisational and technological change is not completely haphazard, we argue that innovation policy can make use of structural regularities in socio-economic change whilst, at the same time, be open to advances in scientific knowledge. We devise a method that achieves these two aims and apply it to a concrete example (knowledge systems). We conclude with practical implications originating from such a ‘learning’ innovation policy. [Copyright &y& Elsevier]

The purpose of the following analysis is to identify the most promising organisational strategies of innovative agents under different environmental constraints. To do so, the processes of the relationships between these agents are taken into account by putting three aspects together. First, it is shown that the transfer, storage, and use of knowledge are significantly influenced by this knowledge's characteristics. Second, the main principles of the generation and selection of innovation are introduced from the systemic point of view. As a third element, the variety of possible relationships between innovative agents are categorised to identify the different organisational principles that can be employed. By putting all these elements together, it is possible to show which strategies are the most promising under different constraints given by the innovation possibilities, the relevant institutions, the knowledge employed, and the kind of innovation expected. [ABSTRACT FROM AUTHOR]