Prof. Dr. Andreas Pyka
Universität Hohenheim, Germany
Abstract - Keynote speach
Innovation Networks: Modeling and Analyzing Complex Innovation Processes
Today innovation networks are widely considered as promising organizational devices for complex innovation processes. In innovation networks various actors like large diversified firms, small and medium sized companies, start-ups and public research institutes mutually exchange and develop new technological knowledge. Due to the increasing complexity of innovation processes which is related to the combinatorial character of technologies, single actors can hardly master not to mention improve all relevant knowledge fields. Innovation networks instead allow actors to excel in their core competences, they provide the prerequisites for a flexible coordination of knowledge interfaces, and trigger creative processes by cross-fertilizing between different and seemingly unrelated knowledge fields.
Despite their widely acknowledged advantageous features innovation networks are still considered as rather puzzling from an economics and management science based view. The reason for this is the complex nature of innovation networks which eludes from being analyzed with traditional methodologies. The actors are extremely heterogeneous concerning their knowledge, their experience, their economic size and their strategic behavior. Additionally, the structure of the networks is supposed to continuous changes following the interaction patterns of the involved agents. This leads to strong non-linearities responsible for self-amplifying effects and critical thresholds shaping the emergence and evolution of innovation networks. With modern tools encompassing agent-based modeling techniques and social network analysis innovation networks, nevertheless, become analytically treatable and can be described in their dynamic appearance.
The presentation is about the current approaches from Neo-Schumpeterian Economics and innovation sociology (e.g. Ahrweiler, Pyka, Gilbert 2011a, b) dealing with the phenomenon of innovation networks, the approaches to model their development as well as empirically analyze their complexity. From this also conclusions for a policy design can be derived which focus on the support of innovation networks and in particular the role of SME's without abstracting from their complex nature.
References:
Ahrweiler, P., Pyka, A. and Gilbert, N. (2011a), A new model for university-industry links in knowledge-based economies, in: Journal of Product Innovation Management, Vol.27 (2), 218-235.
Ahrweiler, P., Pyka, A. and Gilbert, N. (2011b), Agency and Structure. A social Simulation of knowledge-intensive Industries', in: Computational & Mathematical Organization Theory, Vol. 17 (1), 59-76.
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