Simulating Knowledge Dynamics in Innovation Networks

The competitiveness of firms, regions and countries strongly depends on the creation, diffusion and application of new knowledge. Modern innovation research is challenged by the need to incorporate knowledge generation and diffusion processes into the analysis to disentangle the complexity of these dynamic processes. With innovation, however, strong uncertainty, nonlinearities and actor heterogeneity become central, concepts which are at odds with traditional modeling techniques anchored in ideas of equilibrium and homogeneity.§This text introduces SKIN (Simulation Knowledge Dynamics in Innovation Networks), an agent-based simulation model in which joint knowledge creation and exchange of knowledge in innovation co operations and networks is at the core. Knowledge is thereby explicitly modeled and not approximated by, for instance, the level of accumulated R&D investment. The SKIN approach enables applications in different domains ranging from sectoral research activities in knowledge intensive industries to research activities in international research consortia undertaking basic and applied research.§The book contains several applications and modifications of the SKIN model, which is first introduced in a generic way. Each chapter introduces in detail the structure of the model, the relevant methodological considerations and the analysis of simulation results. The possibilities of empirically validating the models structure and outcomes are discussed. The book considers the scope for further applications and outlines possibilities for the development of joint modeling strategies.§