ABSTRACT
Innovation policymakers, business managers and the public often expect that the current investments in R&D, higher education institutions, science-industry networks etc. will immediately produce a flow of products and processes with high commercial returns. The disappointments and legitimatory problems arising from missing outputs are considerable and show the limits of steering, control and policy functions. Although there is not a fundamental apprehension against the importance of knowledge and innovation, the responsible innovation managers mention a frustration with the too messy and complicated features of the innovation process, which simply ‘does not seem to compute’. Innovation, the creation of new, technologically feasible, commercially realizable products, processes and organizational structures (Schumpeter 1912, Fagerberg et al. 2006), is emerging from an ongoing interaction process of innovative organizations such as universities, research institutes, firms, government agencies, venture capitalists and others. These organizations generate and exchange knowledge, financial capital, and other resources in networks of relationships, which are embedded in institutional frameworks on the local, regional, national and international level (Pyka and Kueppers 2003). Innovation is an emergent property from these interactions on the micro level – if the combination of actors and organizations, their compatible capabilities, and their cooperative behaviors match. No equation will predict this match or warn of a mismatch beforehand. This book now has something new to say about innovation. Its contributions make full use of cutting-edge methods coming from the natural and social sciences, from computer science, and mathematics to deal with the complex aspects of socio-economic innovation processes – and this without leaving out the messy features of empirical reality and the ‘human element’, but indeed taking full account of it. Its approach, as highlighted by its title, opens up a new paradigm for innovation research: the contributions analyze innovation in complex social systems while making innovation understandable and tractable using tools such as computational network analysis and agent-based simulation. This introduction will address the question of how a coherent research program might arise from the title of the book, by discussing theoretical and methodological issues around researching innovation in complex social systems... It will also outline a perspective on innovation, which is more or less
shared by the authors of this volume, and finally, the chapter will take on the usual task of an introduction and present the concept and structure of this book while outlining briefly the role of the individual contributions.
