Synopsis
This book explores how complexity science and social simulation can be used to improve and inform policy-making in both research and innovation. Beginning with an introduction to conceptual definitions of complexity science and social simulation, the book demonstrates the validity of the underlying integrated research framework used throughout. It is then divided into two parts, with the first investigating the effects and impacts of policy making on the structure, composition and outputs of research and innovation networks using the agent-based SKIN platform (Simulating Knowledge Dynamics in Innovation Networks, http://cress.soc.surrey.ac.uk/SKIN/). The second half of the book discusses a research initiative funded by the Irish government focusing on innovation policy simulation for economic recovery. This consists of empirical research on Irish research and innovation networks, and SKIN-based simulations of technology transfer issues and the commercialization of research in areas with high potential for innovation and economic growth. The book concludes with reflections on the maturity and utility of an approach combining complexity science and social simulation for research and innovation policy. Joining Complexity Science and Social Simulation for Innovation Policy will be of particular interest to scientists concerned with innovation and complex systems, including economists, sociologists, and complexity researchers, as well as students and practitioners, such as innovation policymakers and innovation business managers.
About the Author
Petra Ahrweiler is Professor of Sociology at Johannes Gutenberg University Mainz in Germany, and the Director of the EA European Academy of Technology and Innovation Assessment, a publicly funded research organisation in Rhineland-Palatinate. Her publications include Innovation in Complex Social Systems (2010); A New Model for University-Industry Links in Knowledge-Based Economies in Journal of Product Innovation Management; and In Search of a Network Theory of Innovations: Relations, Positions, and Perspectives in Journal of the American Society for Information Science and Technology. Nigel Gilbert is Professor of Sociology at the University of Surrey, Guildford, UK, and Director of the Centre for Research in Social Simulation. His publications include Agent-based Models (2008); Computational Social Science (2010); and Simulating Innovation: Computer-based Tools for Rethinking Innovation (2014). Andreas Pyka is Professor and Chair in Innovation Economics at the Economics Institute at the University of Hohenheim. His publications include Innovation Networks in Economics From the incentive-based to the knowledge-based Approaches in the European Journal of Innovation Management (2002), Learning-by-modelling: Insights from an Agent-Based Model of University Industry Relationships in Cybernetics and Systems (2015) and Avoiding evolutionary inefficiencies in innovation networks in Prometheus (2015).
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