Overview
- Edited and authored by leading researchers in the field
- Self-contained introduction into a new and well-tested modelling technique
- Contains case studies
Part of the book series: Understanding Complex Systems (UCS)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (10 chapters)
-
Front Matter
-
Innovation Strategies
-
Front Matter
-
-
Testing Policy Options
-
Front Matter
-
-
Applying SKIN to Innovation Sectors
-
Front Matter
-
-
Back Matter
Keywords
About this book
The competitiveness of firms, regions and countries greatly depends on the generation, dissemination and application of new knowledge. Modern innovation research is challenged by the need to incorporate knowledge generation and dissemination processes into the analysis so as to disentangle the complexity of these dynamic processes. With innovation, however, strong uncertainty, nonlinearities and actor heterogeneity become central factors that are at odds with traditional modeling techniques anchored in equilibrium and homogeneity.
This text introduces SKIN (Simulation Knowledge Dynamics in Innovation Networks), an agent-based simulation model that primarily focuses on joint knowledge creation and exchange of knowledge in innovation co‐operations and networks. In this context, knowledge is explicitly modeled and not approximated by, for instance, the level of accumulated R&D investment. The SKIN approach supports applications in different domains ranging from sector-based research activities in knowledge-intensive industries to the activities of international research consortia engaged in basic and applied research.
Following a general description of the SKIN model, several applications and modifications are presented. Each chapter introduces in detail the structure of the model, the relevant methodological considerations and the analysis of simulation results, while options for empirically validating the models’ structure and outcomes are also discussed. The book considers the scope of further applications and outlines prospects for the development of joint modeling strategies.
Editors and Affiliations
Bibliographic Information
Book Title: Simulating Knowledge Dynamics in Innovation Networks
Editors: Nigel Gilbert, Petra Ahrweiler, Andreas Pyka
Series Title: Understanding Complex Systems
DOI: https://doi.org/10.1007/978-3-662-43508-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Business and Economics, Business and Management (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2014
Hardcover ISBN: 978-3-662-43507-6Published: 05 August 2014
Softcover ISBN: 978-3-662-51148-0Published: 23 August 2016
eBook ISBN: 978-3-662-43508-3Published: 22 July 2014
Series ISSN: 1860-0832
Series E-ISSN: 1860-0840
Edition Number: 1
Number of Pages: XII, 248
Number of Illustrations: 34 b/w illustrations, 37 illustrations in colour
Topics: Innovation/Technology Management, Data-driven Science, Modeling and Theory Building, Simulation and Modeling, Complexity, Operations Research/Decision Theory