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SIMULATING KNOWLEDGE-GENERATION AND DISTRIBUTION PROCESSES IN INNOVATION COLLABORATIONS AND NETWORKS

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An agent-based simulation model representing a theory of the dynamic processes involved in innovation in modern knowledge-based industries is described. The agent-based approach allows the representation of heterogenous agents that have individual and varying stocks of knowledge. The simulation is able to model uncertainty, historical change, effect of failure on the agent population, and agent learning from experience, from individual research and from partners and collaborators. The aim of the simulation exercises is to show that the artificial innovation networks show certain characteristics they share with innovation networks in knowledge intensive industries and which are difficult to be integrated in traditional models of industrial economics.
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Document Type: Research Article

Affiliations: 1: Economics Department, University of Bremen, Hochschulring, Bremen, Germany 2: School of Human Sciences, University of Surrey, Guildford, Surrey, United Kingdom 3: Research Center Media and Politics, Institute for Political Science, University of Hamburg, Germany

Publication date: September 1, 2007

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