Publications (20) View all
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Article: Agency and structure: a social simulation of knowledge-intensive industries
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ABSTRACT: Modern knowledge-intensive economies are complex social systems where intertwining factors are responsible for the shaping of emerging industries: the self-organising interaction patterns and strategies of the individual actors (an agency-oriented pattern) and the institutional frameworks of different innovation systems (a structure-oriented pattern). In this paper, we examine the relative primacy of the two patterns in the development of innovation networks, and find that both are important. In order to investigate the relative significance of strategic decision making by innovation network actors and the roles played by national institutional settings, we use an agent-based model of knowledge-intensive innovation networks, SKIN. We experiment with the simulation of different actor strategies and different access conditions to capital in order to study the resulting effects on innovation performance and size of the industry. Our analysis suggests that actors are able to compensate for structural limitations through strategic collaborations. The implications for public policy are outlined. KeywordsInnovation networks–Agent-based social simulation–Innovation systemsComputational and Mathematical Organization Theory 04/2012; 17(1):59-76. · 0.39 Impact Factor -
Article: A New Model for University‐Industry Links in Knowledge‐Based Economies*
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ABSTRACT: In this paper, we apply the agent-based SKIN model (Simulating Knowledge Dynamics in Innovation Networks) to university-industry links. The model builds on empirical research about innovation networks in knowledge-intensive industries with procedures relying on theoretical frameworks of innovation economics and economic sociology. Our experiments compare innovation networks with and without university agents. Results show that having universities in the co-operating population of actors raises the competence level of the whole population, increases the variety of knowledge among the firms, and increases innovation diffusion in terms of quantity and speed. Furthermore, firms interacting with universities are more attractive for other firms when new partnerships are considered. These results can be validated against empirical findings. The simulation confirms that university-industry links improve the conditions for innovation diffusion and enhance collaborative arrangements in innovation networks.Journal of Product Innovation Management 02/2011; 28(2):218 - 235. · 2.11 Impact Factor -
Chapter: Agent-Based Modelling of Innovation Networks – The Fairytale of Spillover
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ABSTRACT: Today’s knowledge-based economies are more than places where goods and services are bought and sold; they are the sites where complex logistic processes are coordinated, where innovation takes place, where knowledge is generated, communicated, re-combined and exchanged. In such competitive and knowledgeintensive environments characterized by price as well as innovation competition and in which there are quickly changing global technological and economic requirements (Bahlmann, 1990; Hanusch and Pyka, 2007a) and a variety of institutional infrastructures (Amable, 2003; Hanusch and Pyka, 2007b), a firm can improve its performance only by exploiting resources more creatively and intelligently than its competitors (Lam, 2003).05/2010: pages 101-126; -
Article: Simulating Knowledge-Generation and -Distribution Processes in Innovation Collaborations and Networks
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ABSTRACT: 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 al-lows the representation of heterogeneous 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.09/2006; -
Conference Proceeding: The Epistemologies of Social Simulation Research.
Epistemological Aspects of Computer Simulation in the Social Sciences, Second International Workshop, EPOS 2006, Brescia, Italy, October 5-6, 2006, Revised Selected and Invited Papers; 01/2006
