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Digital Library of the
European Council for Modelling and Simulation |
Title: |
Confidential Areas In Innovation Communities: An Agent-Based Model
Using Fuzzy Logic and Qualitative Empirical Data |
Authors: |
Michael A. Zaggl, Benjamin
Stahl, Zeng Zhong |
Published in: |
(2015).ECMS 2015 Proceedings edited
by: Valeri M. Mladenov, Grisha Spasov, Petia Georgieva, Galidiya Petrova, European
Council for Modeling and Simulation. doi:10.7148/2015 ISBN:
978-0-9932440-0-1 29th
European Conference on Modelling and Simulation, Albena (Varna), Bulgaria,
May 26th – 29th,
2015 |
Citation
format: |
Michael A. Zaggl, Benjamin Stahl, Zeng Zhong (2015).
Confidential Areas In Innovation Communities:
An Agent-Based Model Using Fuzzy Logic and Qualitative Empirical Data, ECMS
2015 Proceedings edited by: Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova
European Council for Modeling and Simulation. doi:10.7148/2015-0050 |
DOI: |
http://dx.doi.org/10.7148/2015-0050 |
Abstract: |
This paper
examines the relationship between social and utilitarian incentives in
innovation communities. We develop an agent-based model using insights from a
qualitative empirical study. This method combination is motivated by
shortcomings of empirical research to capture the dynamics and the
interactions between social and utilitarian incentives. Thus, we use the
synergy between complex systems thinking and its strengths in modeling in
combination with qualitative empirical research, which is powerful to
recognize phenomena. The problem of incorporating decisions
driven by multiple motivations is approached by including fuzzy interfaces in
the model. With the method combination of qualitative empirical research,
agent-based modeling, and fuzzy logic we can answer questions of social and
utilitarian motives and their relation to innovation performance in
communities. We find that community members do not only want to innovate but
have social motives in addition. Further, some innovation communities have areas which we call confidential areas. These are areas for
high performers. In the simulation we find that such confidential areas
improve innovation performance. However, this effect depends on the access
restriction. The contribution of this paper is twofold. First, it improves
the understanding of innovation communities and the incentives for
contributing. The extant literature on innovation management profits from a dynamic
perspective on community-based innovation. Second, we provide a novel method combination
that is useful for capturing complex phenomena from the empirical
perspective. |
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