It's a match! Simulating compatibility-based learning in a network of networks
Authored by Michael P Schlaile, Johannes Zeman, Matthias Mueller
Date Published: 2018
DOI: 10.1007/s00191-018-0579-z
Sponsors:
German Research Foundation (Deutsche Forschungsgemeinschaft, DFG)
Platforms:
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Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
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Abstract
In this article, we develop a new way to capture knowledge diffusion and
assimilation in innovation networks by means of an agent-based
simulation model. The model incorporates three essential characteristics
of knowledge that have not been covered entirely by previous diffusion
models: the network character of knowledge, compatibility of new
knowledge with already existing knowledge, and the fact that
transmission of knowledge requires some form of attention. We employ a
network-of- networks approach, where agents are located within an
innovation network and each agent itself contains another network
composed of knowledge units (KUs). Since social learning is a
path-dependent process, in our model, KUs are exchanged among agents and
integrated into their respective knowledge networks depending on the
received KUs' compatibility with the currently focused ones. Thereby, we
are also able to endogenize attributes such as absorptive capacity that
have been treated as an exogenous parameter in some of the previous
diffusion models. We use our model to simulate and analyze various
scenarios, including cases for different degrees of knowledge diversity
and cognitive distance among agents as well as knowledge exploitation
vs. exploration strategies. Here, the model is able to distinguish
between two levels of knowledge diversity: heterogeneity within and
between agents. Additionally, our simulation results give fresh impetus
to debates about the interplay of innovation network structure and
knowledge diffusion. In summary, our article proposes a novel way of
modeling knowledge diffusion, thereby contributing to an advancement of
the economics of innovation and knowledge.
Tags
agent-based simulation
Agent-based modeling
Evolution
Innovation
Dynamics
emergence
Learning
Exploitation
Exploration
Innovation networks
information
Knowledge Diffusion
Social-influence
Absorptive-capacity
Attention
Cognitive distance
Knowledge compatibility
Knowledge
diffusion
Knowledge networks
Memetics
Network-of-networks