Knowledge diffusion in formal networks: the roles of degree distribution and cognitive distance

Kristina Bogner, Matthias Müller and Michael P. Schlaile
Authors registered in the RePEc Author Service: Matthias Mueller

International Journal of Computational Economics and Econometrics, 2018, vol. 8, issue 3/4, 388-407

Abstract: Social networks provide a natural infrastructure for knowledge creation and exchange. In this paper, we study the effects of a skewed degree distribution within formal networks on knowledge exchange and diffusion processes. To investigate how the structure of networks affects diffusion performance, we use an agent-based simulation model of four theoretical networks as well as an empirical network. Our results indicate an interesting effect: neither path length nor clustering coefficient is the decisive factor determining diffusion performance but the skewness of the link distribution is. Building on the concept of cognitive distance, our model shows that even in networks where knowledge can diffuse freely, poorly connected nodes are excluded from joint learning in networks.

Keywords: agent-based simulation; cognitive distance; degree distribution; direct project funding; Foerderkatalog; German energy sector; innovation networks; knowledge diffusion; publicly funded R%D projects; random networks; scale-free networks; simulation of empirical networks; skewness; small-world networks. (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijcome:v:8:y:2018:i:3/4:p:388-407

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