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

K. Bogner, M. Müller, M.P. Schlaile

Research output: Contribution to journalArticleAcademicpeer-review


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.
Original languageEnglish
Pages (from-to)388-407
Number of pages20
JournalInternational Journal of Computational Economics and Econometrics
Issue number3-4
Publication statusPublished - Nov 2018
Externally publishedYes


  • 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 Network


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