Recently we have proposed a simple model of knowledge transfer within an organization [1] based on cellular automata technique [2]. The main goal of this paper was to check which factors influence the efficiency of knowledge transfer. In model organization agents send and receive chunks of knowledge only when numbers of knowledge chunks possessed by sender and receiver are very similar. Namely, we assume that such transfer is possible only when sender has exactly one more chunk of knowledge than recipient. This strong restriction on knowledge transfer influences negatively the efficiency of knowledge transfer what results in decreasing the average number of knowledge chunks possessed by the whole organization for relatively high values of initial concentration of chunks of knowledge within the organization. The latter effect is rather counterintuitive but vanishes when agents may receive chunks of knowledge from senders having the same or greater number of chunks of knowledge than receivers [3].

Now, we would like to check how the range of interaction influence the efficiency of knowledge transfer. Namely, we extend the neighbourhood considered in Refs. [1, 3] from von Neumann neighbourhood to the Moore's one. On square lattice—when von Neumann neighbourhood is assumed—the site at coordinate (x, y) has exactly four neighbours at (x–1, y), (x+1, y), (x, y–1) and (x, y+1). For Moore's neighbourhoods also sites at (x–1, y–1), (x+1, y–1), (x–1, y+1) and (x+1, y+1) belong to the neighbourhood. Our preliminary results indicate that increasing range of interaction make the knowledge transfer more effective.

The Java applet allowing for system evolution observation is available at http://www.zis.agh.edu.pl/knowledge_transfer/.

This research was supported by National Science Centre (NCN) in Poland (grant no. UMO-2014/15/B/HS4/04433).

[1] A. Kowalska-Styczeń, K. Malarz, K. Paradowski, Model of knowledge transfer within an organization, (2017) – to be published.

[2] S. Wolfram, A new kind of science, (Wolfram Media, 2002).

[3] A. Kowalska-Styczeń, K. Malarz, K. Paradowski, Searching for effective way of knowledge transfer within an organization, (2017) – to be published.

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