Social Network Analysis for Tacit Knowledge Management in Universities

The paper assesses Master students’ collaboration in a common research project by using social networks modeling. Our assumptions are that students link to each other based on how compatible they are, on the one hand, and based on the learning opportunities, on the other. We assume that the two matrixes, that of compatibilities and that of learning opportunities, are different and employed differently. We split students into experts and knowledge consumers, based on the knowledge flows direction, and evaluate the way in which they form patterns. We take into consideration tacit knowledge flows. Tacit knowledge is implicit knowledge, which is difficult to transfer to others in a formal way, other than by practicing together. We assume, adapting the Johari window used in communication studies that others may sense that one person possesses knowledge s/he is unaware of. Thus, by studying the distribution of the relations in the social networks, we diagnose which are the sources of knowledge and make them better aware of their tacit knowledge, which they cannot verbalize, but they can intuitively transfer. The conclusions of the research underline the differences between compatibilities and learning relations, in a research team, suggesting possible ways of converting compatibility relationships into learning relationships. Copyright Springer Science+Business Media New York 2015