Social Network Analysis of Innovation Mentor Community of Practice

Abstract

Innovation is directly related to the development of economies, and with the awareness of its criticality, various nation-wide support programs and innovation communities have emerged in recent years. These communities are established along their own specific structures and dynamics that can be examined by their level of connectedness and its underlying members’ attributes. In this research, a government-sponsored innovation mentors’ community of practice (CoP) has been examined. Thus, the members are advised to bring their knowledge to adopt the framework to specific cases and share their experiences with their peers. A CoP stands on the basic premise that the practice (knowhow) is shared among members and stimulates connectedness along their competencies. In this context, the first question is: how to measure the connectedness of the community and whether the CoP under investigation achieves the desired level of connectedness? The second is: what specific mentors’ attributes (competencies) characterize the preferred choices of connectedness? More particularly, how knowledge-sharing preferences are associated by the mentors’ attributes of this CoP? We employed Social Network Analysis techniques and Jaccard Similarity to answer them. The findings reveal that the CoP of innovation mentors is highly connected for a giant component, but low at the network level. Degree, title and institution as the members’ attributes may not play a significant role in the connectedness of this community. Even though mentors meet on a denominator in basic competencies in their cooperation, the findings show that they cooperate interdisciplinary. We argue that the dissimilar competencies of the connected mentors can be considered as a signature of the very idea of connectedness. Further research is needed to validate this claim with richer data, preferably with a temporal aspect.