Dynamics of Research Team Formation in Complex Networks

Most organizations encourage the formation of teams to accomplish complicated tasks, and vice verse, effective teams could bring lots benefits and profits for organizations. Network structure plays an important role in forming teams. In this paper, we specifically study the dynamics of team formation in large research communities in which knowledge of individuals plays an important role on team performance and individual utility. An agent-based model is proposed, in which heterogeneous agents from research communities are described and empirically tested. Each agent has a knowledge endowment and a preference for both income and leisure. Agents provide a variable input ('effort') and their knowledge endowments to production. They could learn from others in their team and those who are not in their team but have private connections in community to adjust their own knowledge endowment. They are allowed to join other teams or work alone when it is welfare maximizing to do so. Various simulation experiments are conducted to examine the impacts of network topology, knowledge diffusion among community network, and team output sharing mechanisms on the dynamics of team formation.