Science Policy Research Report: Funding Team Science

Duke University, Durham NC

Investigators

Abstract

Team science is the collaboration of two or more researchers working interdependently towards a common research goal. As funding agencies continue to encourage and promote team science, it is important to evaluate and synthesize what we know about the consequences of team size. Given scare financial resources, an important science policy issue is how to effectively allocate funding to research teams. For example, given an overall project budget of $1.5M, when is it better to fund a team of three researchers at $500,000 each versus a team of 10 researchers at $150,000 each. On the one hand, funding fewer researchers (with more money per researcher) increases their incentives and makes coordination easier, but reduces the amount of team expertise available. On the other hand, funding more researchers, with less money per researcher, decreases their incentives and makes coordination more difficult, but increases the amount of team expertise available. Through an interdisciplinary review of the academic literature on team science, this project advances our knowledge of the benefits and costs of funding teams of varying size. Related topics will be explored as well, including the role of team complexity (e.g., number of disciplines and number of institutions), the life cycle of teams, for example, funding early in the life of the team vs funding later in the life of the team, and the stage of research development, for example, funding early-stage research vs funding late-stage research. To ensure that the evidence identified is robust and reliable, three categories will be used to classify what is known about team size: (1) strong causal inference (e.g., laboratory experiments and field experiments), (2) moderate causal inference (e.g., longitudinal studies with appropriate controls), and (3) weak causal inference (e.g., cross-sectional surveys and observational studies). Based on the evidence, policy recommendations will be made to guide the efficient allocation of resources to team science in order to facilitate complex problem solving, new research discoveries, and technological innovation.