Team power dynamics and team impact: New perspectives on scientific collaboration using career age as a proxy for team power

Abstract

Power dynamics influence every aspect of scientific collaboration. Team power dynamics can be measured by team power level and team power hierarchy. Team power level is conceptualized as the average level of the possession of resources, expertise, or decision‐making authorities of a team. Team power hierarchy represents the vertical differences of the possessions of resources in a team. In Science of Science, few studies have looked at scientific collaboration from the perspective of team power dynamics. This research examines how team power dynamics affect team impact to fill the research gap. In this research, all coauthors of one publication are treated as one team. Team power level and team power hierarchy of one team are measured by the mean and Gini index of career age of coauthors in this team. Team impact is quantified by citations of a paper authored by this team. By analyzing over 7.7 million teams from Science (e.g., Computer Science, Physics), Social Sciences (e.g., Sociology, Library & Information Science), and Arts & Humanities (e.g., Art), we find that flat team structure is associated with higher team impact, especially when teams have high team power level. These findings have been repeated in all five disciplines except Art, and are consistent in various types of teams from Computer Science including teams from industry or academia, teams with different gender groups, teams with geographical contrast, and teams with distinct size.

Using Explainable AI to Understand Team Formation and Team Impact

“…Xu et al (2022a) took the career age as the basis of power, where senior researchers have more rights in decision‐making than junior researchers. By analyzing teams in Computer Science, Physics, Sociology, Library & Information Science, and Arts & Humanities, Xu et al (2022a) calculated the mean value and Gini coefficient of team members' career age to represent the team power level and team power hierarchy. Finally, they found that a flat structure at different team power levels can have higher team citations.…”

“…A researcher's career age, previous citation, H‐index, previous collaborators, productivity, function, and role can also be taken as the proxy of power since they represent prestige, resources, knowledge, and experience (Merton, 1973). Xu et al (2022a) took the career age as the basis of power, where senior researchers have more rights in decision‐making than junior researchers. By analyzing teams in Computer Science, Physics, Sociology, Library & Information Science, and Arts & Humanities, Xu et al (2022a) calculated the mean value and Gini coefficient of team members' career age to represent the team power level and team power hierarchy.…”

“…Specifically, Li et al (2019) measured the characteristics of first authors (e.g., the accumulated citations, H‐index, publication number) in the author features but ignored the contributions of all other authors. Compared with the influence of an individual, the team structure of how members communicate (Woolley et al, 2010), share power (Xu et al, 2022a) and divide the work (Xu et al, 2022b) has a greater influence on team performance. Besides the characteristics of the first authors or corresponding authors, the team composition, such as team size (Wu et al, 2019), gender and race diversity (Hofstra et al, 2020), country diversity (Wagner et al, 2019) of team members are also determinants of team success.…”