Team formation and team impact: The balance between team freshness and repeat collaboration
Introduction
Teamwork is increasingly pervasive and drives innovations in the contemporary scientific landscape (Liu et al., 2020; Milojević, 2014; Hu, 2021; Yang et al., 2021). Compared to singular knowledge production, collaborative work can yield more discoveries and breakthroughs (Liu et al., 2020; Wuchty et al., 2007). Despite considerable efforts to explore the heterogeneity of team members, we know little about how teams are formed to incorporate fresh members who have no prior collaboration with other team members, and incumbents who have repeat collaborative connections with other team members, and the relationship between team freshness and team impact.
The evolution of team freshness might be accompanied by historical changes in science. Contemporary science has witnessed an exponential growth of scientific publications and a rise in the volume of the scientific labor force (Baskaran, 2017; Fortunato et al., 2018; Price, 1963). Scientific research is characterized by a fundamental shift toward team-based research (Rawlings & McFarland, 2011; Wuchty et al., 2007). Due to the increasing specialization in science (Cole & Harriet, 2017; Evans, 2016; Jones, 2009; Moody, 2004), the need to combine diverse and interdisciplinary knowledge and skills to address complex research problems (Katz & Martin, 1997) and the growing costs of scientific facilities and instruments (Shrum et al., 2007), in almost all branches of science, scientists are increasingly involved in teamwork (Wuchty et al., 2007). In addition, advances in information and communication technologies (Binz-Scharf et al., 2015; He & Berry, 2022) and reductions in travel costs (Katz & Martin, 1997), have made constructing new collaboration links easier. These changes have led to the increasing need to involve new members in teams for diverse and distant knowledge, reduced the costs of constructing fresher teams, and might change the development of team freshness. To understand the temporal changes in team freshness from a historical standpoint, we propose RQ1. How has team freshness evolved in the past decades?
Fresh members enhance team learning and thus spur team creativity by bringing new knowledge and novel perspectives (Perretti & Negro, 2007; Rosenkopf & Almeida, 2003; Skilton & Dooley, 2010). Teams might become less creative over time due to groupthink, homogeneity, and less tendency to disturb the status quo (West & Anderson, 1996). The entry of fresh members could generate conflicts and divergent opinions that can trigger creativity (Badke‐Schaub et al., 2010; Farh et al., 2010; Kane et al., 2005; Santos et al., 2015). In this sense, team freshness could lead to high team performance. A recent study found that team freshness is positively related to a paper's originality and multi-disciplinary impact, which is consistent with this argument (Zeng et al., 2021).
However, too much team freshness could be risky and harmful to team impact due to the high cost of forming new ties (Jackson et al., 1992) and fresh members’ adaption (Chen, 2005), and less trust and familiarity (Van Der Vegt et al., 2010). From the psychological perspective, repeat collaboration entails greater certainty, trust, and reciprocity, and more efficient knowledge transfer, all of which offset the negative consequences of team freshness and thus facilitate team impact (Dahlander & McFarland, 2013; Uzzi, 1997). However, high levels of repeat collaboration could dampen the creation of innovative ideas by reducing collaboration efficiency, homogenizing the pool of knowledge, narrowing the search spaces of teams, and reducing conflicts (Guimera et al., 2005; Porac et al., 2004). Due to the co-existing benefits and disadvantages of team freshness and repeat collaboration, empirical evidence shows that the combination of team freshness and repeat collaboration leads to the best team performance (Guimera et al., 2005; Perretti & Negro, 2007). The mixed arguments about the positive and negative consequences of freshness and repeat collaboration prompt us to explore the “bliss point” between team freshness and repeat collaboration that brings the optimal team impact. Thus, we raise RQ2. What is the relationship between team freshness and team impact?
The relationship between team freshness and team impact might vary with changes in team size. Whether and how team freshness shapes team impact relies on whether the benefits and detriments caused by team freshness outweigh each other, which might be different across team sizes. Fewer and simpler links are embedded in small teams where negative impacts caused by a high level of team freshness could disrupt the whole team (Zhang et al., 2020) and thus worsen team impact, while negative impacts of team freshness might be subtle in large teams and so barely influence team performance. A few empirical studies suggest that stability is more important for small teams’ survival, and that large teams gain benefits from membership dynamics (Palla et al., 2007; Zhang et al., 2020). However, it is still unclear whether and how the relationship between team freshness and team performance is shaped by team size. Thus, we propose RQ3: Is the relationship between team freshness and team impact in small teams different from that in large teams?
To address the three research questions, based on more than 43 million publications between 1950 and 2018 from Microsoft Academic Graph, the research objectives of this paper are threefold: to provide a comprehensive introduction to the evolution of team freshness, to explore how freshness is related to team impact, and to investigate whether and how the relationship between team freshness and team impact depends on team size. This study contributes to the existing literature in multiple dimensions. A better understanding of the balance between freshness and repeat collaboration in teams could improve our knowledge of how the combination of team members’ characteristics relates to team outcomes from the perspective of dynamic team formation. In addition, turnover of members that involves the arrival of new members or the departure of incumbents is increasingly common in scientific teams, which can have profound consequences for team performance by altering the distribution of knowledge and skills within teams, and the relations among team members (Levine et al., 2005). From a practical perspective, the investigation into the balance of freshness and repeat collaboration sheds light on how teams achieve the best performance by maintaining a certain proportion of incumbents and absorbing some fresh members. The remainder of the paper is organized as follows. The related work section reviews the current state of the art, and is followed by section 3, where data and methodology are introduced. Section 4 presents the results. The last section discusses findings and implications for relevant policies.
Section snippets
Related work
In this section, we review three strands of literature concerning the three research questions. We review the literature on team freshness and repeat collaboration, and further provide a discussion on how team size might shape the relationship between team freshness and team impact.
Data
In this study, we use Microsoft Academic Graph (MAG), a heterogeneous graph comprised of 173.67 million scientific papers published between the years 1800 and 2018. MAG provides related information about the publications, such as institutions, venues, the field of study and citation relationships. Due to its comprehensive coverage, MAG has become an important resource for scholarly communication studies in recent years (Cui et al., 2022; Huang et al., 2022; Kanakia et al., 2019; Wang et al.,
RQ1: The temporal evolution of article team freshness in the past half-century
Generally, article team freshness increased over time. Article team freshness has grown over years from 1970 to 2000, remained stable in the 2000s, and increased again after 2010 (see Fig. 2(a)). The average article team freshness reached 0.443 in 2018, which means that nearly 44% of author pairs in an article team have no prior collaboration, on average. To investigate the extreme cases of article team freshness, we calculate the proportion of papers with freshness of value 0 and that of value
Discussions and conclusion
Newcomers and old members bring freshness and experience to teams, respectively. Based on more than 43 million research articles published between 1950 and 2018 from the MAG dataset, we extend a measurement that quantifies freshness in teams, investigate the temporal evolution of freshness, and explore its correlation to papers’ citations and how this association changes with the variations in team size.
On average, we observe that article team freshness is growing over time,3
Supplementary Information
Supplementary Information (SI) is available for this paper: https://zenodo.org/record/7124156#.YzVyA3ZBzGJ.
CRediT authorship contribution statement
Meijun Liu: Conceptualization, Writing – original draft, Data curation, Investigation. Ajay Jaiswal: Data curation, Writing – original draft. Yi Bu: Conceptualization, Supervision, Investigation, Writing – review & editing. Chao Min: Data curation. Sijie Yang: Data curation. Zhibo Liu: Data curation. Daniel Acuña: Conceptualization. Ying Ding: Conceptualization, Supervision, Writing – review & editing.
Acknowledgments
This work is supported by the Youth Program of National Natural Science Foundation in China (No: 72104054 and 72104007), the Youth Project of Humanities and Social Sciences of the Ministry of Education (MOE) of China (No: 21YJC870001), Shanghai Pujiang Program (21PJC026) and “ISTIC-Taylor & Francis Joint Lab for Academic Frontier Observation Open Fund”. The authors deeply appreciate the constructive comments from the reviewers.
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