Abstract
Today’s most pressing scientific problems necessitate scientific teamwork; the increasing complexity and specialization of knowledge render “lone geniuses” ill-equipped to make high-impact scientific breakthroughs. Social network research has begun to explore the factors that promote the assembly of scientific teams. However, this work has been limited by network approaches centered conceptually and analytically on “nodes as people,” or “nodes as teams.” In this article, we develop a “team-interlock ecosystem” conceptualization of collaborative environments within which new scientific teams, or other creative team-based enterprises, assemble. Team interlock ecosystems comprise teams linked to one another through overlapping memberships and/or overlapping knowledge domains. They depict teams, people, and knowledge sets as nodes, and thus, present both conceptual advantages as well as methodological challenges. Conceptually, team interlock ecosystems invite novel questions about how the structural characteristics of embedding ecosystems serve as the primordial soup from which new teams assemble. Methodologically, however, studying ecosystems requires the use of more advanced analytics that correspond to the inherently multilevel phenomenon of scientists nested within multiple teams. To address these methodological challenges, we advance the use of hypergraph methodologies combined with bibliometric data and simulation-based approaches to test hypotheses related to the ecosystem drivers of team assembly.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 174-198 |
| Number of pages | 25 |
| Journal | Communication Methods and Measures |
| Volume | 12 |
| Issue number | 2-3 |
| DOIs | |
| State | Published - Apr 3 2018 |
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ASJC Scopus subject areas
- Communication
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How Team Interlock Ecosystems Shape the Assembly of Scientific Teams : A Hypergraph Approach. / Lungeanu, Alina Ionica; Carter, Dorothy R.; DeChurch, Leslie Ann; Contractor, Noshir.
In: Communication Methods and Measures, Vol. 12, No. 2-3, 03.04.2018, p. 174-198.Research output: Contribution to journal › Article
TY - JOUR
T1 - How Team Interlock Ecosystems Shape the Assembly of Scientific Teams
T2 - A Hypergraph Approach
AU - Lungeanu, Alina Ionica
AU - Carter, Dorothy R.
AU - DeChurch, Leslie Ann
AU - Contractor, Noshir
PY - 2018/4/3
Y1 - 2018/4/3
N2 - Today’s most pressing scientific problems necessitate scientific teamwork; the increasing complexity and specialization of knowledge render “lone geniuses” ill-equipped to make high-impact scientific breakthroughs. Social network research has begun to explore the factors that promote the assembly of scientific teams. However, this work has been limited by network approaches centered conceptually and analytically on “nodes as people,” or “nodes as teams.” In this article, we develop a “team-interlock ecosystem” conceptualization of collaborative environments within which new scientific teams, or other creative team-based enterprises, assemble. Team interlock ecosystems comprise teams linked to one another through overlapping memberships and/or overlapping knowledge domains. They depict teams, people, and knowledge sets as nodes, and thus, present both conceptual advantages as well as methodological challenges. Conceptually, team interlock ecosystems invite novel questions about how the structural characteristics of embedding ecosystems serve as the primordial soup from which new teams assemble. Methodologically, however, studying ecosystems requires the use of more advanced analytics that correspond to the inherently multilevel phenomenon of scientists nested within multiple teams. To address these methodological challenges, we advance the use of hypergraph methodologies combined with bibliometric data and simulation-based approaches to test hypotheses related to the ecosystem drivers of team assembly.
AB - Today’s most pressing scientific problems necessitate scientific teamwork; the increasing complexity and specialization of knowledge render “lone geniuses” ill-equipped to make high-impact scientific breakthroughs. Social network research has begun to explore the factors that promote the assembly of scientific teams. However, this work has been limited by network approaches centered conceptually and analytically on “nodes as people,” or “nodes as teams.” In this article, we develop a “team-interlock ecosystem” conceptualization of collaborative environments within which new scientific teams, or other creative team-based enterprises, assemble. Team interlock ecosystems comprise teams linked to one another through overlapping memberships and/or overlapping knowledge domains. They depict teams, people, and knowledge sets as nodes, and thus, present both conceptual advantages as well as methodological challenges. Conceptually, team interlock ecosystems invite novel questions about how the structural characteristics of embedding ecosystems serve as the primordial soup from which new teams assemble. Methodologically, however, studying ecosystems requires the use of more advanced analytics that correspond to the inherently multilevel phenomenon of scientists nested within multiple teams. To address these methodological challenges, we advance the use of hypergraph methodologies combined with bibliometric data and simulation-based approaches to test hypotheses related to the ecosystem drivers of team assembly.
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UR - http://www.scopus.com/inward/citedby.url?scp=85042207896&partnerID=8YFLogxK
U2 - 10.1080/19312458.2018.1430756
DO - 10.1080/19312458.2018.1430756
M3 - Article
VL - 12
SP - 174
EP - 198
JO - Communication Methods and Measures
JF - Communication Methods and Measures
SN - 1931-2458
IS - 2-3
ER -