How Team Interlock Ecosystems Shape the Assembly of Scientific Teams

A Hypergraph Approach

Alina Ionica Lungeanu*, Dorothy R. Carter, Leslie Ann DeChurch, Noshir Contractor

*Corresponding author for this work

Research output: Contribution to journalArticle

3 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)174-198
Number of pages25
JournalCommunication Methods and Measures
Volume12
Issue number2-3
DOIs
StatePublished - Apr 3 2018

Fingerprint

Ecosystems
teamwork
specialization
knowledge
Industry
social network
driver
simulation

ASJC Scopus subject areas

  • Communication

Cite this

@article{0d56dc44f98a49d890c1f1319002398c,
title = "How Team Interlock Ecosystems Shape the Assembly of Scientific Teams: A Hypergraph Approach",
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.",
author = "Lungeanu, {Alina Ionica} and Carter, {Dorothy R.} and DeChurch, {Leslie Ann} and Noshir Contractor",
year = "2018",
month = "4",
day = "3",
doi = "10.1080/19312458.2018.1430756",
language = "English (US)",
volume = "12",
pages = "174--198",
journal = "Communication Methods and Measures",
issn = "1931-2458",
publisher = "Routledge",
number = "2-3",

}

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.

UR - http://www.scopus.com/inward/record.url?scp=85042207896&partnerID=8YFLogxK

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 -