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Stakeholder theory and management: Understanding longitudinal collaboration networks
This paper explores the evolution of research collaboration networks in the ‘stakeholder theory and management’ (STM) discipline and identifies the longitudinal effect of co-authorship networks on research performance, i.e., research productivity and citation counts. Research articles totaling 6,127...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8516199/ https://www.ncbi.nlm.nih.gov/pubmed/34648505 http://dx.doi.org/10.1371/journal.pone.0255658 |
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author | Fares, Julian Chung, Kon Shing Kenneth Abbasi, Alireza |
author_facet | Fares, Julian Chung, Kon Shing Kenneth Abbasi, Alireza |
author_sort | Fares, Julian |
collection | PubMed |
description | This paper explores the evolution of research collaboration networks in the ‘stakeholder theory and management’ (STM) discipline and identifies the longitudinal effect of co-authorship networks on research performance, i.e., research productivity and citation counts. Research articles totaling 6,127 records from 1989 to 2020 were harvested from the Web of Science Database and transformed into bibliometric data using Bibexcel, followed by applying social network analysis to compare and analyze scientific collaboration networks at the author, institution and country levels. This work maps the structure of these networks across three consecutive sub-periods (t(1): 1989–1999; t(2): 2000–2010; t(3): 2011–2020) and explores the association between authors’ social network properties and their research performance. The results show that authors collaboration network was fragmented all through the periods, however, with an increase in the number and size of cliques. Similar results were observed in the institutional collaboration network but with less fragmentation between institutions reflected by the increase in network density as time passed. The international collaboration had evolved from an uncondensed, fragmented and highly centralized network, to a highly dense and less fragmented network in t(3). Moreover, a positive association was reported between authors’ research performance and centrality and structural hole measures in t(3) as opposed to ego-density, constraint and tie strength in t(1). The findings can be used by policy makers to improve collaboration and develop research programs that can enhance several scientific fields. Central authors identified in the networks are better positioned to receive government funding, maximize research outputs and improve research community reputation. Viewed from a network’s perspective, scientists can understand how collaborative relationships influence research performance and consider where to invest their decision and choices. |
format | Online Article Text |
id | pubmed-8516199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85161992021-10-15 Stakeholder theory and management: Understanding longitudinal collaboration networks Fares, Julian Chung, Kon Shing Kenneth Abbasi, Alireza PLoS One Research Article This paper explores the evolution of research collaboration networks in the ‘stakeholder theory and management’ (STM) discipline and identifies the longitudinal effect of co-authorship networks on research performance, i.e., research productivity and citation counts. Research articles totaling 6,127 records from 1989 to 2020 were harvested from the Web of Science Database and transformed into bibliometric data using Bibexcel, followed by applying social network analysis to compare and analyze scientific collaboration networks at the author, institution and country levels. This work maps the structure of these networks across three consecutive sub-periods (t(1): 1989–1999; t(2): 2000–2010; t(3): 2011–2020) and explores the association between authors’ social network properties and their research performance. The results show that authors collaboration network was fragmented all through the periods, however, with an increase in the number and size of cliques. Similar results were observed in the institutional collaboration network but with less fragmentation between institutions reflected by the increase in network density as time passed. The international collaboration had evolved from an uncondensed, fragmented and highly centralized network, to a highly dense and less fragmented network in t(3). Moreover, a positive association was reported between authors’ research performance and centrality and structural hole measures in t(3) as opposed to ego-density, constraint and tie strength in t(1). The findings can be used by policy makers to improve collaboration and develop research programs that can enhance several scientific fields. Central authors identified in the networks are better positioned to receive government funding, maximize research outputs and improve research community reputation. Viewed from a network’s perspective, scientists can understand how collaborative relationships influence research performance and consider where to invest their decision and choices. Public Library of Science 2021-10-14 /pmc/articles/PMC8516199/ /pubmed/34648505 http://dx.doi.org/10.1371/journal.pone.0255658 Text en © 2021 Fares et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Fares, Julian Chung, Kon Shing Kenneth Abbasi, Alireza Stakeholder theory and management: Understanding longitudinal collaboration networks |
title | Stakeholder theory and management: Understanding longitudinal collaboration networks |
title_full | Stakeholder theory and management: Understanding longitudinal collaboration networks |
title_fullStr | Stakeholder theory and management: Understanding longitudinal collaboration networks |
title_full_unstemmed | Stakeholder theory and management: Understanding longitudinal collaboration networks |
title_short | Stakeholder theory and management: Understanding longitudinal collaboration networks |
title_sort | stakeholder theory and management: understanding longitudinal collaboration networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8516199/ https://www.ncbi.nlm.nih.gov/pubmed/34648505 http://dx.doi.org/10.1371/journal.pone.0255658 |
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