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Stakeholder theory and management: Understanding longitudinal collaboration networks
Julian Fares1, Kon Shing Kenneth Chung2, Alireza Abbasi3
1Department of Management Studies, Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon.
Plos One
|October 14, 2021
Summary
Research collaboration in stakeholder theory and management (STM) shows increasing density over time. Network centrality positively impacts author performance, guiding future research investments.
Area of Science:
- Bibliometrics and Scientometrics
- Social Network Analysis
- Stakeholder Theory and Management (STM)
Background:
- Understanding the evolution of research collaboration networks is crucial for scientific progress.
- The impact of co-authorship on research performance (productivity, citations) requires longitudinal analysis.
- Stakeholder Theory and Management (STM) as a discipline lacks comprehensive network evolution studies.
Purpose of the Study:
- To explore the evolution of research collaboration networks in STM from 1989-2020.
- To identify the longitudinal effect of co-authorship networks on research performance.
- To analyze network structures at author, institution, and country levels across different time periods.
Main Methods:
- Harvested 6,127 research articles from Web of Science Database (1989-2020).
- Transformed bibliometric data using Bibexcel.
- Applied social network analysis to map and compare collaboration networks across three sub-periods (t1: 1989-1999, t2: 2000-2010, t3: 2011-2020).
Main Results:
- Author collaboration networks remained fragmented but increased in clique size over time.
- Institutional networks showed less fragmentation and increased density.
- International collaboration evolved from fragmented to a dense, less fragmented network by t3.
- Positive association between author performance and centrality/structural holes in t3, contrasting with t1's ego-density/constraint/tie strength.
Conclusions:
- Research collaboration networks in STM are evolving towards greater density and interconnectedness.
- Network centrality and structural holes are key indicators of research performance in later periods.
- Findings inform policymakers and researchers on optimizing collaboration strategies and resource allocation.
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