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利益相关者理论与管理:理解纵向协作网络。

Stakeholder theory and management: Understanding longitudinal collaboration networks.

机构信息

Department of Management Studies, Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon.

School of Project Management, Faculty of Engineering, The University of Sydney, Sydney, Australia.

出版信息

PLoS One. 2021 Oct 14;16(10):e0255658. doi: 10.1371/journal.pone.0255658. eCollection 2021.

Abstract

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 (t1: 1989-1999; t2: 2000-2010; t3: 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 t3. Moreover, a positive association was reported between authors' research performance and centrality and structural hole measures in t3 as opposed to ego-density, constraint and tie strength in t1. 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.

摘要

本文探讨了“利益相关者理论与管理”(ST)学科研究合作网络的演变,并确定了合著网络对研究绩效(即研究生产力和引文计数)的纵向影响。本研究从 Web of Science 数据库中提取了 1989 年至 2020 年的 6127 篇研究文章记录,并使用 Bibexcel 将其转换为文献计量数据,然后应用社会网络分析比较和分析作者、机构和国家层面的科学合作网络。这项工作绘制了这些网络在三个连续子时期(t1:1989-1999;t2:2000-2010;t3:2011-2020)的结构,并探讨了作者社会网络属性与其研究绩效之间的关系。结果表明,作者合作网络在整个时期都是碎片化的,但是随着团块数量和大小的增加而增加。机构合作网络也观察到了类似的结果,但随着网络密度的增加,机构之间的碎片化程度降低。国际合作经历了从无凝结、碎片化和高度集中的网络,到 t3 中高度密集和碎片化程度较低的网络的演变。此外,与 t1 中的 ego-density、constraint 和 tie strength 相比,t3 中报告了作者研究绩效与中心度和结构空洞测量之间的正相关关系。研究结果可用于政策制定者改进合作并制定研究计划,以增强几个科学领域。网络中确定的核心作者更有资格获得政府资金,最大限度地提高研究成果并提高研究社区的声誉。从网络的角度来看,科学家可以了解合作关系如何影响研究绩效,并考虑在哪里投入他们的决策和选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc6b/8516199/bf92bcd4c3ce/pone.0255658.g001.jpg

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