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Structural efficiency to manipulate public research institution networks

机译:操纵公共研究机构网络的结构效率

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摘要

With the rising use of network analysis in the public sector, researchers have recently begun paying more attention to the management of entities from a network perspective. However, guiding elements in a network is difficult because of their complex and dynamic states. In a bid to address the issues involved in achieving network-wide outcomes, our work here sheds new light on quantifying structural efficiency to control inter-organizational networks maintained by public research institutions. In doing so, we draw attention to the set of subordinates suitable as change initiators to influence the entire research profiles of subordinates from three major public research institutions: the Government-funded Research Institutes (GRIs) in Korea, the Max-Planck-Gesellschaft (MPG) in Germany, and the National Laboratories (NLs) in the United States. Building networks on research similarities in portfolios, we investigate these networks with respect to their structural efficiency and topological properties. According to our estimation, only less than 30% of nodes are sufficient to initiate a cascade of changes throughout the network across institutions. The subunits that drive the network exhibit an inclination neither toward retaining a large number of connections nor toward having a long academic history. Our findings suggest that this structural efficiency indicator helps assess structural development or improvement plans for networks inside a multiunit public research institution.
机译:随着公共部门对网络分析的使用越来越多,研究人员最近开始从网络角度更加关注实体的管理。但是,由于网络中的引导元素复杂且动态,因此很难。为了解决实现全网成果所涉及的问题,我们在这里的工作为量化结构效率以控制公共研究机构维护的组织间网络提供了新的思路。在此过程中,我们提请注意适合用作变革发起人的下属集合,以影响三个主要公共研究机构的下属的整个研究概况:韩国政府资助的研究机构(GRI),Max-Planck-Gesellschaft( MPG)和美国国家实验室(NL)。建立基于投资组合研究相似性的网络,我们就其结构效率和拓扑特性来研究这些网络。根据我们的估计,只有不到30%的节点足以启动跨机构的整个网络的级联更改。驱动网络的子单元既不倾向于保留大量连接,也不倾向于具有悠久的学术历史。我们的发现表明,这种结构效率指标有助于评估多部门公共研究机构内部网络的结构发展或改进计划。

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