How do intra- and inter-organisational collaboration affect research performance? Evidence from German universities

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Cecilia Garcia Chavez , Sonia Gruber , Torben Schubert
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引用次数: 0

Abstract

This paper examines how organisational boundaries shape the relationship between collaboration and research performance in universities. Using meso-level co-authorship networks and matched registry data from 83 German universities between 2006 and 2019, this study advances the understanding of how organisational structures condition collaborative knowledge production and its research performance outcomes. By examining the contingency effects of intra- and inter-organisational networks, we offer new insights into the cost-benefit trade-offs of collaboration, highlighting the importance of balancing internal cohesion with external diversity. While intra-organisational networks reinforce strong relational ties that support existing knowledge, they may constrain the formation of novel knowledge combinations. Conversely, inter-organisational networks expand opportunities for new knowledge combinations, but at the cost of weaker ties, which may reduce the depth and stability of knowledge exchange. Our findings highlight the strategic value of integrating intra- and inter-organisational networks to optimise the research impact of universities.
组织内部和组织间的合作如何影响研究绩效?来自德国大学的证据
本文探讨了组织边界如何塑造大学合作与研究绩效之间的关系。利用2006年至2019年间来自83所德国大学的中观合作作者网络和匹配的注册表数据,本研究推进了对组织结构如何影响协作知识生产及其研究绩效结果的理解。通过研究组织内部和组织间网络的偶然性效应,我们为合作的成本效益权衡提供了新的见解,强调了平衡内部凝聚力和外部多样性的重要性。虽然组织内部网络加强了支持现有知识的强大关系联系,但它们可能会限制新知识组合的形成。相反,组织间网络扩大了新知识组合的机会,但以较弱的联系为代价,这可能会降低知识交换的深度和稳定性。我们的研究结果强调了整合组织内部和组织间网络以优化大学研究影响的战略价值。
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来源期刊
Journal of Informetrics
Journal of Informetrics Social Sciences-Library and Information Sciences
CiteScore
6.40
自引率
16.20%
发文量
95
期刊介绍: Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.
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