对国际合作持开放态度,在加强知识创造方面发挥纽带作用

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Jing Tu
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引用次数: 0

摘要

本研究旨在了解开放的国际合作是否以及在何种条件下促进知识创造。在以自我为中心的网络中,研究了一个机构的开放性、国内联系和国外联系的配置如何影响其知识创造。利用固定效应面板数据模型,我们发现开放程度与知识创造之间存在正相关关系,国内纽带强度对知识创造起到促进作用,国外纽带强度对知识创造起到抑制作用,且国内外纽带强度对知识创造都存在倒u型影响。研究结果通过提出同时保持强大的国内联系和广泛的相对薄弱的国外联系是利用国际合作来整合国内外知识的有效方法,从而为国际合作和知识基础观点文献做出了贡献。它还丰富了强联系理论,表明强大的国内联系的强度可以通过开放来加强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Openness to international collaboration and tie strength in enhancing knowledge creation

This study aims to understand whether and under what condition openness to international collaboration enhances knowledge creation. How the configuration of openness, domestic ties, and foreign ties of an institution affects its knowledge creation is examined in egocentric networks. Using fixed-effects panel data models, we find that a positive association exists between openness and knowledge creation, which is catalyzed by domestic tie strength and diminished by foreign tie strength, and both domestic and foreign tie strength have an inverted U-shaped effect on knowledge creation. The findings contribute to international collaboration and knowledge-based view literature by proposing that maintaining strong domestic ties and a wide range of relatively weak foreign ties simultaneously is an efficient way to leverage international collaboration to integrate domestic and foreign knowledge. It also enriches the strong tie theory by suggesting the strength of strong domestic ties could be reinforced by openness.

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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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