Factors affecting web links between European higher education institutions

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Informetrics Pub Date : 2012-07-01 DOI:10.1016/j.joi.2012.03.001
Marco Seeber , Benedetto Lepori , Alessandro Lomi , Isidro Aguillo , Vitaliano Barberio
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引用次数: 29

Abstract

We examine the extent to which the presence and number of web links between higher education institutions can be predicted from a set of structural factors like country, subject mix, physical distance, academic reputation, and size. We combine two datasets on a large sample of European higher education institutions (HEIs) containing information on inter-university web links, and organizational characteristics, respectively. Descriptive and inferential analyses provide strong support for our hypotheses: we identify factors predicting the connectivity between HEIs, and the number of web links existing between them. We conclude that, while the presence of a web link cannot be directly related to its underlying motivation and the type of relationship between HEIs, patterns of network ties between HEIs present interesting statistical properties which reveal new insights on the function and structure of the inter organizational networks in which HEIs are embedded.

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影响欧洲高等教育机构之间网络连接的因素
我们研究了高等教育机构之间网络链接的存在和数量在多大程度上可以从一系列结构因素预测,如国家、学科组合、物理距离、学术声誉和规模。我们结合了欧洲高等教育机构(HEI)大样本的两个数据集,分别包含大学间网络链接和组织特征的信息。描述性和推断性分析为我们的假设提供了有力的支持:我们确定了预测高等教育机构之间连通性的因素,以及它们之间存在的网络链接数量。我们得出的结论是,虽然网络链接的存在不能与其潜在动机和高等教育机构之间的关系类型直接相关,但高等教育机构间的网络联系模式呈现出有趣的统计特性,揭示了对高等教育机构所嵌入的组织间网络的功能和结构的新见解。
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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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