{"title":"Factors affecting web links between European higher education institutions","authors":"Marco Seeber , Benedetto Lepori , Alessandro Lomi , Isidro Aguillo , Vitaliano Barberio","doi":"10.1016/j.joi.2012.03.001","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"6 3","pages":"Pages 435-447"},"PeriodicalIF":3.4000,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.joi.2012.03.001","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Informetrics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751157712000235","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
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.
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.