Proposal for a multilevel university cybermetric analysis model

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-012-0868-5Universities’ online seats have gradually become complex systems of dynamic information where all their institutions and services are linked and potentially accessible. These online seats now constitute a central node around which universities construct and document their main activities and services. This information can be quantitative measured by cybermetric techniques in order to design university web rankings, taking the university as a global reference unit. However, previous research into web subunits shows that it is possible to carry out systemic web analyses, which open up the possibility of carrying out studies which address university diversity, necessary for both describing the university in greater detail and for establishing comparable ranking units. 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Use of news articles and announcements on official websites of universities. Turkish Online Journal of Educational Technology, 10(2), 287–296

Proximity Dimensions and Scientific Collaboration among Academic Institutions in Europe: The Closer, the Better?

The main objective of this paper is to examine the effect of various proximity dimensions (geographical, cognitive, institutional, organizational, social and economic) on academic scientific collaborations (SC). The data to capture SC consists of a set of co-authored articles published between 2006 and 2010 by universities located in EU-15, indexed by the Science Citation Index (SCI Expanded) of the ISI Web of Science database. We link this data to institution-level information provided by the EUMIDA dataset. Our final sample consists of 240,495 co-authored articles from 690 European universities that featured in both datasets. Additionally, we also retrieved data on regional R&D funding from Eurostat. Based on the gravital equation, we estimate several econometrics models using aggregated data from all disciplines as well as separated data for Chemistry & Chemical Engineering, Life Sciences and Physics & Astronomy. Our results provide evidence on the substantial role of geographical, cognitive, institutional, social and economic distance in shaping scientific collaboration, while the effect of organizational proximity seems to be weaker. Some differences on the relevance of these factors arise at discipline level

Webometrics benefitting from web mining? An investigation of methods and applications of two research fields

Webometrics and web mining are two fields where research is focused on quantitative analyses of the web. This literature review outlines definitions of the fields, and then focuses on their methods and applications. It also discusses the potential of closer contact and collaboration between them. A key difference between the fields is that webometrics has focused on exploratory studies, whereas web mining has been dominated by studies focusing on development of methods and algorithms. Differences in type of data can also be seen, with webometrics more focused on analyses of the structure of the web and web mining more focused on web content and usage, even though both fields have been embracing the possibilities of user generated content. It is concluded that research problems where big data is needed can benefit from collaboration between webometricians, with their tradition of exploratory studies, and web miners, with their tradition of developing methods and algorithms

Influences of the regional and national economic environment on the technology transfer performance of academic institutions in Europe: University Evolution, Entrepreneurial Activity and Regional Competitiveness

The paper looks how the national and regional environment influence the knowledge and technology transfer (KTT) performance of universities and public research institutes. We regress a number of institutional control variables, country dummies and variables for region size and economic structure, per capita income, technology intensity, and R&D intensity on four different tech transfer performance measures (R&D agreements with companies, patent applications, start-ups, licence agreements). Drawing on data from a survey of more than 200 European institutions we find: (1) Country differences are related to differences in the institutional set-up of technology transfer and to the (regional) economic environment which suggests multi-level analyses to properly take these interactions into account. (2) Institutions in a country usually excel for one performance measure which we take as a supporting argument for the development of transfer strategies. (3) Having manufacturing companies and a large share of governmental R&D expenditure in the region matter more than the technology intensity and R&D intensity of the regional economy. The latter result is counterintuitive and indicates that further research is needed in order to understand better where the clients of university technologies actually come from. © Springer International Publishing Switzerland 2016. All rights are reserved