Search (5 results, page 1 of 1)

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Date

8. 1.2019 18:22:45

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Date

22. 1.2011 12:51:07

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Abstract

A technique is developed using patent information available online (at the U.S. Patent and Trademark Office) for the generation of Google Maps. The overlays indicate both the quantity and the quality of patents at the city level. This information is relevant for research questions in technology analysis, innovation studies, and evolutionary economics, as well as economic geography. The resulting maps can also be relevant for technological innovation policies and research and development management, because the U.S. market can be considered the leading market for patenting and patent competition. In addition to the maps, the routines provide quantitative data about the patents for statistical analysis. The cities on the map are colored according to the results of significance tests. The overlays are explored for the Netherlands as a "national system of innovations" and further elaborated in two cases of emerging technologies: ribonucleic acid interference (RNAi) and nanotechnology.

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Abstract

Normalization of citation scores using reference sets based on Web of Science subject categories (WCs) has become an established ("best") practice in evaluative bibliometrics. For example, the Times Higher Education World University Rankings are, among other things, based on this operationalization. However, WCs were developed decades ago for the purpose of information retrieval and evolved incrementally with the database; the classification is machine-based and partially manually corrected. Using the WC "information science & library science" and the WCs attributed to journals in the field of "science and technology studies," we show that WCs do not provide sufficient analytical clarity to carry bibliometric normalization in evaluation practices because of "indexer effects." Can the compliance with "best practices" be replaced with an ambition to develop "best possible practices"? New research questions can then be envisaged.

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Abstract

The Leiden Rankings can be used for grouping research universities by considering universities which are not statistically significantly different as homogeneous sets. The groups and intergroup relations can be analyzed and visualized using tools from network analysis. Using the so-called "excellence indicator" PPtop-10%-the proportion of the top-10% most-highly-cited papers assigned to a university-we pursue a classification using (a) overlapping stability intervals, (b) statistical-significance tests, and (c) effect sizes of differences among 902 universities in 54 countries; we focus on the UK, Germany, Brazil, and the USA as national examples. Although the groupings remain largely the same using different statistical significance levels or overlapping stability intervals, these classifications are uncorrelated with those based on effect sizes. Effect sizes for the differences between universities are small (w < .2). The more detailed analysis of universities at the country level suggests that distinctions beyond three or perhaps four groups of universities (high, middle, low) may not be meaningful. Given similar institutional incentives, isomorphism within each eco-system of universities should not be underestimated. Our results suggest that networks based on overlapping stability intervals can provide a first impression of the relevant groupings among universities. However, the clusters are not well-defined divisions between groups of universities.