10,495 research outputs found
Towards a new crown indicator: Some theoretical considerations
The crown indicator is a well-known bibliometric indicator of research
performance developed by our institute. The indicator aims to normalize
citation counts for differences among fields. We critically examine the
theoretical basis of the normalization mechanism applied in the crown
indicator. We also make a comparison with an alternative normalization
mechanism. The alternative mechanism turns out to have more satisfactory
properties than the mechanism applied in the crown indicator. In particular,
the alternative mechanism has a so-called consistency property. The mechanism
applied in the crown indicator lacks this important property. As a consequence
of our findings, we are currently moving towards a new crown indicator, which
relies on the alternative normalization mechanism
Evaluating a Departmentâs Research: Testing the Leiden Methodology in Business and Management
The Leiden methodology (LM), also sometimes called the âcrown indicatorâ, is a quantitative method for evaluating the research quality of a research group or academic department based on the citations received by the group in comparison to averages for the field. There have been a number of applications but these have mainly been in the hard sciences where the data on citations, provided by the ISI Web of Science (WoS), is more reliable. In the social sciences, including business and management, many journals and books are not included within WoS and so the LM has not been tested here. In this research study the LM has been applied on a dataset of over 3000 research publications from three UK business schools. The results show that the LM does indeed discriminate between the schools, and has a degree of concordance with other forms of evaluation, but that there are significant limitations and problems within this discipline
Rivals for the crown: Reply to Opthof and Leydesdorff
We reply to the criticism of Opthof and Leydesdorff [arXiv:1002.2769] on the
way in which our institute applies journal and field normalizations to citation
counts. We point out why we believe most of the criticism is unjustified, but
we also indicate where we think Opthof and Leydesdorff raise a valid point
An Integrated Impact Indicator (I3): A New Definition of "Impact" with Policy Relevance
Allocation of research funding, as well as promotion and tenure decisions,
are increasingly made using indicators and impact factors drawn from citations
to published work. A debate among scientometricians about proper normalization
of citation counts has resolved with the creation of an Integrated Impact
Indicator (I3) that solves a number of problems found among previously used
indicators. The I3 applies non-parametric statistics using percentiles,
allowing highly-cited papers to be weighted more than less-cited ones. It
further allows unbundling of venues (i.e., journals or databases) at the
article level. Measures at the article level can be re-aggregated in terms of
units of evaluation. At the venue level, the I3 creates a properly weighted
alternative to the journal impact factor. I3 has the added advantage of
enabling and quantifying classifications such as the six percentile rank
classes used by the National Science Board's Science & Engineering Indicators.Comment: Research Evaluation (in press
Normalization at the field level: fractional counting of citations
Van Raan et al. (2010; arXiv:1003.2113) have proposed a new indicator (MNCS)
for field normalization. Since field normalization is also used in the Leiden
Rankings of universities, we elaborate our critique of journal normalization in
Opthof & Leydesdorff (2010; arXiv:1002.2769) in this rejoinder concerning field
normalization. Fractional citation counting thoroughly solves the issue of
normalization for differences in citation behavior among fields. This indicator
can also be used to obtain a normalized impact factor
A Rejoinder on Energy versus Impact Indicators
Citation distributions are so skewed that using the mean or any other central
tendency measure is ill-advised. Unlike G. Prathap's scalar measures (Energy,
Exergy, and Entropy or EEE), the Integrated Impact Indicator (I3) is based on
non-parametric statistics using the (100) percentiles of the distribution.
Observed values can be tested against expected ones; impact can be qualified at
the article level and then aggregated.Comment: Scientometrics, in pres
A Review of Theory and Practice in Scientometrics
Scientometrics is the study of the quantitative aspects of the process of science as a communication system. It is centrally, but not only, concerned with the analysis of citations in the academic literature. In recent years it has come to play a major role in the measurement and evaluation of research performance. In this review we consider: the historical development of scientometrics, sources of citation data, citation metrics and the âlaws" of scientometrics, normalisation, journal impact factors and other journal metrics, visualising and mapping science, evaluation and policy, and future developments
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