Vana, Laura and Hochreiter, Ronald and Hornik, Kurt ORCID: https://orcid.org/0000-0003-4198-9911
(2016)
Computing a journal meta-ranking using paired comparisons and adaptive lasso estimators.
Scientometrics, 106 (1).
229-251.
ISSN 1588-2861
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Abstract
In a "publish-or-perish culture", the ranking of scientific journals plays a central role in assessing the performance in the current research environment. With a wide range of existing methods for deriving journal rankings, meta-rankings have gained popularity as a means of aggregating different information sources. In this paper, we propose a method to create a meta-ranking using heterogeneous journal rankings. Employing a parametric model for paired comparison data we estimate quality scores for 58 journals in the OR/MS/POM community, which together with a shrinkage procedure allows for the identification of clusters of journals with similar quality. The use of paired comparisons provides a flexible framework for deriving an aggregated score while eliminating the problem of missing data.
Item Type: | Article |
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Additional Information: | To see the final version of this paper please visit the publisher's website. Access to the published version requires a subscription. |
Keywords: | Adaptive lasso estimators, Journal lists, Meta-ranking, Operations research |
Divisions: | Departments > Finance, Accounting and Statistics > Statistics and Mathematics Forschungsinstitute > Rechenintensive Methoden |
Version of the Document: | Accepted for Publication |
Depositing User: | Gertraud Novotny |
Date Deposited: | 24 Jan 2017 14:46 |
Last Modified: | 24 Oct 2019 13:41 |
Related URLs: | |
FIDES Link: | https://bach.wu.ac.at/d/research/results/73271/ |
URI: | https://epub.wu.ac.at/id/eprint/5392 |
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