Liu, Wenbin, Xu, Fang, Mingers, John (2015) New Journal Classification Methods Based on the Global h-Index. Information Processing and Management, 51 (2). pp. 50-61. ISSN 0306-4573. (doi:10.1016/j.ipm.2014.10.011) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:53905)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1016/j.ipm.2014.10.011 |
Abstract
In this work we develop new journal classification methods based on the h-index. The introduction of the h-index for research evaluation has attracted much attention in the
bibliometric study and research quality evaluation. The main purpose of using an h-index is to compare the index for different research units (e.g. researchers, journals, etc.) to differentiate their research performance. However the h-index is defined by only comparing citations counts of one’s own publications, it is doubtful that the h index alone should be used for reliable comparisons among different research units, like researchers or journals. In this paper we propose a new global h-index (Gh-index), where the publications in the core are selected in comparison with all the publications of the units to be evaluated. Furthermore, we introduce some variants of the Gh-index to address the issue of discrimination power. We show that together with the original h-index, they can be used to evaluate and classify academic journals with some distinct advantages, in particular that they can produce an automatic classification into a number of categories without arbitrary cut-off points. We then carry out an empirical study for classification of operations research and management science (OR/MS) journals using this index, and compare it with other well-known journal ranking results such as the Association of Business Schools (ABS) Journal Quality Guide and the Committee of Professors in OR (COPIOR) ranking lists.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.ipm.2014.10.011 |
Uncontrolled keywords: | Research evaluation, Journal ranking, h-index, Gh-index, Xj Class, Lj Class |
Subjects: | H Social Sciences > HA Statistics > HA33 Management Science |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | John Mingers |
Date Deposited: | 02 Feb 2016 04:13 UTC |
Last Modified: | 17 Aug 2022 11:00 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/53905 (The current URI for this page, for reference purposes) |
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