Mingers, John, Watson, Kate, Scaparra, Maria Paola (2012) Estimating Business And Management Journal Quality From The 2008 Research Assessment Exercise In The UK. Information Processing and Management, 48 (6). pp. 1078-1093. ISSN 0306-4573. (doi:10.1016/j.ipm.2012.01.008) (KAR id:28981)
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Official URL: http://dx.doi.org/10.1016/j.ipm.2012.01.008 |
Abstract
The 2008 Research Assessment Exercise in the UK involved the peer review of over 12,500 research outputs in Business and Management, of which 92% were journal articles. Each output was graded on a 4-point scale from "world leading" to "national" with a fifth point being unclassified. These grades were accumulated for each department to provide an overall quality profile in terms of the proportions of its outputs in each category. The assessments of individual papers were not made public but the papers submitted by each department were. This data provides a major opportunity for addressing issues of concern about the evaluation of research and the effects of journal rankings, as well as the possibility of reconstructing the judgements made by the Panel about journal quality. Given the submission details and the resulting grade profile for each department, we have used linear programming to produce the best estimate of the grades awarded to papers from each journal that had more than three entries. This provides both a grade profile for each journal and a single quality estimate. The results are shown to have good validity in comparison with other journal rankings. Apart from providing a ranking of 700 journals based on the RAE results, the paper is also able to shed light on issues such as the accuracy and coverage of the ABS ranking: the degree of selectivity of submissions; the dispersion of grades for a journal; and differences between different subject areas.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.ipm.2012.01.008 |
Uncontrolled keywords: | Journal rankings Linear programming (LP) Research Assessment Exercise (RAE) Research evaluation |
Subjects: |
H Social Sciences H Social Sciences > H Social Sciences (General) |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | John Mingers |
Date Deposited: | 02 Mar 2012 15:17 UTC |
Last Modified: | 05 Nov 2024 10:10 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/28981 (The current URI for this page, for reference purposes) |
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