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Ranking journals in business and management: a statistical analysis of the Harzing data set

Mingers, John, Harzing, Anne-Wil (2007) Ranking journals in business and management: a statistical analysis of the Harzing data set. European Journal of Information Systems, 16 (4). pp. 303-316. ISSN 0960-085X. (doi:10.1057/palgrave.ejis.3000696) (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:3160)

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://www.palgrave-journals.com/ejis/journal/v16/...

Abstract

Creating rankings of academic journals is an important but contentious issue. It is of especial interest in the U.K. at this time (2007) as we are only one year away from getting the results of the next Research Assessment Exercise (RAE) the importance of which, for U.K. universities, can hardly be overstated. The purpose of this paper is to present a journal ranking for business and management based on a statistical analysis of the Harzing data set which contains 13 rankings. The primary aim of the analysis is two-fold – to investigate relationships between the different rankings, including that between peer rankings and citation behaviour; and to develop a ranking based on four groups that could be useful for the RAE. Looking at the different rankings, the main conclusions are that there is in general a high degree of conformity between them as shown by a principal components analysis. Cluster analysis is used to create four groups of journals relevant to the RAE. The higher groups are found to correspond well with previous studies of top management journals and also gave, unlike them, equal coverage to all the management disciplines. The RAE Business and Management panel have a huge and unenviable task in trying to judge the quality of over 10,000 publications and they will inevitably have to resort to some standard mechanistic procedures to do so. This work will hopefully contribute by producing a ranking based on a statistical analysis of a variety of measures.

Item Type: Article
DOI/Identification number: 10.1057/palgrave.ejis.3000696
Uncontrolled keywords: citation indices, cluster analysis, journal rankings, research assessment exercise (RAE)
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HA Statistics
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: John Mingers
Date Deposited: 14 May 2008 07:15 UTC
Last Modified: 05 Nov 2024 09:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/3160 (The current URI for this page, for reference purposes)

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