One component of research assessment has been, and will continue to be, the explicit (or implicit) ranking of journals. Despite the obvious limitations, citations data are generally used to generate rankings as they provide one of the few quantifiable aspects of a journal's performance. Previous ranking schemes based on multiple performance measures constructed from citations data, such as the `Diamond Core', can be criticised for their use of `arbitrary' weighting schemes to generate their final rankings. This paper addresses this problem by applying ranking techniques, namely, Data Envelopment Analysis and Integer Programming, which systematically allow for multiple performance measures.
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Burton et al. (1995) studied this question.
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