A data envelopment analysis approach for ranking journals. (July 2017) - Rosenthal, Edward C.; Weiss, Howard J.
Abstract: We create a data envelopment analysis (DEA) model to rank business journals, using data from the Thomson Reuters Journal Citation Reports ® (JCR). As opposed to previous models that ranked journals in only one field and mostly relied on survey data, this model is used to rank 358 business journals from five different JCR categories according to such citation-based factors as the number of articles, the number of citations, impact factor, five-year impact factor, immediacy index, eigenfactor score, and article influence score. We compute relative efficiencies of the journals and thereby create plausible journal rankings that largely, but not completely, corroborate three widely used business publication journal ranking lists. In addition, we show how the different characteristics of the JCR data impact the DEA ranking model. Finally, we identify journals that are not on the business publication lists but consistently perform very well relative to those benchmark journals, and should possibly be included in the business publication ranking lists. We also identify journals whose inclusion in widely used business publication rankings cannot be justified by our methodology. Highlights: We create a Data Envelopment Analysis (DEA) model to rank business journals. The journal categories span all areas of academic business research. We use objective data taken from the Thomson Reuters Journal Citation Reports (JCR). Our rankings largely, but not completely, corroborate those in the popular media. We show how the different characteristics of the JCR data impact the DEA rankings.