We are interested in the degree to which there three groups of journals are connected by publications they reference in the papers published. This will provide evidence about how far the three groups relate to similar underlying concepts, theories, and perspectives. To investigate this, we compute the bibliographic coupling between the articles published in the journals listed above. The degree to which two articles are considered coupled depends on the number of references that appear in the reference lists in both articles (Kessler, 1963); that is, the percentage of references that is shared between two articles. If two articles reference a paper titled "Global Strategy and Finance" this will count toward their degree of coupling. If one article "Global Strategy" cites an article "Finance", and the article "Finance" cites the article "Global Strategy", this will not count toward coupling, because they do not cite the same article. The latter example would be a case of a cross-reference, which is not what we investigate here. We have chosen this methodology because, in cross-referencing, the degree to which articles are related will depend on the standing of the journal they are published in (as authors tend to cite papers published in well-ranked journals), which makes a comparison across fields with different numbers of top-ranked journals difficult. Rather, we compute the average association strength between articles published in different outlets (Van Eck & Waltman, 2007). This coefficient represents the ratio of coupling links between nodes (i.e., the journals) over all coupling links between one node and all other nodes, normalized for the total number of possible links. It takes the maximum value of one for a pair of journals that reference exclusively the same publication outlet, and a minimum of zero for a pair of journals that have no references to a common publication outlet. These numerical operations result in a symmetric matrix representing the coupling strength between pairs of journals. Computations for this illustration are performed using the normalizeSimilarity() command in the bibliometrix package (Aria & Cuccurullo, 2017) in an R 3.4.2 distribution. We plot this matrix below in Figure 1. Darker fields represent stronger coupling, brighter fields less coupling. The diagonal is set to zero. Figure 1 shows the resulting average coupling between articles in management, finance, and IB/GS journals. The illustration shows that the three groups of journals indeed form rather distinct ecosystems of publications. There is very strong coupling among finance journals, while there is very PUCK AND FILATOTCHEV