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Chapter 2 28 Table 2.2: The most frequent outlets for publications in the big data and performance debate Primary articles Secondary (cited) articles Journal N Journal N 1 Expert Systems with Applications 61 MIS Quarterly 196 2 Decision Support Systems 27 Harvard Business Review 172 3 International Journal of Sports Science & Coaching 18 MIT Sloan Management Review 80 4 European Journal of Operational Research 14 Journal of Management Information Systems 49 5 International Journal of Production Research 8 Academy of Management Journal 44 6 Journal of Knowledge Management 8 California Managmenet Review 39 7 Journal of Business Research 6 Journal of Marketing 38 8 International Journal of Production Economics 6 Academy of Management Review 34 9 Frontiers in Human Neuroscience 6 Journal of the Association for Information Systems 31 10 Journal of Manageement Information Systems 6 Journal of Machine Learning Research 29 The cluster interpretation followed the suggestion of Zupic and Čater (2015). After running the cluster analyses (Study 1 and 3), the two authors independently explored the content of each cluster by reading through the abstracts and full text of the 25 publications with the highest weighted degree and recording any relevant keywords and topics. In a subsequent session, the authors compared and discussed their keywords, topics and interpretations, after which the current cluster names were determined. 2.2.3 Measures Several network statistics were calculated during the analyses. The weighted degree centrality represents the number of edges (i.e., citation relationships) a node (i.e., document) has to other nodes, weighted for the edges’ importance. Both incoming and outgoing edges are included in this measure. In general, the higher the weighted degree, the more important a document is to the network. Closeness centrality represents a node’s distance to all other network nodes, inversed. The higher the closeness, the more central a document’s location in the network. Finally, betweenness centrality represents a node’s uniqueness in connecting other unconnected nodes. The higher the betweenness, the more a document functions as an important pathway connecting other documents (for more information see Nooy, Mrvar, & Batagelj, 2011). 2.3 Study 1: Document Co-citation Co-citation analysis (McCain, 1990) uses the frequency with which two documents are cited together to determine their semantic similarity. The underlying assumption is that secondary papers which are co-cited (i.e., both referred to in the same primary document) share content-wise similarities and are thus semantically related. Co-citation count would thus indicate to what extent papers represent related key concepts, theories, or methods that a certain field or fields have or have drawn from (Small, 1973). Co- citation is a dynamic measure because it changes over time as documents accumulate