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Chapter 2 34 by their publication year, on the vertical axis, and their closeness, on the horizontal axis (for a more details see Van Eck, Waltman, Dekker, & Van den Berg, 2010). 2.4.1 Results The results of the historiography are presented in Figure 2.2, which clearly demonstrates that BDA-performance research has two main evolutionary streams. The first stream is rooted in statistics and algorithms and their application on financial and customer topics. The seminal paper by Altman (1968) is the root of this stream. After about forty years, several publications in Expert Systems with Applications followed, examining the application of predictive analytics within finance, such a credit risk scoring (e.g., Twala, 2010; Wang, Hao, Ma, & Jiang, 2011). The first stream includes several other root papers with a more statistical orientation (e.g., classification and regression trees, bagging, random forests) (Breiman, 1996, 2001; Breiman et al., 1984). The contemporary papers that arise from this root also cover predictive analytics, but focus on predictions regarding customer behavior (e.g., Ballings & Poel, 2012). Generally speaking, the left side of Figure 2 relates to the development of new statistical methods and applications within the fields of financial and customer analytics. Figure 2.2: Citation network of the evolution of the big data – performance data. Curved lines indicate citation relations. Colours represent the cluster to which primary papers have been assigned. Clusters represent closely related papers, sharing thematic similarities. Second, a more management and strategically oriented stream evolved on the right side of Figure 2.2. Although the first paper has focuses on methodology, structural equation modelling in specific (Fornell & Larcker, 1981), other root papers in this second