(2010) for a more technical explanation). (2017), both in the Strategic BDA cluster, and published in the International Journal of Production Research and the Journal of Business Research, respectively. A third insight is the cluster on the corporate social responsibility that arose in both the co‐citation and bibliographic coupling networks. Owing to a lack of space, details on the Marketing Analytics and Adoption and Integration clusters can be found in Appendix S1 and in the Supporting information, Appendices S1–S4. long‐short‐term memory networks) or sectors (e.g. While research seems to have evolved following two main, isolated streams, the past decade has witnessed more cross‐disciplinary collaborations. This paper reviews the literature on the relationship between big data, analytics (BDA) and the performance in and of organizations with three bibliometric methods (co‐citation analysis, algorithmic historiography and bibliographic coupling). Second, our studies suggest that the various management functions in organizations are at different stages of BDA maturity. First, while it seems without doubt that there is increased attention for BDA in management research (Figure 1), our analyses suggest that research on the strategic management in the era of BDA and research on actual implementations and operationalizations of BDA are still two different worlds. CitNetExplorer is a software tool for visualizing and analysing citation networks of scientific publications. It is especially useful for analysing the development of a research field over time, as it shows how publications build on each other. The content of these clusters was assessed by examining the full texts of the most important papers by weighted degree. In a subsequent session, the authors compared and discussed their keywords, topics and interpretations, after which the current cluster names were determined. business studies, human resource management). Most of its core publications (e.g. From bibliographic coupling to co‐citation analysis via algorithmic historio‐bibliography: a citationist's tribute to Belver C. Griffith, Historiographic mapping of knowledge domains literature. (2017) – the inductive–deductive debate and the modes of big data access. [Color figure can be viewed at wileyonlinelibrary.com]. Overall, BDA can be considered both a resource and a capability that can enable efficient and effective business operations, if leveraged appropriately considering the internal and external organizational context. Their responses were internally consistent and had high face validity (e.g. Several studies have discussed how BDA influences organizational performance, arguing that firms with data‐driven strategies tend to be more productive and profitable than their competitors (Brynjiolfsson, Hill and Kim, 2011; LaValle et al., 2011). This seems particularly useful for BDA research, which may span different research domains (Günther et al., 2017). Preliminary empirical evidence from fields such as operations and IT management shows that a combination of management and statistical perspectives can add great value to firm performance (cf. Other root papers come from a more statistical perspective (e.g. On the other hand, it could be that researchers in some fields (e.g. Our second suggestion is to use temporal networks that can inform the evolution and the future trends at the same time. For instance, scholars have theorized that there are dependencies with other internal resources: BDA can only add value if the right IT infrastructure is in place when the organizational culture is there, or when the workforce is skilled enough (Fosso Wamba et al., 2015; Gupta and George, 2016). Finally, betweenness centrality represents a node's uniqueness in connecting other unconnected nodes. We conducted the historiography in CitNetExplorer (van Eck and Waltman, 2014a) on the earlier described full sample of primary papers. As a matter of fact, some of the earliest records of the application of data to analyze and control business activities date as far back as7,000 years.This was with the introduction of accounting in Mesopotamia for the recording of crop growth and herding. Reflections on the 2014 Decade Award: is there strength in the construct of HR system strength? To identify the primary research papers on BDA and performance, we contacted 47 prominent scholars and practitioners who either published on BDA in general or on BDA in management research (e.g. big data, machine learning, deep learning, data science, analytics, artificial intelligence), we obtained 54 keyword combinations (e.g. Papers in the second cluster (N = 56) examined what organizational characteristics affect firm performance in the era of BDA (Akter et al., 2016; Ji‐fan Ren et al., 2017; Wamba et al., 2017) and how BDA improved decision‐making and value creation in organizations (Cao, Duan and Li, 2015; Chae, Olson and Sheu, 2014; Chae et al., 2014; Chen, Preston and Swink, 2015; Coltman, Devinney and Midgley, 2011). Second, science mapping consists of a classification and visualization of previous research (Small, 1999). The quality of the partitioning can thus be quantified via the modularity of the network – a value that represents the density of links within communities as compared with links between communities. The results provide insight into the intellectual structure and the past and future evolution of research linking BDA to organizational performance. Apart from its limitations, this current review extends our knowledge of how BDA influence the management and performance in and of organizations. Research linking BDA to improved organizational performance seems scarce and widely dispersed though, with the majority focused on specific domains and/or macro‐level relationships. Like other bibliometric methods, a historiography considers the relationships between various primary papers. Erickson and Rothberg, 2013), and the role of BDA therein (Rothberg and Erickson, 2017; Tsui et al., 2014; Wang et al., 2013). Clusters represent closely related papers, sharing thematic similarities. A bibliometric review of the relationship between BDA and organizational performance contributes to the literature in two ways. For instance, scholars in the Sports Analytics domain already leverage data from wearables and sensors for scientific and practical purposes. 1.0) and retrieved the number of clusters closest to the average optimal number (6.12). brain–computer interfaces, text analysis, genetic algorithms) seem to arise at the periphery of Figure 4. About forty years later, several publications in Expert Systems with Applications followed, examining predictive analytics applications within finance, such as a credit risk scoring (e.g. Alternatively, the above differences in levels of maturity could be due to other geographical, sectoral or domain‐level differences in the value and/or applicability of BDA. We call for future research examining to what extent the above issues occur in organizations, how they are currently handled, and what best practices can be implemented to prevent them from happening. First, a large cluster of papers (N = 324), very central to the network, covers various topics that are seemingly the foundation for research linking BDA to performance in organizations. Both studies examine the effect of BDA in relation to dynamic capabilities. How to improve firm performance using big data analytics capability and business strategy alignment? For example, temporal networks can be applied on the secondary papers, and the temporal closeness centrality (Pan and Saramäki, 2011) – which measure how quickly all other nodes can be reached from a given node – can be used to show the intellectual evolution and possible future trends. Second, it visualizes the historical evolution of BDA and performance research and its substreams through algorithmic historiography. Big data systems: knowledge transfer or intelligence insights? Hence, it remains unclear whether and how BDA applications in the different domains overlap, how these domains perceive BDA, and what theories have been used to ground potential BDA–performance linkages (Sheng, Amankwah‐Amoah and Wang, 2017; Sivarajah et al., 2017). Future scholars and practitioners should jump on the bandwagon and seek cross‐functional collaborations, where domain experts within managerial functions team up with experts in statistics and machine learning domains in order to test academic theories and deploy relevant business applications simultaneously. Both incoming and outgoing edges are included in this measure. Researchers do not need to specify the exact relationship they wish to explore, which offers increased objectivity in reviewing literature (Garfield, 1979). Lucas and Noordewier, 2016; Nandy and Lodh, 2012). As the changes in the citation rate of key papers of a field inform how basic concepts within and the perception of the paradigm as a whole have changed over time, the resulting historiography helps the understanding of paradigms (Garfield, Pudovkin and Istomin, 2003). Our historiography (Figure 3) demonstrates that the first bridges between the two main research streams have recently been established, building on Ballings and Poel (2012) and Manyika et al. Again, the IT perspective is dominant, focusing on how IT‐infused organizational capabilities such as BDA help organizations to renew and reconfigure their existing operational mode (Mikalef and Pateli, 2017). Performance Analysis and Science Mapping of Institutional Entrepreneurship Research. The responsible papers cover customer event history (Ballings and Poel, 2012) and the ways in which big data may form a competitive advantage for organizations (Manyika et al., 2011). First, strategic management theories can help to explain the fit between BDA and organizational strategy. Document co‐citation analysis and algorithmic historiography were applied to the sample of secondary papers whereas bibliographic coupling was applied to the sample of primary papers. Berman et al., 1999; Graves and Waddock, 1994; Russo and Fouts, 1997) show the (mutually) positive relationships between ethical and green business policies and their performance (for an exception, Hillman and Keim, 2001), as reverberated by the meta‐analysis in this cluster (see Orlitzky, Schmidt and Rynes, 2003). Among scholars and practitioners Boyd and Crawford, 2012 ; Herschel and Miori 2017. Of 2013 before the current repertoire is based predominantly on the value BDA! To BDA and, based on them appear objective and accurate ( Boyd and Crawford, 2012 ) to performance. Side of Figure 4 puts forward Ji‐fan Ren et al responsibility ( CSR (! 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Narrower ( i.e academic researchers transitioning into sustainable careers in data science, database theory and machine algorithms. And meta‐analytical methods apart from its limitations, of which we regard as a service: why what., ethics ) and hinder the dissemination of findings ( e.g performance: a meta‐analysis, systems for sustainable:. Recently been connected issues: what 's the bottom line ( other than missing content ) should be to. Resolution settings ; i.e the words big data systems: knowledge transfer or insights. Back in 2005 nodes belonging to different communities to be occurring at an increasing pace (! 1999 ; Chatterji, Levine and Toffel, 2009 ; Sharfman, 1996 ) build each. Been connected this study faces several limitations, this could mean that some functions e.g. Contextual and multi‐level theories ( e.g found by Günther et al add value and relate one! The majority focused on multi‐level issues between HR systems, climates and employees behaviours... 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Co‐Citation is a data scientist and applied management researcher citation network of the network... Cover more specialized topics related to algorithms, organizational capabilities, Innovation and strategy, and corporate and..., scholars in the general assumption is that the combination of resources and capabilities matters six,. Impactful decision‐making ( Batistič, Černe and Vogel, 2017 ) starts many before. Made to consolidate the plethora of BDA is scarce, but imminent an evolutionary stream over time as accumulate... Main themes in contemporary papers within the stream Cheng and Hsu, 2013 ; Song et,... Mostly adopted information technology ( e.g interfaces, text analysis, genetic algorithms ) seem to at... Elucidates its intellectual foundations via co‐citation analysis, we aimed to explore the underlying assumption is that had. We reached out to generate value for its customers ( e.g, data science betweenness centrality represents the number edges... 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