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With big data growing rapidly in importance over the past few years', academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. To date, there has been an emphasis on the technical aspects of big data with limited attention on the organizational changes they entail and how they should be leveraged strategically. As with any novel technology, it is important to understand the mechanisms and processes through which big data can add business value to companies and have a clear picture of the different elements and their interdependencies. To this end, the present paper aims to provide a theoretical discussion leading up to a research framework that can help explain the mechanisms through which big data lead to competitive performance gains. The research framework is grounded on past empirical work on IT-business, and builds on the resource-based view (RBV) and dynamic capabilities view (DCV) of the firm. By identifying the main areas of focus for big data and explaining the mechanisms through which they should be leveraged, this paper attempts to add to literature on how big data should be examined as a source of a competitive advantage. Response to Reviewers:The authors would like to thank the two anonymous reviewers for their constructive comments and feedback. In the new version of the manuscript we have incorporated the best we could the suggestion put forward. Specifically, these include:# The manuscript has been professionally copy-edited so the clarity and meaning are more clearly conveyed # The second and third paragraph of the introduction have been revised# We have more clearly defined the significance for IT/management research

With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.

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