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Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms

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  • Brewis, Claire
  • Dibb, Sally
  • Meadows, Maureen

Abstract

Big data can improve the profitability and competitiveness of organisations by extending market knowledge and strategic marketing insight. However, there is a disconnect between the opportunities presented and the readiness of incumbent firms to engage with big data, with consequences for their ability to benefit from it. With many organisations overwhelmed by how to manage and use big data, the paper identifies the dynamic capabilities required to exploit big data for strategic marketing and to improve market responsiveness. Data gathered from in-depth, semi-structured interviews with senior managers from four case study organisations, reveals the five interconnected dynamic capabilities required to leverage value from big data. These capabilities are shown to be part of a sequential ‘sensing-reconfiguring-seizing’ process, in which the reconfiguring capabilities play a vital role. The findings contribute to dynamic capabilities theory by identifying and mapping the configuration of big data capabilities required to support strategic marketing initiatives. A new Big Data Capabilities Model is developed, which can be used by organisations to guide how they can leverage value from big data.

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  • Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:tefoso:v:190:y:2023:i:c:s0040162523000872
    DOI: 10.1016/j.techfore.2023.122402
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