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Exploring Configurations of Data-Driven Decision-Making Dimensions for Successful Growth Hacking Implementation: An fsQCA Approach

In: Advanced Technologies in Business, Volume I

Author

Listed:
  • Luca Simone Macca

    (Faculty of Business, American University of Beirut – Mediterraneo)

  • Gabriele Santoro

    (University of Turin
    University of Nicosia, Gnosis: Mediterranean Institute for Management Science, School of Business)

Abstract

This study explores how data-driven decision-making dimensions influence successful growth hacking implementation in platform-based enterprises employing fuzzy set Qualitative Comparative Analysis. Focusing on five key dimensions of data-driven decision-making (i.e., learning orientation, technological infrastructure, data analysis skills, proactive process management, and knowledge renewal), the research aims to uncover the configurations of these dimensions that most significantly contribute to successful growth hacking performance outcomes. By analysing combinations of these conditions, the study seeks to determine which conditions are necessary and sufficient for achieving the highest growth hacking performance outcomes. The findings provide actionable insights for platform-based businesses, guiding them on how to structure and prioritise their data-driven approaches for optimised growth hacking outcomes.

Suggested Citation

  • Luca Simone Macca & Gabriele Santoro, 2026. "Exploring Configurations of Data-Driven Decision-Making Dimensions for Successful Growth Hacking Implementation: An fsQCA Approach," Palgrave Intersections of Business and the Sciences, in association with Gnosis Mediterranean Institute for Management Science, in: Shahriar Akter & Md Afnan Hossain & Hélène Yildiz & Demetris Vrontis & Alkis Thrassou (ed.), Advanced Technologies in Business, Volume I, chapter 0, pages 245-273, Palgrave Macmillan.
    • Handle: RePEc:pal:pinchp:978-3-032-03480-9_10
    DOI: 10.1007/978-3-032-03480-9_10
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