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Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management

Author

Listed:
  • Kozak, Jan
  • Kania, Krzysztof
  • Juszczuk, Przemysław
  • Mitręga, Maciej

Abstract

One type of data-driven innovations in management is data-driven decision making. Confronted with a big amount of data external and internal to their organization's managers strive for predictive data analysis that enables insight into the future, but even more for prescriptive ones that use algorithms to prepare recommendations for current and future actions. Most of the decision-making techniques use deterministic machine learning (ML) techniques but unfortunately, they do not take into account the variety and volatility of decision-making situations and do not allow for a more flexible approach, i.e., adjusted to changing environmental conditions or changing management priorities. A way to better adapt ML tools to the needs of decision-makers is to use swarm intelligence ML (SIML) methods that provide a set of alternative solutions that allow matching actions with the current decision-making situation. Thus, applying SIML methods in managerial decision-making is conceptualized as a company capability as it allows for systematic alignment of allocating resources decisions vis-à -vis changing decision-making conditions.

Suggested Citation

  • Kozak, Jan & Kania, Krzysztof & Juszczuk, Przemysław & Mitręga, Maciej, 2021. "Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management," International Journal of Information Management, Elsevier, vol. 60(C).
  • Handle: RePEc:eee:ininma:v:60:y:2021:i:c:s0268401221000505
    DOI: 10.1016/j.ijinfomgt.2021.102357
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    Cited by:

    1. Alghamdi, OmarA. & Agag, Gomaa, 2024. "Competitive advantage: A longitudinal analysis of the roles of data-driven innovation capabilities, marketing agility, and market turbulence," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).

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