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

Jan Kozak, Krzysztof Kania, Przemysław Juszczuk and Maciej Mitręga

International Journal of Information Management, 2021, vol. 60, issue C

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.

Keywords: Churn management; Data-driven innovation; Machine learning; Decision trees; Classification; Dynamic capabilities (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ininma:v:60:y:2021:i:c:s0268401221000505

DOI: 10.1016/j.ijinfomgt.2021.102357

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