Navigating disruptive innovation through opportunity recognition: A configurational approach to team learning

Zhiwei Wang, Lican Wei and Song Wang

Technovation, 2025, vol. 144, issue C

Abstract: Perceiving, interpreting, and predicting disruptive innovation ex ante are crucial but challenging. Although recognizing disruptive innovation opportunities is more likely a result of collective efforts, prior research has primarily focused on external organizational drivers and individual-level attributes or only focused on simple effect of single factors. Recent studies highlight the strategic role of team learning in building the micro-foundations of organizational dynamic capabilities. This study employs a configurational approach (fsQCA) to examine how individual and team-level antecedents interact to facilitate the recognition of disruptive innovation opportunities through team learning processes (intuition, interpretation, and integration). Drawing on field data from 65 teams, we identify three distinct configurations: Sharing-integrated, Improvisation-inspired, and Star-led. Specifically, teams can proactively recognize disruptive innovation opportunities through collective wisdom, which is generated by sharing and integration within the team, inspired by a learning process of improvisation, or catalyzed by the guidance of star performers in the team. This study contributes to the existing literature on disruptive innovation by elaborating how teams can collaboratively and creatively recognize disruptive opportunities through learning processes. Furthermore, it advances micro-foundations research on organizational capabilities in effectively managing disruption. The configurational approach provides a nuanced understanding of opportunity recognition within the context of disruptive innovation.

Keywords: Opportunity recognition of disruptive innovation; Team learning; Disruptive innovation; Opportunity recognition; fsQCA (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:144:y:2025:i:c:s0166497225000689

DOI: 10.1016/j.technovation.2025.103236

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