How Double-Loop Learning Powers Business Model Innovation in Digital Startups: Mapping Enablers Across Core Dimensions

Little is known about the enablers of Business Model Innovation (BMI) and their impact on value creation, delivery, and capture in digital startups (DSs). This study examines these enablers through the lens of organizational learning, demonstrating that double-loop learning is the key mechanism through which DSs reframe underlying assumptions to achieve sustained BM transformation. We integrate two existing frameworks into a unified model consisting of three categories of enablers (i.e., dynamic capabilities, paradoxical management strategies, and methodologies) that are subdivided into eight primary BMI enablers. We apply this framework deductively by conducting 22 in-depth interviews with founders of 20 DSs. The findings reveal how BMI unfolds in practice, highlighting the dominant role of sensing capabilities, exploration/exploitation strategies, and Lean Startup methodology in shaping value creation and capture. Theoretically, this study contributes to the extant literature on BMI and organizational learning literature by demonstrating how specific enablers activate double-loop learning processes to drive strategic renewal across value creation, delivery, and capture. In practice, this study provides a roadmap for startups, policymakers, and ecosystem actors to mobilize specific enablers aligned with the targeted BMI dimension, enhancing strategic agility and resilience.