The essential ingredients for business model innovation on the verge of emerging disruptive technologies: Harnessing foresight, mastering sensemaking, and embracing learning

This doctoral dissertation explores how organizations can renew their business models (BMs) in the face of rapid technological disruption and environmental turbulence. The research highlights the limitations of traditional business model innovation (BMI) approaches in volatile, uncertain, complex, and ambiguous (VUCA) contexts and proposes strategic foresight as a key enabler of future-oriented innovation.

Through four interconnected studies, the dissertation demonstrates how foresight methods—such as horizon scanning, scenario planning, and sensemaking—help firms anticipate change, overcome cognitive and structural barriers, and align innovation with emerging technologies like 5G. The findings show that strategic foresight not only expands innovation beyond entrenched logics but also strengthens organizational learning and adaptability.

Empirical evidence confirms that foresight directly and indirectly influences BMI through enhanced sensemaking and learning processes. By integrating qualitative foresight methodologies with quantitative hypothesis testing, the research offers a robust mixed-methods approach and actionable insights for managers seeking resilient and adaptive business models.

This pioneering work is the first to systematically and empirically link strategic foresight with BMI, providing a valuable contribution to both academic theory and practical strategy development in dynamic technological landscapes.