Why Guess When You Can Test? How and Why Scientific Pivoting is Implemented in Startups

Abstract

This research investigates the implementation and antecedents of a scientific approach to pivoting, a decision-making process involving theorization, hypothesis setting, hypothesis testing and evaluation. The need to shift towards new directions is common in the uncertain environments startups operate in, but little is known about how and when pivots are performed using scientific practices. A qualitative research design was employed to conduct 28 in-depth interviews with key decision-makers of startups that have performed a pivot, aiming to explore the antecedents that drive adoption of scientific activities during pivots and the ways these activities are implemented in practice. The findings reveal that scientific activities are applied pragmatically and iteratively, rather than through formalized practices. Hypothesis setting and testing were rarely observed and theorization and evaluation emerged through informal means. 5 key antecedents drive the adoption of scientific practices: key decision-maker experience, resource constraints, stakeholder guidance, strategic decision-making demands and industry complexity. Notably, resource constraints drive scientific behaviour among experienced entrepreneurs that recognize the risks of pivoting without careful theorization and validation. Otherwise, these constraints drive intuitive behaviour. This thesis contributes to entrepreneurial decision-making and pivoting literature by identifying antecedents and refining the conceptualisation of scientific pivoting, emphasizing its hybrid nature