Moving forward quantitative research on innovation management: a call for an inductive turn on using and presenting quantitative research

Abstract

Whereas innovation scholars have mainly relied on survey designs, secondary data and experiments to engage in deductive theory‐testing research, I highlight that quantitative data can also be viable sources to induce theoretical insights into emerging innovation phenomena. In this paper, I discuss how scholars can use quantitative data for inductive innovation management research. First, I point to quantitative data as viable complements to enrich qualitative inductive research. Second, I point to the presence of alternative methods (e.g., cluster analyses and fsQCA) that allow using quantitative data as the core data for inductive research. Finally, I highlight the need to reduce the existing gap between how quantitative research on innovation management is executed and how it is presented in paper publications. In particular, I advocate an alternative mode of reporting that embraces the surprises and counterintuitive insights, which often emerge as scholars engage in a quantitative research journey. Together, my arguments aim to stimulate an inductive turn on quantitative research in innovation management, which can complement the existing deductive research tradition.