Investigating and communicating the uncertainty of effects: The power of graphs

Abstract

Entrepreneurial activities are inherently risky and related outcomes uncertain. Consequently, empirical studies to build entrepreneurship theory need to investigate not only the direction and average size of effects but also the uncertainty of these effects. Current research published in academic entrepreneurship journals tends to focus on dichotomous likelihood evaluations employing statistical significance tests. This editorial argues that graphs communicating the distribution of observed effects offer a far more useful way to communicate, evaluate, and discuss uncertainty. Publishing such graphs will support theory building and offer more meaningful guidance to practitioners and policy makers.