This paper argues that abductive reasoning provides a valuable approach for integrating computational methods into management and organization studies (MOS). Although computational methods excel at uncovering unexpected patterns in data, the epistemic frameworks used to construct and evaluate insights from these discoveries are often in misalignment. As tools for generating candidate explanations and aiding in selecting the most pursuitworthy candidates among competing explanations, abductive-computational research designs complement traditional hypothesis-testing approaches. Abductive-computational research designs yield several pathways toward developing novel types of provisionally plausible theoretical contributions from large-scale data sets. The paper discusses the challenges of aligning such computational methodologies with existing academic norms and argues for adopting abductive reasoning as a core epistemic framework in support of computational MOS research designs.
