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From hypothesis testing toward inference to the best explanation: A PEEBI testimonial structure for abductive studies in strategy
Journal article   Open access   Peer reviewed

From hypothesis testing toward inference to the best explanation: A PEEBI testimonial structure for abductive studies in strategy

Sandeep Devanatha Pillai, Brent Goldfarb, David A. Kirsch, Seojin Kim and Evan Starr
Strategic management journal, Forthcoming
02 Aug 2026
Featured in Collection :   Drexel's Newest Publications
url
https://doi.org/10.1002/smj.70114View
Published, Version of Record (VoR) Open

Abstract

abduction narratives philosophy of science reasoning testimony

Research Summary Though scholars employ abduction, there is no agreed-upon structure to reporting their findings. Moreover, the traditional hypo-deductive reasoning structure does not align with the epistemology of abduction. We propose an abductive testimonial structure, termed PEEBI, which consists of five sections in which the authors take prior knowledge and theories, establish the context and observations that are worthy of interest, identify and evaluate candidate explanations for the observed patterns, determine the best explanation and their reasoning for accepting it, and abstract the best explanation to a more generalizable theoretical contribution. Consistent with abductive epistemology, PEEBI advances knowledge in a modest, stepwise fashion. PEEBI foregrounds transparency and communication of the author's judgment and elevates the role of the readers by giving them information to better make judgments.Managerial Summary Researchers frequently make discoveries by starting from a surprising observation and reasoning backward to the best explanation. Yet, the field has no shared way to write up this kind of work, and the conventional hypothesis-testing template does not match how such reasoning unfolds. We propose a reporting structure, PEEBI, which consists of five sections in which the authors take prior knowledge and theories, establish the context and observations that are worthy of interest, identify and evaluate candidate explanations for the observed patterns, determine the best explanation and their reasoning for accepting it, and abstract the best explanation to a more generalizable theoretical contribution. PEEBI makes the author's judgment transparent, giving readers the information they need to weigh the evidence and reach their own conclusions.

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