BAR - Brazilian Administration Review

Despite the consolidation of experimental designs as a central standard for causal inference in adjacent fields, experiments remain peripheral in large segments of management research. This article argues that such marginalization is not primarily technical, but epistemic and institutional. It reconstructs six recurrent objections — complexity, external validity, feasibility, theory reduction, non-manipulability, and ethical scope — that structure skepticism toward experimentation and shows how they normalize the substitution of statistical sophistication for design-based identification. The analysis suggests that resistance to experiments reflects entrenched evaluative norms about what counts as rigor and relevance, rather than demonstrated methodological inadequacy. To move beyond dichotomous debates, the article introduces a simple evaluative framework structured along two dimensions: causal ambition and organizational embeddedness. By conceptualizing experimentation as a continuum, the framework aligns the strength of causal claims with the inferential capacities of different designs, making trade-offs explicit rather than implicit. The central contribution is disciplinary rather than technical: repositioning experimentation as a reference point for transparent causal reasoning. The article concludes by calling for greater alignment between causal claims and research design, emphasizing inferential discipline as a condition for credible knowledge in management research.

The academic publication landscape in marketing and management has changed greatly in the past decades. In this interview, Professor Adamantios Diamantopoulos reflects on increased competition in top journals, the rise of open-access outlets, higher methodological standards, and more complex editorial structures. Drawing on his experience as an author, reviewer, associate editor, and editor, he discusses changes in peer review, editorial roles, and the challenges of desk rejections and reviewer competence. The discussion also covers artificial intelligence’s impact on authorship, reviewing, and data generation. The interview offers practical insights for scholars navigating a more competitive, complex publication environment.