Multimethod research promises substantial benefits — the ability to generate and test theory within a single manuscript, triangulation across methodological traditions, and more complete understanding of complex organizational phenomena. Yet these benefits accrue only when the research is deliberately designed and genuinely integrated. Drawing on a review of 238 articles published in the Academy of Management Journal (Wellman et al., 2023), this session examines the practicalities of mixing methods in management research. I first introduce five empirically derived archetypes of multimethod research — methodological triangulation for hypothesis testing, methodological triangulation for theory development, test-and-explore, explore-and-test, and full research cycle — and show that the field overwhelmingly defaults to a single archetype (triangulation for hypothesis testing, 75%), leaving considerable theoretical potential untapped. I then identify three common pitfalls observed in editorial review: poor justification for mixing methods, poor methodological fit with the state of existing theory, and poor theoretical complementarity across studies. To address the integration challenge, I draw on Tunarosa and Glynn’s (2017) relational algorithms framework, demonstrating how different conceptual connectors between methods (beyond the default “and”) open up richer integration possibilities — including simultaneous, full-cycle, and mono-logic strategies. The session concludes with four practical recommendations: employ less common archetypes, explain the rationale for mixing methods explicitly and early, ensure theoretical and operational alignment across studies, and use supplementary materials thoughtfully. Throughout, I emphasize that more methods are not inherently better — the value of multimethod research lies not in the combination itself, but in the theoretical coherence and integration it enables.
