The baby and the bathwater: On the need for substantive-methodological synergy in organizational research

Joeri Hofmans*, Alexandre J.S. Morin, Heiko Breitsohl, Eva Ceulemans, Leándre Alexis Chénard-Poirier, Charles C. Driver, Claude Fernet, Marylène Gagné, Nicolas Gillet, Vicente González-Romá, Kevin J. Grimm, Ellen L. Hamaker, Kit Tai Hau, Simon A. Houle, Joshua L. Howard, Rex B. Kline, Evy Kuijpers, Theresa Leyens, David Litalien, Anne MäkikangasHerbert W. Marsh, Matthew J.W. McLarnon, John P. Meyer, Jose Navarro, Elizabeth Olivier, Thomas A. O'Neill, Reinhard Pekrun, Katariina Salmela-Aro, Omar N. Solinger, Sabine Sonnentag, Louis Tay, István Tóth-Király, Robert J. Vallerand, Christian Vandenberghe, Yvonne G.T. Van Rossenberg, Tim Vantilborgh, Jasmine Vergauwe, Jesse T. Vullinghs, Mo Wang, Zhonglin Wen, Bart Wille

*Corresponding author for this work

Research output: Contribution to JournalComment / Letter to the editorAcademic


Murphy (2021) argues that the field of Industrial-Organizational (I/O) Psychology needs to pay more attention to descriptive statistics (“Table 1”; e.g., M, SD, reliability, correlations) when reporting and interpreting results. We agree that authors need to present a clear and transparent description of their data and that descriptive statistics and plots can be helpful in making sense of one’s data and analyses (Tay et al., 2016). Many journals already require this. Although this information can be presented in the manuscript, more details can be placed in online supplements where there are fewer space limitations (e.g., detailed presentation and discussion of descriptive statistics, missing data and outliers, plots and diagrams, conceptual issues, and computer syntax). However, we strongly disagree with the claim that “increasing complexity and diversity of data-analytic methods in organizational research has created several problems in our field” (p. 2). This claim suffers from two important oversights: (1) it neglects the crucial role of methodological fit, or the notion that theory, methods, and analyses need to be aligned, and (2) it neglects the fact that in I/O research, most constructs are not directly observable but need to be inferred indirectly though latent variable models. We expand on both issues, using xamples to illustrate that the complexity and diversity of data-analytic methods is not a threat but a blessing for I/O research (and beyond). Finally, we conclude by highlighting the need for substantive-methodological synergies to solve some of the issues raised by Murphy (2021).
Original languageEnglish
Pages (from-to)497-504
Number of pages8
JournalIndustrial and Organizational Psychology
Issue number4
Early online date14 Dec 2021
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
The second author was supported by a grant from the Social Sciences and Humanities Research Council of Canada (435-2018-0368).


  • sustantive-methodological synergy
  • Research methods


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