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

Joeri Hofmans, Alexandre Morin, Heiko Breitsohl, Eva Ceulemans, Leandre Alexis Chenard-Poirier, Charles Driver, Claude Fernet, Marylene Gagne, Nicolas Gillet, Vicente Gonzalez-Roma, Kevin Grimm, Ellen Hamaker, Kit-Tai Hau, S. Houle, Joshua Howard, Rex Kline, E. Kuijpers, Theresa Leyens, David Litalien, Anne MikakangasHerbert Marsh, Matthew McLarnon, John Meyer, Jose Navarro, Elisabeth Olivier, Thomas O'Neill, Reinhard Pekrun, Katharina Salmela-Aro, Omar Solinger, S. Sonnentag, Louis Tay, Istvan Toth Kiraly, Robert Vallerand, Christian Vandenberghe, Yvonne Gerarda Theodora van Rossenberg, Tim Vantilborgh, Jasmine Vergauwe, Jesse Vullinghs, Mo Wang, Zhonglin Wen, Bart Wille

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
JournalIndustrial and Organizational Psychology
Publication statusPublished - 2021


  • sustantive-methodological synergy
  • Research methods


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