When to Use PLS-SEM (and When Not)

Hair et al. (2019), p. 5: "Researchers should select PLS-SEM:

  • when the analysis is concerned with testing a theoretical framework from a prediction perspective;
  • when the structural model is complex and includes many constructs, indicators and/or model relationships;
  • when the research objective is to better understand increasing complexity by exploring theoretical extensions of established theories (exploratory research for theory development);
  • when the path model includes one or more formatively measured constructs;
  • when the research consists of financial ratios or similar types of data artifacts;
  • when the research is based on secondary/archival data, which may lack a comprehensive substantiation on the grounds of measurement theory;
  • when a small population restricts the sample size (e.g. business-to-business research); but PLS-SEM also works very well with large sample sizes;
  • when distribution issues are a concern, such as lack of normality; and
  • when research requires latent variable scores for follow-up analyses."

Hair, J.F./ Risher, J.J./ Sarstedt, M./ Ringle, C.M.: When to Use and How to Report the Results of PLS-SEM, European Business Review, Volume 31 (2019), Issue 1, pp. 2-24.

Also see these articles that provide recommendations when to select PLS-SEM (and when not):