Confirmatory Composite Analysis (CCA)

Confirmatory composite analysis (CCA; Hair et al. 2018, Chapter 13; Hair et al., 2020; Henseler and Schuberth, 2020; Schuberth et al., 2018) is a series of steps that can be executed with composite-based SEM methods such as PLS-SEM or GSCA to confirm both reflective and formative measurement models within a specific nomological network (for a CCA introduction and distinction of different views on CCA, see Crittenden et al., 2020). SmartPLS fully supports both CCA approaches in PLS-SEM.


  • Crittenden, V., Sarstedt, M., Astrachan, C., Hair, J., and Lourenco C. E. (2020). Guest Editorial: Measurement and Scaling Methodologies. Journal of Product & Brand Management, 29(4), 409-414.
  • Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2018). Multivariate Data Analysis, 8th ed., Cengage: Mason, OH.
  • Hair, J. F., Howard, M. C., and Nitzl, C. (2020). Assessing Measurement Model Quality in PLS-SEM Using Confirmatory Composite Analysis. Journal of Business Research, 109, 101-110.
  • Henseler, J. and Schuberth, F. (2020). Using Confirmatory Composite Analysis to Assess Emergent Variables in Business Research. Journal of Business Research, 120, 147-156.
  • Schuberth, F., Henseler, J., and Dijkstra, T. K. (2018). Confirmatory Composite Analysis. Frontiers in Psychology, 9, 2541.


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