Overall, PLS can be an adequate alternative to CBSEM (covariance based SEM) if the problem has the following characteristics (Chin, 1998; Chin & Newsted, 1999):
- PLS makes fewer demands regarding sample size than other methods.
- PLS does not require normal-distributed input data.
- The phenomenon to be investigated is relatively new and measurement models need to be newly developed,
- The structural equation model is complex with a large number of LVs and indicator variables,
- Relationships between the indicators and LVs have to be modeled in different modes (i.e., formative and reflective measurement models),
- The conditions relating to sample size, independence, or normal distribution are not met, and/or
- Prediction is more important than parameter estimation.
- PLS is better suited for theory development than for theory testing.