They are both internationally recognised. SEM-AMOS is typically used when you are working with reflective constructs whilst SEM-SMARTPLS can be used if you are using formative constructs or a mixture of both construct type.
The CB-SEM (SEM-AMOS) method was referred to by Wold as “hard modeling” because of the more restrictive assumptions of the method, such as normally distributed data and larger sample sizes. In contrast, he referred to PLS-SEM (SEM-SmartPLS) as “soft modeling” because it does not require normally distributed data and performs well even when the data are highly skewed as is typical of much social sciences data (Hair et al., 2019).
Using AMOS, one can estimate, specify and access their model in the form of a diagram and define the relationship between the variables. This helps the researcher in analyzing and testing the data for validity and reliability.
The goal is predicting key target constructs or identifying key “driver” constructs.
Formatively measured constructs are part of the structural model. Note that formative measures can also be used with CB-SEM, but doing so requires construct specification modifications (e.g., the construct must include both formative and reflective indicators to meet identification requirements).
The structural model is complex (many constructs and many indicators).
The sample size is small and/or the data are nonnormally distributed.
The plan is to use latent variable scores in subsequent analyses.
Use CB-SEM when
The goal is theory testing, theory confirmation, or the comparison of alternative theories.
Error terms require additional specification, such as the covariation.
The structural model has circular relationships.
The research requires a global goodness-of-fit criterion.