Reflective-Reflective Higher Order Model using SMART-PLS
A widely debated Hierarchical Component Model (HCM) configuration is the reflective-reflective type. Critics argue that this type of HCM does not exist, or that it is meaningless because the reflective measures should be unidimensional and conceptually interchangeable. This conflicts with the view held by others that multiple underlying dimensions are distinct in nature.
Applying the disjoint two-stage approach,
A Reflective-Reflective Higher Order model may be assessed using Repeated indicators approach or Disjoint Two Stage Approach. In this tutorial the focus is on disjoint two stage approach. In Disjoint two stage approach, we follow the following mentioned procedure.
In the first stage create and estimate the model connecting all the lower-order components (Including Exogenous and Endogenous constructs). The model assessment first focuses on the reflective measurement models of the lower-order components. No Higher Order Constructs are modeled. Only LOCs for the HOCs are added to the canvas in the SMART-PLS. In the first stage all the LOCs are assessed for Reliability and Validity. The Measurement model is assessed as we normally do. for further detail, Click Here
After the Measurement model is assessed and reported (to learn how to report, Click here), use Latent Variable Score and save it in your data file to be used in the Second Stage.
In stage two, use the latent variable scores of the lower-order components from stage one to create and estimate for the stage two model.
For this purpose, locate the scores of LOCs of the HOC and add these as new variables to the dataset. The results are similar to the ones of the repeated indicators approach but with slight differences of the path coefficient estimates.
The evaluation of stage two starts with focusing on the reflective measurement model of the higher-order component. For HOC, see the loadings of LOC for the HOC, assess the CR and AVE using the coefficients (loadings) enabling us to establish indicator reliabilities and AVE.
These results above the critical value of 0.5. Cronbach’s alpha, CR and AVE establish reliability and convergent validity. Based on the HTMT criterion, discriminant validity with other LOCs can been established.
Finally, the assessment of the stage two results addresses the structural model. The analysis shall assess the structural model evaluation (e.g., significance and relevance for path coefficients, Q², PLS predict).
Sarstedt, M., Hair Jr, J. F., Cheah, J. H., Becker, J. M., & Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian Marketing Journal (AMJ), 27(3), 197-211.