The Newest addition is the SmartPLS4. The software released to the general public in 2022 is an easy to use tool for Structural Equation Modelling. To estimate the model in SmartPLS, the model has to be estimated at two levels that include the measurement model assessment and structural model assessment.
Measurement Model assessment involves several steps that includes the assessment of quality criteria that includes the evaluation of factor loadings, construct reliability, construct validity. The criteria for factor loadings is 0.70, any items with loadings less than 0.70 may be considered for removal, if removing the items can improve the reliability and validity over the required threshold. Further Construct reliability is assessed using Cronbach Alpha and Composite Reliability, the required value for both is 0.70. Further, construct validity is assessed using convergent validity (AVE > 0.50) and Discriminant validity (Fornell & Larcker Criterion and Heterotrait-Monotrait Ratio).
Next, after measurement model assessment structural model is assessed to substantiate the proposed hypotheses. This can include direct, indirect, or moderating relationships. SmartPLS4 is an increasingly used tool for SEM that can help model simple and complex model.
Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), pp. 1-32, p. 1, p. 15, and p. 30. http://marketing-bulletin.massey.ac.nz/V24/MB_V24_T1_Wong.pdf
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.), Thousand Oaks, CA: Sage Publications. https://us.sagepub.com/en-us/nam/a-primer-on-partial-least-squares-structural-equation-modeling-pls-sem/book270548
Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2018). Advanced issues in partial least squares structural equation modeling (PLS-SEM), Thousand Oaks, CA: Sage Publications. https://us.sagepub.com/en-us/nam/advanced-issues-in-partial-least-squares-structural-equation-modeling/book243803
Wong, Ken Kwong-Kay (2019-02-22). Mastering Partial Least Squares Structural Equation Modeling (Pls-Sem) with Smartpls in 38 Hours. iUniverse. ISBN 9781532066481. 9781532066481
Mumtaz Ali Memona, T. Ramayah, Jun-Hwa Cheah, Hiram Ting, Francis Chuah and Tat Huei Cham (2021). "PLS-SEM Statistical Programs: A Review" (PDF). Journal of Applied Structural Equation Modeling. 5(i): i–xiv.{{cite journal}}: CS1 maint: multiple names: authors list (link) https://jasemjournal.com/wp-content/uploads/2021/04/Memon-et-al-2021_JASEM51.pdf
Lohmöller, J.-B. (1989). Latent variable path modeling with partial least squares. Physica: Heidelberg, p. 29. https://www.worldcat.org/oclc/891146763
Wold, H. (1982). Soft modeling: The basic design and some extensions, in: K. G. Jöreskog and H. Wold (eds.), Systems under indirect observations: Part II, North-Holland: Amsterdam, pp. 1-54, pp. 2-3. /wiki/Herman_Wold
Ramayah, T., Cheah, J., Chuah, F., Ting, H., and Memon, M. A. (2018). Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0: An updated and practical guide to statistical analysis (2nd ed.), Singapore et al.: Pearson. https://www.researchgate.net/publication/312460772_Partial_Least_Squares_Structural_Equation_Modeling_PLS-SEM_using_SmartPLS_30_An_Updated_and_Practical_Guide_to_Statistical_Analysis
Garson, G. D. (2016). Partial least squares regression and structural equation models, Statistical Associates: Asheboro, pp. 122-188. http://www.statisticalassociates.com/pls-sem.htm
Sarstedt, Marko; Cheah, Jun-Hwa (2019-06-27). "Partial least squares structural equation modeling using SmartPLS: A software review" (PDF). Journal of Marketing Analytics. 7 (3): 196–202. doi:10.1057/s41270-019-00058-3. ISSN 2050-3318. S2CID 198334897. http://psasir.upm.edu.my/id/eprint/81615/1/Partial%20least%20squares%20structural%20equation%20modeling%20using%20SmartPLS%20a%20software%20review.pdf
Hair, Joseph F.; Risher, Jeffrey J.; Sarstedt, Marko; Ringle, Christian M. (2019). "When to use and how to report the results of PLS-SEM". European Business Review. 31 (1): 2–24. doi:10.1108/EBR-11-2018-0203. ISSN 0955-534X. S2CID 158782424. https://doi.org/10.1108/EBR-11-2018-0203
Temme, D., Kreis, H., and Hildebrandt, L. (2010). A comparison of current PLS path modeling software: Features, ease-of-use, and performance, in: V. Esposito Vinzi, W. W. Chin, J. Henseler, and H. Wang (eds.), Handbook of partial least squares: Concepts, methods and applications, Springer: Berlin-Heidelberg, pp. 737-756, p.745. https://www.worldcat.org/oclc/990473184
"Steps in Data Analysis". ResearchWithFawad. Retrieved 2023-10-09. https://researchwithfawad.com/index.php/lp-courses/smartpls4-tutorial-series/steps-in-data-analsis/
"A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)". SAGE India. 2023-10-08. Retrieved 2023-10-09. https://in.sagepub.com/en-in/sas/a-primer-on-partial-least-squares-structural-equation-modeling-pls-sem/book244583
"Recommended videos - SmartPLS". www.smartpls.com. Retrieved 2023-10-09. https://www.smartpls.com/documentation/getting-started/videos