The weighted PLS algorithm (WPLS), as presented by Becker, J.-M., & Ismail, I. R. (2016). Accounting for Sampling Weights in PLS Path Modeling: Simulations and Empirical Examples. European Management Journal, 34(6), 606-617 is an extension of the traditional PLS path modeling approach. It incorporates sampling weights into the estimation process to improve the representativeness of the results with respect to the target population. By accounting for unequal probabilities of selection and sample design, WPLS enables more accurate and generalizable conclusions in survey-based research. Additional information on WPLS can be found in the explanatory resources provided on the SmartPLS website.

The WPLS exmaple used the model and data presented by Cheah, J.-H., Roldán, J. L., Ciavolino, E., Ting, H., & Ramayah, T. (2021). Sampling Weight Adjustments in Partial Least Squares Structural Equation Modeling: Guidelines and Illustrations. Total Quality Management & Business Excellence, 32(13-14), 1594-1613. For a comprehensive explanation of the WPLS approach—including details on the model, dataset, and results—please refer to this article.

Simply download the project and import it in SmartPLS 4.