ANAHEI Webinars

WarpPLS: An Introduction

July 18, 2017 at 10:00am EST (New York Time)

WarpPLS: An Introduction

Presented by Dr. S. Mostafa Rasoolimanesh

Webinar Starts in:


Structural Equation Modeling (SEM) is a statistical approach to analyze a hypothetical framework. It allows a researcher to test and develop theories, and to test the relationships between latent variables on the conceptual model. PLS-SEM, a major type of SEM, can handle theory development and is lenient towards model’s assumption of data normality and sample size. PLS-SEM is a variance-based approach and aims to maximize the explained variance of the dependent latent constructs. Hence, PLS-SEM is preferred when a researcher wants to predict the construct and identify relationship between them. WarpPLS software package is a powerful non-linear package to perform PLS-SEM. It can handle linear and non-linear relationships between constructs. The software provides various composite and factor –based algorithms for outer model, and different resampling methods. In addition to all quality criteria to assess the reflective and formative measurement models, several important criteria such as; full collinearity including lateral and vertical collinearity between constructs are provided by WarpPLS. It provides plots of all relationships between constructs, as well as, 2D and 3D figures for moderators. WarpPLS 6.0 as the latest version of WarpPLS, providing many more new features to analyze models. This webinar will briefly explain PLS-SEM and WarpPLS and its features.

Webinar video and slides are available online.

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Dr. S. Mostafa Rasoolimanesh

Dr. S. Mostafa Rasoolimanesh is a lecturer and senior lecturer in the School of Hospitality, Tourism, and Events at Taylor's University, Malaysia. He has published several articles in high impact SSCI-indexed journals such as Tourism Management, Journal of Travel Research, Journal of Sustainable Tourism, Cities, Habitat International, International Journal of Tourism Research, and Asia Pacific Journal of Tourism Research.