Structural model robustness checks in PLS-SEM

TLDR

PLS‑SEM is widely used for complex variable relationships, yet tourism research has been slow to adopt complementary robustness methods that have been documented elsewhere. The article demonstrates recent PLS‑SEM advances that assess robustness to nonlinear effects, endogeneity, and unobserved heterogeneity, urging routine use to improve methodological rigor. The authors illustrate these advances within a PLS‑SEM framework to ensure structural model results are robust against nonlinear effects, endogeneity, and unobserved heterogeneity.

Abstract

Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contributed several complementary methods for assessing the robustness of PLS-SEM results. Although these improvements are documented in extant literature, research on tourism has been slow to adopt the relevant complementary methods. This article illustrates the use of recent advances in PLS-SEM, designed to ensure structural model results’ robustness in terms of nonlinear effects, endogeneity, and unobserved heterogeneity in a PLS-SEM framework. Our overarching aim is to encourage the routine use of these complementary methods to increase methodological rigor in the field.