Treating Unobserved Heterogeneity in PLS-SEM: A Multi-method Approach

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An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research (2017, methodology): “No statistical method, including PLS-SEM, can offset a badly designed sample (Sarstedt et al., 2017a).”
Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling (2018, methodology): “Sarstedt, Ringle, and Hair (2017b) recently introduced a systematic procedure for identifying and treating unobserved heterogeneity in PLS path models.”
Structural model robustness checks in PLS-SEM (2020, methodology): “To determine the maximum number of segments to extract, we first computed the minimum sample size required to estimate each segment (Sarstedt et al., 2017b).”
Why Not Green Marketing? Determinates of Consumers’ Intention to Green Purchase Decision in a New Developing Nation (2020, background): “Moreover, statistical experts noted that there are enormous advantages of PLS-SEM as a nonparametric; such as the fact that normally distributed data are not required, the small sample size is applicable, and type II errors can reduce with efficiently managing formative measurements [142,143,145,146”