Table 1.

Estimators for structural equation models based on PLS

EstimatorInventor(s)Purpose
PLSWold (1974, 1975, 1982)A computationally efficient but inconsistent estimator for structural equation models containing latent variables (however, it provides consistent estimates for the composite model)
ordinal PLSCantaluppi and Boari (2016) A modification of PLS that can cope with ordinal categorical observed variables in a psychometric way
robust PLSSchamberger et al. (2020) A modification of PLS that can cope with unsystematic outliers
PLScDijkstra and Henseler (2015a, 2015b)An extension of PLS that provides consistent estimates for structural models containing latent variables
PLSe1Huang (2013) A one-step improvement methodology based on PLSc-estimated factor loadings and 2SLS-estimated structural parameters
PLSe2Huang (2013) An optimal generalized least squares methodology using a PLSc-implied covariance matrix
ordinal PLScSchuberth et al. (2018b)A modification of PLSc that can cope with ordinal categorical observed variables in a psychometric way
robust PLScSchamberger et al. (2020) A modification of PLSc that can cope with unsystematic outliers
PLSc via regularizationJung and Park (2018) A modification of PLSc that can cope with multicollinearity issues in the structural model

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