… This paper proposes that PLS path models in longitudinal studies can be distinguished
according to two criteria: the research objective and the data basis that is available. In a first step, …

… R 2 (Cohen et al., 2003). Mode B estimation in PLS path modeling is known to produce
higher R 2 values for proxies of dependent concepts, as compared to R 2 values using Mode A …

… provides a brief introduction to the PLS path modeling algorithm. The third section presents
… and application of PLS path modeling as well as for users of PLS path modeling in general …

… variables’ R-squared, the statistical inference of path coefficients, and effect sizes. … or service
quality studies—a typical domain of PLS path modeling. A central finding is that when there …

… Applications of the partial least squares (PLS) path modeling approach—… for PLS path
modeling (PLS-GAS) that accounts for the critical issue of unobserved heterogeneity in the path …

… least squares (PLS) path modeling and shows that the inconsistency of PLS path coefficient
… To remedy this, the study introduces a vital extension of PLS: consistent PLS (PLSc). PLSc …

… PLS path models are formally defined by two sets of linear … Figure 12.1 depicts an example
of a PLS path model. … First, we look at the coefficient of determination (R 2 value) of the …

… Their study examined out-of-sample R 2 in regression. The authors created large … -sample
R 2 only when both sample size was quite large and true predictability (the true population R 2 …

… In particular, the main features of the ADANCO, SmartPLS, WarpPLS, XLSTAT-PLSPM, the
Stata package for plssem, and the cSEM and SEMinR packages for R, are illustrated in this …

… PLS path modeling community should work to complete and validate a purely composite-based
approach to evaluating modeling … However, the R 2 only has informative value with …