Partial least squares path modeling (PLS-PM) is an estimator that has found widespread
application for causal information systems (IS) research. Recently, the method has been …

Perhaps no other topic in risk analysis is more difficult, more controversial, or more important
to risk management policy analysts and decision-makers than how to draw valid, correctly …

When estimating moderating effects in partial least squares structural equation modeling
(PLS-SEM), researchers can choose from a variety of approaches to model the influence of …

Digital transformation and technologies have drastically channeled innovative global market
trends from conventional commerce to digital currency. Therefore, this study examined the …

Purpose In their paper titled “A Miracle of Measurement or Accidental Constructivism? How
PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on …

Multicollinearity, or the existence of excessive correlations among (combinations of)
predictor variables, is a commonly encountered phenomenon that affects (PLS-SEM) …

Despite the recent developments in AI, ethical questions arise when consumers contemplate
how their data is being treated. This paper develops a conceptual model building on the …

Bayesian approaches for estimating multilevel latent variable models can be beneficial in
small samples. Prior distributions can be used to overcome small sample problems, for …

Climate change poses significant risks to coastal regions, compromising habitats,
economies, and well-being through flooding. This research assesses the indirect effects of …

This paper critically discusses a recent EJIS paper entitled “Will PLS have to become factor-
based to survive and thrive?”, which laments that covariance-based structural equation …