Partial least squares path modeling: Quo vadis?

By Jörg Henseler. Quality & Quantity: International Journal of Methodology, 2018

541 citations recorded by the source corpus.

Subfields: Information Systems and Management, Marketing, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/3a8ba46f2dcff1c5bd12ab3d5db4d03bac840b18

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Citations in the corpus

The COVID-19 pandemic and organisational commitment of senior hotel managers (2020, unknown): “Third, the model is complex since it includes direct and indirect relationships in order to predict dependent latent variables, the task which PLS is capable of handling effectively (Cepeda-Carrion et al., 2019).”
Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations (2020, methodology): “Practically all studies that use PLS-SEM frame their approach in a confirmatory sense – that is, a literature review is followed by the derivation of formal hypotheses and finally the model estimation (Henseler, 2018).”
Marketing Mix Modeling Using PLS-SEM, Bootstrapping the Model Coefficients (2021, background): “As [35] stated, the different meaning of the term fit does not depend on whether co‐ variance‐based SEM or variance‐based SEM is used but on whether confirmatory or ex‐ planatory research is performed (see [36]).”
Confirmatory composite analysis using partial least squares: setting the record straight (2020, background): “Moreover, studies provide arguments for and against the use of PLS (e.g., Rigdon 2016) and how PLS can be of value for different types of research (Henseler 2018).”
Investigating the effects of tourist engagement on satisfaction and loyalty (2019, methodology): “Results and findings To assess the measurement model and the structural model, we followed the recently suggested guidelines for the use of PLS-PM in confirmatory and explanatory research (Henseler, Hubona, & Ray, 2016; Müller, Schuberth, & Henseler, 2018).”