Quantifying uncertainty in PLS-SEM-based mediation analyses

To identify potential mediating effects, researchers applying partial least squares structural equation modeling (PLS-SEM) typically contrast specific indirect and direct effects in a sequence of steps. Extending this standard procedure, we conceive mediation analysis as a type of model comparison,...

Full description

Saved in:
Bibliographic Details
Published inJournal of marketing analytics Vol. 12; no. 1; pp. 87 - 96
Main Authors Sarstedt, Marko, Moisescu, Ovidiu-Ioan
Format Journal Article
LanguageEnglish
Published London Palgrave Macmillan UK 01.03.2024
Palgrave Macmillan
Subjects
Business and Management
Market analysis
Marketing
Mathematical models
Original Article
Quality assessment
Reputations
Researchers
Structural equation modeling
Uncertainty
Akaike weights
Uncertainty
Mediation
Partial least squares structural equation modeling
PLS-SEM
Online AccessGet full text

Cover

More Information
Summary:To identify potential mediating effects, researchers applying partial least squares structural equation modeling (PLS-SEM) typically contrast specific indirect and direct effects in a sequence of steps. Extending this standard procedure, we conceive mediation analysis as a type of model comparison, which facilitates quantifying the degree of the model effects’ uncertainty induced by the introduction of the mediator. By introducing a new dimension of quality assessment, the procedure offers a new means for deciding whether or not to introduce a mediator in a PLS path model, and improves the replicability of research results.
ISSN:2050-3318
2050-3326
DOI:10.1057/s41270-023-00231-9