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Partial Least Squares Structural Equation Modeling (PLS-SEM) Techniques Using SmartPLS

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TLDR
This paper is written to address this knowledge gap and help beginners to understand how PLS-SEM can be used in marketing research.
Abstract
SmartPLS is one of the prominent software applications for Partial Least Squares Structural Equation Modeling (PLS-SEM). It was developed by Ringle, Wende & Will (2005). The software has gained popularity since its launch in 2005 not only because it is freely available to academics and researchers, but also because it has a friendly user interface and advanced reporting features. Although an extensive number of journal articles have been published on the topic of PLS modeling, the amount of instructional materials available for this software is limited. This paper is written to address this knowledge gap and help beginners to understand how PLS-SEM can be used in marketing research.

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References
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Journal ArticleDOI

Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
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TL;DR: A convenient, although not comprehensive, presentation of required sample sizes is providedHere the sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests.
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Xianggui Qu
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On the evaluation of structural equation models

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Book

A primer on partial least squares structural equation modeling (PLS-SEM)

TL;DR: The Second Edition of this practical guide to partial least squares structural equation modeling is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
Related Papers (5)
Trending Questions (2)
Why SmartPLS 4.0 be used to conduct different types of SEM analyses?

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How to calculate sample size from population when we use PLS SEM?

Determining the appropriate sample size is often a challenge when using PLS-SEM.