Reflections on Partial Least Squares Path Modeling

doi:10.1177/1094428114529165

Reflections on Partial Least Squares Path Modeling

2014-04-10

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Cameron N. McIntosh *

DOI：10.1177/1094428114529165

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Abstract

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The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics and proponents of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (a) can be truly characterized as a technique for structural equation modeling (SEM), (b) is able to correct for measurement error, (c) can be used to validate measurement models, (d) accommodates small sample sizes, (e) is able to provide null hypothesis tests for path coefficients, and (f) can be employed in an exploratory, model-building fashion. We summarize and elaborate further on the key arguments underlying the exchange, drawing from the broader methodological and statistical literature to offer additional thoughts concerning the utility of PLS-PM and ways in which the technique might be improved. We conclude with recommendations as to whether and how PLS-PM serves as a viable contender to SEM approaches for estimating and evaluating theoretical models.

Keywords:

structural equation modeling

partial least squares

factor analysis

reliability and validity

instrumental variables

bootstrapping

model fit

Reflections on Partial Least Squares Path Modeling

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