PLS‐SEM: A method demonstration in the R statistical environment

In line with calls to stimulate methodological diversity and support evidence‐based human resource development (HRD) through quantitative competencies, we present a methods demonstration leveraging open‐source tools and lesser‐known quantitative research methods to support the HRD research community...

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Veröffentlicht in:Human resource development quarterly 2023-11, Vol.35 (4), p.501-529
Hauptverfasser: Legate, Amanda E., Ringle, Christian M., Hair, Joseph F.
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container_title Human resource development quarterly
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creator Legate, Amanda E.
Ringle, Christian M.
Hair, Joseph F.
description In line with calls to stimulate methodological diversity and support evidence‐based human resource development (HRD) through quantitative competencies, we present a methods demonstration leveraging open‐source tools and lesser‐known quantitative research methods to support the HRD research community and applied HRD in the workplace. In this paper, we provide an informative introduction to partial least squares structural equation modeling (PLS‐SEM). We discuss PLS‐SEM application trends in the field of HRD, present key characteristics of the method, and demonstrate up‐to‐date metrics and evaluation guidelines using an illustrative model. Our PLS‐SEM demonstration and explanations can serve as a valuable resource for practitioners concerned with substantiating results for organizational stakeholders and support researchers in methodological decision‐making while avoiding common pitfalls associated with less familiar methods. Our step‐by‐step demonstration is conducted in open‐source software and accompanied by explicitly coded operations so that readers can easily replicate the illustrative analyses presented.
doi_str_mv 10.1002/hrdq.21517
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subjects causal‐predictive modeling
HRD
human resource development
Human resource management
mediation analysis
Open source software
partial least squares structural equation modeling
PLS‐SEM
R statistical software
SEMinR
Structural equation modeling
title PLS‐SEM: A method demonstration in the R statistical environment
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