The 3rd Edition of the Primer on PLS-SEM is out!

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd ed. Thousand Oaks, CA: Sage.

All case studies in this PLS-SEM book use the SmartPLS 3 software.

Get it worldwide via Google Play Books!

 

 

 

 

 

 

Brief Description

With applications using SmartPLS — the primary software used in partial least squares structural equation modeling (PLS-SEM) — this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the third edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

 

New to this edition

  • All screenshots and instructions have been updated for the latest edition of the SmartPLS 3 software.
  • The latest research on the nature of composite-based modeling provides a more thorough conceptual foundation for PLS-SEM.
  • More on the distinction between PLS-SEM and CB-SEM helps readers choose the right technique for their project.
  • Applications of PLS-SEM with secondary or archival data shows readers even more applications for this approach.
  • Improved guidelines for generating and validating single-item measures for redundancy analyses and determining minimum sample sizes help clarify these steps.
  • Coverage of model fit, analysis of predictive power, and metrics of model comparison have all been expanded for a richer discussion of PLS-SEM.
  • A thoroughly revised and updated Chapter 7 on mediator and moderator analysis covers more types of mediation, and provides updated explanations and guidelines on moderated mediation.
  • Extended coverage of more advanced concepts helps readers go further with PLS-SEM
  • Summaries are now structured by learning outcome for improved organization.

Hear from Marko Sarstedt about the new edition's unique features!


New Courses on PLS-SEM

ONLINE COURSE: Partial Least Squares SEM Using SmartPLS: Foundations and Advanced Topics

Foundations on PLS-SEM: November 04-05, 2021

Advanced topics in PLS-SEM: November 25-26, 2021

 

Visit the SmartPLS webpages to get to know other upcoming courses on PLS-SEM.


24/7 Online Courses!

You want to learn the basics of PLS-SEM or dive into more advanced topics such as moderation, mediation, or higher-order models? Join the PLS-SEM Academy and learn everything you need to know about the method. Here are some of the Academy's key benefits:

  • More than seven hours of video material on the principles and advanced topics in PLS-SEM

  • Based on the famous PLS-SEM books

  • Presented by world-wide renown instructors

  • Covers the latest developments in PLS-SEM as requested by reviewers and journal editors

  • Comprehensive lecturing slides included

  • Annotated outputs from SmartPLS illustrate all analyses step-by-step

  • Certificate after successful completion of the final exam


Go to PLS-SEM Academy and check out the freel trial lectures.


2022 International Conference on
Partial Least Squares Structural Equation Modeling


October 25-28, 2022
Beihang University, Beijing

Conference co-chairs:
Huiwen Wang, Yide Liu, Christian M. Ringle, and Marko Sarstedt


Keynote speaker:
Joseph F. Hair, Professor of Marketing, University of South Alabama, USA

 

Preconference workshops: October 25, 2020




The Primer on PLS-SEM in Spanish!

 

Hair, J.F., Hult, G.T.M., Ringle, C.M, Sarstedt, M., Castillo Apraiz, J., Cepeda Carrión, G.A., an Roldán, J.L. (2019). Manual de Partial Least Squares Structural Equation Modeling (PLS-SEM) (Segunda Edición). OmniaScience. 

https://www.omniascience.com/books/index.php/scholar/catalog/book/108




PLS-SEM Courses and Training

Please visit https://www.smartpls.com/courses/index
for the latest information on upcoming courses.


SmartPLS 3 - The Software for the Next Generation of PLS Path Modeling