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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

Second Edition

© 2017 | 384 pages | SAGE Publications, Inc

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 Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

Please note that all examples in this Second Edition use SmartPLS 3.
To access this software, please visit this link.

Chapter 1: An Introduction to Structural Equation Modeling
What Is Structural Equation Modeling?  
Considerations in Using Structural Equation Modeling  
Structural Equation Modeling With Partial Least Squares Path Modeling  
PLS-SEM, CB-SEM, and Regressions Based on Sum Scores  
Organization of Remaining Chapters  
Chapter 2: Specifying the Path Model and Examining Data
Stage 1: Specifying the Structural Model  
Stage 2: Specifying the Measurement Models  
Stage 3: Data Collection and Examination  
Case Study Illustration: Specifying the PLS-SEM Model  
Path Model Creation Using the SmartPLS Software  
Chapter 3: Path Model Estimation
Stage 4: Model Estimation and the PLS-SEM Algorithm  
Case Study Illustration: PLS Path Model Estimation (Stage 4)  
Chapter 4: Assessing PLS-SEM Results Part I: Evaluation of Reflective Measurement Models
Overview of Stage 5: Evaluation of Measurement Models  
Stage 5a: Assessing Results of Reflective Measurement Models  
Case Study Illustration—Reflective Measurement Models  
Running the PLS-SEM Algorithm  
Reflective Measurement Model Evaluation  
Chapter 5: Assessing PLS-SEM Results Part II: Evaluation of the Formative Measurement Models
Stage 5b: Assessing Results of Formative Measurement Models  
Bootstrapping Procedure  
Bootstrap Confidence Intervals  
Case Study Illustration—Evaluation of Formative Measurement Models  
Chapter 6: Assessing PLS-SEM Results Part III: Evaluation of the Structural Model
Stage 6: Assessing PLS-SEM Structural Model Results  
Case Study Illustration—How Are PLS-SEM Structural Model Results Reported?  
Chapter 7: Mediator and Moderator Analysis
Chapter 8: Outlook on Advanced Methods
Importance-Performance Map Analysis  
Hierarchical Component Models  
Confirmatory Tetrad Analysis  
Dealing With Observed and Unobserved Heterogeneity  
Consistent Partial Least Squares  


Student Resource Site
Visit the companion website to download data sets and other materials to supplement your studies in PLS-SEM!

“A text that students will find easy to read and enjoyable.”

Toni M. Somers
Wayne State University

The book brings new possibilities to analyse data. The book is easy to understand. Even the advanced topics are clear and easy to apply.

Professor Lucas Lira Finoti
Business Administration , FACEAR
June 20, 2016
Key features


  • A new overview of the latest research on composite-based modeling (e.g., distinction between composite and causal indicators) enhances reader understanding of the conceptual foundation for PLS-SEM.
  • New coverage includes recent discussion of PLS-SEM as a composite-based method to SEM, the distinction between PLS-SEM and CB-SEM and the model constellations which favor the use of PLS-SEM, the concept of model fit in a PLS-SEM context, and a new criterion for discriminant validity assessment: the heterotrait-monotrait (HTMT) ratio of correlations.
  • A new in-depth discussion explores the various types of mediation, alternative mediation analysis procedures, mediated moderation, and moderated mediation.
  • Coverage of several methods for constructing bootstrap confidence intervals includes percentile, studentized, bias-corrected, and accelerated, as well as two double bootstrap methods.
  • An updated chapter on advanced topics briefly introduces, among others, the importance-performance map analysis, confirmatory tetrad analysis, multigroup analysis, and measurement invariance assessment in PLS-SEM.
  • An extended description of moderation covers different approaches for creating the interaction term (e.g., the orthogonalizing approach), three-way interactions, measurement model evaluation, and the interpretation of results by using slope plots.


  • Simple instructions give readers the “how-tos” of using the SmartPLS software ( to obtain solutions, and prepare manuscripts using PLS-SEM for academic journal submissions.
  • Rules of Thumb in every chapter provide guidelines on best practices in the application and interpretation of PLS-SEM.
  • A focus on accessibility is reflected through limited equations, formulas, and Greek symbols to facilitate clear understanding.
  • Chapters organized around learning outcomes simplify the process of learning the concepts and statistical terms.
  • Concepts consistently defined in plain language further facilitate comprehension of methods.

Sample Materials & Chapters

Chapter 4

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