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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
  • Joseph F. Hair, Jr. - Mitchell College of Business, University of South Alabama, USA
  • G. Tomas M. Hult - Michigan State University, USA
  • Christian Ringle - Hamburg University of Technology, Germany, University of Newcastle, Australia
  • Marko Sarstedt - Otto-von-Guericke University, Magdeburg, Germany, University of Newcastle, Australia
Additional resources:

March 2016 | 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

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Sample Materials & Chapters

Chapter 4

For instructors

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