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

Second Edition


384 pages | SAGE Publications, Inc

With applications using SmartPLS (www.smartpls.com)—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
Mediation

 
Moderation

 
 
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

 

Supplements

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

I found the book to be informative for my students.

Dr Keith Ng
The University of Waikato Joint Institute, Zhejiang University City College
October 1, 2021

WEll explained friendly

Mrs Gloria Aznar
Business Economics, San Pablo University - CEU
April 5, 2021

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
April 7, 2016

Sample Materials & Chapters

Chapter 4


Joseph F. Hair, Jr.

Joseph F. Hair, Jr.is Professor of Marketing, PhD Director, and the Cleverdon Chair of Business in the Mitchell College of Business, University of South Alabama, USA. He previously held the Copeland Endowed Chair of Entrepreneurship and was Director, Entrepreneurship Institute, Ourso College of Business Administration, Louisiana State University. He has authored over 95 books, including Multivariate Data Analysis (8th edition, 2019) (cited 170,000+ times), MKTG (13th edition, 2019), Essentials of Business Research Methods, 5th edition, 2023), and Essentials of Marketing Research (6th edition, 2023). Dr. Hair is the most highly cited... More About Author

G. T. Hult

G. Tomas M. Hult is Professor and Byington Endowed Chair at Michigan State University (USA), and holds a visiting Chaired Professorship at Leeds University Business School (United Kingdom) and a visiting professorship at Uppsala University (Sweden). Professor Hult is a member of the Expert Networks of the World Economic Forum and United Nations/UNCTAD’s World Investment Forum, and is also part of the Expert Team at the American Customer Satisfaction Index (ACSI). Dr. Hult was recognized in 2016 as the Academy of Marketing Science / CUTCO-Vector Distinguished Marketing Educator; he is an elected Fellow of the Academy of International... More About Author

Christian M. Ringle

Christian M. Ringle is Professor of Management at the Hamburg University of Technology (Germany). His research addresses management of organizations, human resource management, methods development for business analytics and their application to business research. His contributions in these fields have been published in journals such as International Journal of Research in Marketing, Information Systems Research, Journal of the Academy of Marketing Science, MIS Quarterly, Organizational Research Methods, and The International Journal of Human Resource Management. Since 2018, he has been named member of Clarivate Analytics’ Highly Cited... More About Author

Marko Sarstedt

Marko Sarstedt is Professor of Marketing at the Ludwig-Maximilians-University Munich (Germany) and an adjunct research professor at Babe?-Bolyai-University Cluj-Napoca (Romania). His main research interest is the advancement of research methods to further the understanding of consumer behavior. His research has been published in Nature Human Behaviour, Journal of Marketing Research, Journal of the Academy of Marketing Science, Multivariate Behavioral Research, Organizational Research Methods, MIS Quarterly, British Journal of Mathematical and Statistical Psychology, and Psychometrika, among others. His research ranks among the most... More About Author