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

The Third Edition of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) guides readers through learning and mastering the techniques of this approach. The authors use their teaching experience to communicate the fundamentals of PLS-SEM with limited emphasis on equations and and symbols, relying on straightforward language instead.

Table of Contents:
Preface About the Authors Chapter 1. An Introduction to Structural Equation Modeling Chapter Preview What Is Structural Equation Modeling? Considerations in Using Structural Equation Modeling Principles of Structural Equation Modeling PLS-SEM, CB-SEM, and Regressions Based on Sum Scores Considerations When Applying PLS-SEM Guidelines for Choosing Between PLS-SEM and CB-SEM Organization of Remaining Chapters Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 2. Specifying the Path Model and Examining Data Chapter Preview 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 Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 3. Path Model Estimation Chapter Preview Stage 4: Model Estimation and the PLS-SEM Algorithm Case Study Illustration—PLS Path Model Estimation (Stage 4) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 4. Assessing PLS-SEM Results—Part I: Evaluation of the Reflective Measurement Models Chapter Preview Overview of Stage 5: Evaluation of Measurement Models Stage 5a: Assessing Results of Reflective Measurement Models Case Study Illustration—Evaluation of the Reflective Measurement Models (Stage 5a) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 5. Assessing PLS-SEM Results—Part II: Evaluation of the Formative Measurement Models Chapter Preview Stage 5b: Assessing Results of Formative Measurement Models Case Study Illustration—Evaluation of the Formative Measurement Models (Stage 5b) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 6. Assessing PLS-SEM Results—Part III: Evaluation of the Structural Model Chapter Preview Stage 6: Structural Model Results Evaluation Case Study Illustration—Evaluation of the Structural Model (Stage 6) Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 7. Mediator and Moderator Analysis Chapter Preview Mediation Moderation Case Study Illustration—Moderation Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Chapter 8. Outlook on Advanced Methods Chapter Preview Importance-Performance Map Analysis Necessary Condition Analysis Higher-Order Constructs Confirmatory Tetrad Analysis Examining Endogeneity Treating Observed and Unobserved Heterogeneity Measurement Model Invariance Consistent PLS-SEM Summary Review Questions Critical Thinking Questions Key Terms Suggested Readings Glossary References Index

About the Author :
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 scholar in PLS-SEM and marketing, with 340,000+ citations (Google Scholar, 2023). He also has published numerous articles in scholarly journals and was recognized as the Academy of Marketing Science Marketing Educator of the year. A popular guest speaker, Professor Hair often presents seminars on research techniques, multivariate data analysis, and marketing issues for organizations in Europe, Australia, China, India, and South America. 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 Business; and he ranks in the top-10 scholars in marketing per the prestigious “world ranking of scientists.” At Michigan State University, Dr. Hult was recognized with the Beal Outstanding Faculty Award in 2019 (MSU’s highest award ”for outstanding total service to the University“), and he has also been recognized with the John Dunning AIB Service Award for outstanding service to AIB – as the longest serving Executive Director in AIB’s history (2004-2019) (the most prestigious service award given by the Academy of International Business). Professor Hult regularly teaches doctoral seminars on multivariate statistics, structural equation modeling, and hierarchical linear modeling worldwide. He is a dual citizen of Sweden and the United States. More information about Professor Hult can be found at http://www.tomashult.com. 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 Researchers List. In 2014, Ringle co-founded SmartPLS (http://www.smartpls.com), a software tool with a graphical user interface for the application of the partial least squares structural equation modeling (PLS-SEM) method. Besides supporting consultancies and international corporations, he regularly teaches doctoral seminars on business analytics and multivariate statistics, the PLS-SEM method, and the use of SmartPLS worldwide. More information about Professor Dr. Christian M. Ringle can be found at https://www.tuhh.de/hrmo/team/prof-dr-c-m-ringle.html. 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 frequently cited in the social sciences with more than 100,000 citations according to Google Scholar. Marko has won numerous best paper and citation awards, including five Emerald Citations of Excellence awards and two AMS William R. Darden Awards. Marko has been repeatedly named member of Clarivate Analytics’ Highly Cited Researchers List. In March 2022, he was awarded an honorary doctorate from Babe?-Bolyai-University Cluj-Napoca for his research achievements and contributions to international exchange.