Book on Advanced Issues in PLS-SEM
Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM) (2e)
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. 2024. Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM) (2e). Thousand Oaks, CA: Sage.

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

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Brief Description

Written as an extension of [A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)](/documentation/getting-started/pls-sem-book), this easy-to-understand, practical guide covers advanced content on PLS-SEM to help students and researchers apply techniques to research problems and accurately interpret results. The book provides a brief overview of basic concepts before moving to the more advanced material. Offering extensive examples on SmartPLS software and accompanied by free downloadable data sets, the book emphasizes that any advanced PLS-SEM approach should be carefully applied to ensure that it fits the appropriate research context and the data characteristics that underpin the research.

Key Features:

  • Coverage of advanced concepts demonstrates the PLS-SEM method as a viable alternative to the more popular CB-SEM approach and clearly shows students and researchers how they can apply the techniques to their research problems and accurately interpret the results.
  • Limited use of formulas, equations, Greek symbols, and similar notations makes it easy to understand concepts.
  • Rules of Thumb in every chapter provide practical guidelines on best practices in applying and interpreting PLS-SEM and in preparing manuscripts for publication in peer-reviewed journals.
  • The same case and database is used throughout the book to facilitate consistency in the issues associated with the case.
  • Free online resources include downloadable data sets and SmartPLS projects to practice techniques covered.

Brief Table of Contents

Chapter 1: An Overview of Recent and Emerging Developments in PLS-SEM

  • Origins and Evolution of PLS-SEM
  • Model Specification
  • Model Estimation
  • Case Study Illustration

Chapter 2: Higher-Order Constructs

  • Terminology and Motivation
  • Types of Higher-Order Constructs
  • Specifying Higher-Order Constructs
  • Estimating Higher-Order Constructs
  • Validating Higher-Order Constructs
  • Case Study Illustration

Chapter 3: Advanced Modeling and Model Assessment

  • Nonlinear Relationships
  • Confirmatory Tetrad Analysis (CTA-PLS)
  • Case Study Illustrations

Chapter 4: Advanced Results Illustration

  • Necessary Conditions Analysis (NCA)
  • Importance-Performance Map Analysis (IPMA)
  • Case Study Illustrations

Chapter 5: Modeling Observed Heterogeneity

  • Testing for Measurement Model Invariance
  • Parametric Multigroup Analysis (Parameteric MGA)
  • Bootstrap Multigroup Analysis (Bootstrap MGA)
  • Permutation Test (Permutation MGA)
  • Comparing More Than Two Groups
  • Case Study Illustration

Chapter 6: Modeling Unobserved Heterogeneity

  • Finite Mixture Partial Least Squares (FIMIX-PLS)
  • Prediction-oriented Segmentation for Partial Least Squares (PLS-POS)
  • Case Study Illustration

The Authors

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. He previously held the Copeland Endowed Chair of Entrepreneurship and was director of the Entrepreneurship Institute, Ourso College of Business Administration, Louisiana State University. He has authored over 95 books, including Multivariate Data Analysis (8th ed., 2019; cited 170,000+ times), MKTG (13th ed., 2019), Essentials of Business Research Methods (5th ed., 2023), and Essentials of Marketing Research (6th ed., 2023). 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.

Marko Sarstedt is professor of marketing at the Ludwig Maximilians University of Munich (Germany) and an adjunct research professor at Babeș-Bolyai University at 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 150,000 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 a member of Clarivate Analytics’ Highly Cited Researchers List. In March 2022, he was awarded an honorary doctorate from Babeș-Bolyai University for his research achievements and contributions to international exchange.

Christian M. Ringle is professor of management at the Hamburg University of Technology (Germany). His research focuses on management and marketing topics, method development, business analytics, machine learning, and the application of business research methods to decision making. His research contributions 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 cofounded SmartPLS, 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.

Siegfried P. Gudergan is professor of strategy within James Cook University in Australia. He also is a visiting distinguished professor at Aalto University in Finland, visiting professor at Vienna University of Economics and Business (WU Wien) in Austria, and emeritus professor at the University of Waikato in New Zealand. He holds a PhD in management from the Australian Graduate School of Management that was awarded by both the University of Sydney and the University of New South Wales in Australia, and a degree in business and economics from RWTH-Aachen University in Germany. His research has been published in leading management, strategy, and marketing journals, and is recognized internationally. Some of his PhD students have won awards from the Academy of Management and Strategic Management Society. He has various board and professional roles, and has consulted or worked with numerous organizations, including start-ups and large multinational companies.