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

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

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

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Written with those with limited mathematical and statistical knowledge in mind, this concise and practical guide helps researchers to do their research in new and alternative ways.

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

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

The authors explain the statistical modeling technique and the fundamental aspects of the methods in a straightforward manner that is accessible to individuals with limited statistical and mathematical training. They clarify the nature and role of PLS-SEM in social sciences research that allows researchers to pursue research in new and different ways. In order to facilitate learning, a single case study has been used throughout the book.

Changes in the 2nd edition include:

  • an overview of the latest research on composite-based modelling
  • more coverage of the distinction between PLS-SEM and CB-SEM
  • introduction of a new criterion for discrimination validity assessment
  • revision and extension of the chapter on mediation
  • extended description of moderation
  • a brief introduction to some more advanced techniques

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

"A text that students will find easy to read and enjoyable." -- Toni M. Somers

About Joe Hair

Joseph F. Hair, Jr. is Cleverdon Chair of Business, and Director of the PhD Degree in Business Administration, Mitchell College of Business, University of South Alabama. He previously held the Copeland Endowed Chair of Entrepreneurship and was Director, Entrepreneurship Institute, Ourso College of Business Administration, Louisiana State University. Joe was recognized by Clarivate Analytics in 2018, 2019 and 2020 for being in the top 1% globally of all Business and Economics professors based on his citations and scholarly accomplishments, which exceed 238,000 over his career. He has authored more than 75 books, including Multivariate Data Analysis (8th edition, 2019) (cited 140,000+ times), MKTG (13th edition, 2020), Essentials of Business Research Methods (2020), and Essentials of Marketing Research (4th edition, 2020). 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. He has a new book on Marketing Analytics, forthcoming in 2021 (McGraw-Hill). 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 Christian M. Ringle is a chaired Professor of Management at the Hamburg University of Technology (Germany) and an Adjunct Professor at the University of Waikato (New Zealand). 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, Professor Ringle co-founded 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. More information about Professor Christian M. Ringle can be found at Marko Sarstedt is a chaired Professor of Marketing at the Otto-von-Guericke-University Magdeburg (Germany) and an Adjunct Professor at Babe?-Bolyai University, Romania. His main research interest is the advancement of research methods to enhance the understanding of consumer behavior. His research has been published in Nature Human Behavior, Journal of Marketing Research, Journal of the Academy of Marketing Science, Multivariate Behavioral Research, Organizational Research Methods, MIS Quarterly, and Psychometrika, among others. His research ranks among the most frequently cited in the social sciences with more than 70,000 citations according to Google Scholar. Professor Sarstedt has won numerous best paper and citation awards, including five Emerald Citations of Excellence awards and two AMS William R. Darden Awards. According to the 2020 F.A.Z. ranking, he is the second most influential researcher in Germany, Austria, and Switzerland. Professor Sarstedt has been named member of Clarivate Analytics' Highly Cited Researchers List, which includes the "world's most impactful scientific researchers."

Table of Contents

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

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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) by Joe Hair
Used - Very Good
SAGE Publications Inc
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

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