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

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

Dr. Joe Hair is Founder and Senior Scholar of the Doctoral Degree in Business Administration, Coles College, Kennesaw State University, 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 40 books, including Multivariate Data Analysis, Prentice-Hall, 7th edition, 2010 (cited 22,000+ times); Marketing, South-Western Publishing Company, 12th edition 2012; Essentials of Business Research Methods, M.E. Sharpe, 2011; Research Methods for Business, Wiley, 2007; and Essentials of Marketing Research, McGraw-Hill/Irwin, 3rd edition 2013. He also has published numerous articles in scholarly journals such as the Journal of Marketing Research, Journal of Academy of Marketing Science, Journal of Business/Chicago, Journal of Advertising Research, Journal of Business Research, Journal of Long Range Planning, Journal of Marketing Theory and Practice, International Marketing Review, Journal of Experimental Education, Business Horizons, Journal of Retailing, Multivariate Behavioral Research, and others. He was recognized as the 2011 Academy of Marketing Science Marketing Educator of the year. He often presents seminars on research techniques, multivariate data analysis and marketing issues for organizations in Europe, Australia and other locations outside the U.S.