POST-CONFERENCE “ADVANCED” PLS WORKSHOP
2017 Academy of Marketing Science (AMS)
Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM): Treating Observed and Unobserved Heterogeneity, Multi-Group Analysis, Invariance, and more . . .
Saturday, May 27, 2017, 9.00 am – 2.00 pm
Joe F. Hair and Marko Sarstedt
Partial Least squares is a family of regression-based methods developed in the 1970s and 1980s by the Swedish econometrician Herman O. A. Wold, who vigorously pursued the development of methods for the social sciences where “soft models and soft data” were the rule rather than the exception, and where approaches focusing on prediction would be of great value. One procedure that emerged from Wold’s efforts is partial least squares structural equation modeling (PLS-SEM), which has gained widespread popularity in a variety of disciplines such as marketing, strategic management, management information systems, and accounting.
Along with the increasing prominence of the PLS-SEM technique, researchers have started developing more advanced modeling techniques that enable them to more fully explore the roles of intervening and contingent variables and to control for data structures that pose a threat to the validity of results. The benefits of having such advanced PLS-SEM approaches readily available are tremendous, since these types of analyses assist in evaluation of PLS-SEM estimations and are increasingly being requested by editors and reviewers. At the same time, however, applying these and other advanced PLS-SEM approaches requires understanding their intricacies and knowing when they can assist in analyzing data in a meaningful way such that the applications fit the research context.
In light of these developments, this post-conference workshop provides an introduction to advanced issues in PLS-SEM, focusing on the issues of observed and unobserved heterogeneity as well as other relevant analyses. Specifically, the workshop will cover the following topics:
- Measurement invariance
- Multigroup analysis
- Identifying and treating unobserved heterogeneity (FIMIX-PLS and PLS-POS)
The course is based on their new PLS-SEM textbook:
Hair, Joe F.; Marko Sarstedt; Christian M. Ringle and Siggi P. Gudergan (2018). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM), Thousand Oaks: Sage.
Practical applications and the use of the software SmartPLS 3 are an integral part of the workshop. Each course participant will get a free two-month professional license for the SmartPLS 3 software.
Place: Hotel del Coronado, 1500 Orange Avenue, Coronado, CA 92118
Date: Saturday, May 27, 2017
Time: 9.00 am – 2.00 pm
Cost: $130 (Participants must be an active AMS member.)
Registration: Participants need to register on the AMS website. Deadline to register is May 20, 2017.
- The workshop builds on the contents and the data from the newly published book Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM) (Sage, 2017). Handouts with major concepts will be provided.
- Most of the workshop will involve “hands-on” analysis of real-world datasets using the SmartPLS 3 software. The SmartPLS 3 software output diagnostics and interpretation of the results will be covered.
- Potential obstacles and “rules-of-thumb” to ensure appropriate application of the techniques will be addressed.
- Participants should have knowledge of the fundamentals of PLS-SEM and be familiar with the basics of model development and evaluation.
- Participants must bring a laptop with the SmartPLS 3 software readily installed. The software is available from http://www.smartpls.com. If you encounter any software related problems, please create a support ticket here: http://support.smartpls.com/.
- Course participants will obtain a free two-month license for SmartPLS 3 Professional.
Who should attend? Individuals wishing to learn more advanced PLS-SEM topics and the SmartPLS software for their PhD research and/or top-tier journal publications.
Joe Hair is Distinguished Professor of Marketing, DBA Director and the Cleverdon Chair of Business in the Mitchell College of Business, University of South Alabama. He previously was Senior Scholar, DBA Program, Coles College of Business, Kennesaw State University, and prior to that held the Copeland Endowed Chair of Entrepreneurship and was Director, Entrepreneurship Institute, Ourso College of Business Administration, Louisiana State University. He has authored over 60 books, including Multivariate Data Analysis (7th edition, 2010) (cited 120,000+ times), MKTG (12th edition, 2017), Essentials of Business Research Methods (2016), and Essentials of Marketing Research (4th edition, 2017). 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 Chaired Professor of Marketing at the Otto-von-Guericke-University Magdeburg (Germany) and Conjoint Professor to the Faculty of Business and Law at the University of Newcastle (Australia). He previously was an Assistant Professor of Quantitative Methods in Marketing and Management at the Ludwig-Maximilians-University Munich (Germany). His main research is in the application and advancement of structural equation modeling methods to further the understanding of consumer behavior and to improve marketing decision making. His research has been published in journals such as Journal of Marketing Research, Journal of the Academy of Marketing Science, Organizational Research Methods, MIS Quarterly, International Journal of Research in Marketing, Long Range Planning, Journal of World Business, and Journal of Business Research. He regularly teaches doctoral seminars on multivariate statistics, structural equation modeling, and measurement worldwide.
Additional references and suggested readings:
Becker, Jan-Michael; Arun Rai; Christian M. Ringle and Franziska Völckner (2013). "Discovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats." MIS Quarterly, 37 (3), 655-694.
Hair, Joe F.; Tomas Hult; Christian M. Ringle and Marko Sarstedt (2017). A Primer on Partial Least Squares Path Modeling (PLS-SEM), 2nd edition, Thousand Oaks: Sage.
Hair, Joe F., Marko Sarstedt, Christian M. Ringle, and Jeannette A. Mena. (2012). "An Assessment of the Use of Partial Least Squares Structural Equation Modeling in Marketing Research." Journal of the Academy of Marketing Science, 40 (3): 414-433.
Hair, Joe F.; Marko Sarstedt; Lucy Matthews and Christian M. Ringle (2016). “Identifying and Treating Unobserved Heterogeneity with FIMIX-PLS: Part I – Method,“ European Business Review, 28 (1), 63-76.
Henseler, Jörg; Theo K. Dijkstra; Marko Sarstedt; Christian M. Ringle; Adamantios Diamantopoulos; Detmar W. Straub; Dave J. Ketchen; Joe F Hair; G. Tomas M. Hult and Roger J. Calantone (2014). “Common Beliefs and Reality about Partial Least Squares: Comments on Rönkkö & Evermann (2013)." Organizational Research Methods, 17 (2), 182-209.
Henseler, Jörg; Christian M. Ringle and Marko Sarstedt (2016). “Testing Measurement Invariance of Composites Using Partial Least Squares,” International Marketing Review, 33 (3), 405-431.
Matthews, Lucy; Marko Sarstedt; Joe F. Hair and Christian M. Ringe (2016). “Identifying and Treating Unobserved Heterogeneity with FIMIX-PLS: Part II – A Case Study,“ European Business Review, 28 (2), 208-224.
Specific inquiries should be directed to Marko Sarstedt at Marko.Sarstedt@ovgu.de.