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Partial Least Squares Structural Equation Modeling (PLS-SEM): Advanced Modeling and Model Assessment

24 September 2019
RW I, S 57

Time: 9:00am - 5:00pm

Trainer: Prof. Dr. Marko Sarstedt
Language: English
Registration: until 10 September 2019
for doctoral candidates via BayDOC: https://baydoc.uni-bayreuth.de

Partial least squares structural equation modeling (PLS-SEM) has recently received considerable attention in a variety of disciplines, including marketing, strategic management, management information systems, and many more. PLS is a composite-based approach to SEM, which aims at maximizing the explained variance of dependent constructs in the path model. Compared to other SEM techniques, PLS allows researchers to estimate very complex models with many constructs and indicator variables. Furthermore, PLS-SEM allows to estimate reflective and formative constructs and generally
offers much flexibility in terms of data requirements.

This one-day workshop focuses on recent advances in PLS-SEM. Specifically, the workshop will cover new model assessment criteria that assist researchers in adequately evaluating their results. In addition, the workshop will deal with several advanced modeling techniques that allow testing more complex model structures.

The course will cover the following state-of-theart topics:

  • Prediction-oriented model assessment of PLS-SEM results using PLSpredict
  • Model comparisons
  • Higher-order constructs
  • Mediation
  • Moderation (including an outlook on multigroup analysis)

Qualification objectives

This workshop is designed to familiarize with the potentials of using PLS-SEM in business research. The objectives of this course are to provide a methodological introduction into recent advances in modeling and model evaluation. More specifically, participants will understand the following topics:

  • How to use PLSpredict to assess a model’s predictive power
  • How to compare different models in PLS-SEM
  • How to establish and validate higher-order constructs
  • How to assess mediating effects
  • How to implement and assess moderating effects
  • Outlook on related topics such as multigroup analysis, measurement invariance assessment, and latent class analysis

This course has been designed for PhD students who are interested in learning how to use advanced PLS-SEM methods in their own research applications. Participants should have been exposed to the PLS-SEM method and the SmartPLS software.


Marko Sarstedt is a Chaired Professor of Marketing at the Otto-von-Guericke-University Magdeburg (Germany) and Adjunct Professor at the Monash University Malaysia (Malaysia) His main research interests are in the advancement of research methods to further the understanding of consumer behavior. His research has been published in, for example, Journal of Marketing Research, Journal of the Academy of Marketing Science, International Journal of Research in Marketing, Organizational Research Methods, Multivariate Behavioral Research, Decision Sciences, MIS Quarterly, Journal of Business Research, Journal of World Business, Marketing Letters, and Long Range Planning.

Marko has co-edited several special issues of leading journals and co-authored four widely adopted textbooks, including “A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)” (together with Joe F. Hair, G. Tomas M. Hult, and Christian M. Ringle). Marko’s works have been awarded with several citation and best paper awards. According to the 2018 F.A.Z. ranking, he is among the three most influential economists in the category research. He has recently been included in the Clarivate Analytics’ Highly Cited Researchers list. Additional information: http://www.marketing.ovgu.de

Verantwortlich für die Redaktion: Eva Querengässer

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