Partial least squares structural equation modeling (PLS-SEM) is a well-established method
that enables researchers to assess theoretical arguments and to evaluate how well theories in a
variety of research fields predict outcomes. This course provides concise instructions on how
to use this method to conduct research and obtain solutions. Topics will include an overall
introduction to PLS-SEM, specification and estimation of path models, assessments of PLSSEM
results (e.g., evaluation of reflective measurement models, of formative measurement
models, and of the structural model), and advanced PLS-SEM analyses such as mediation and
moderation analyses.

The course is suited to PhD students who pursue a deductive research approach that involves
survey-based (and other) data and path models with latent variables.

After completion this course, students will be able to apply PLS-SEM in their dissertation
projects.

Minimum attendance is 80% of course hours, giving presentations is compulsory for every
participant.

The course will rest on a selected set of readings that may include journal papers and possibly
chapters from the first, and maybe the second, of the following two books (to be determined):

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least
Squares Structural Equation Modeling (PLS-SEM), 3rd ed. Thousand Oaks, CA: Sage.

Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2018). Advanced Issues in
Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks, CA:
Sage.

In the introduction section, the course instructor will give an overview of PLS-SEM. In the
following sections, student groups discuss PLS-SEM applications on certain topics within the
course. Each group will prepare a slide deck and make it accessible to the other groups
(upload to Learn@WU).

In each of the initial presentations, groups introduce the PLS-SEM topic that they have been
assigned and illustrate its application by outlining respective step-by-step PLS-SEM
estimations drawing on their own data or on data provided by the instructor. Fellow students
provide comments on each group’s presentation. The course instructor will spur and moderate
a discussion to develop understanding about common pitfalls in the application of PLS-SEM.

In the final presentations, with a focus on each group’s data, each group will outline the use of
all PLS-SEM assessment features that have been discussed throughout the course. A
discussion following these presentations will probe the individual students’ critical
comprehension of the PLS-SEM topics covered in the course. On this basis, each group will
write and submit a report outlining their application of PLS-SEM.

To facilitate learning, students may be expected to run some analyses during some of the
sessions. Therefore, it will be assumed that students will bring their laptop/macbook to
sessions.

Initial presentation: 25%
In-class discussion: 25%
Final presentation:  25%
Written report:        25%

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siggi.gudergan@jcu.edu.au