Advanced Topics of PLS-SEM Using SmartPLS

hosted by NIT - Northern Institute of Technology Management -

Start: Thursday, 25 Nov 2021 09:00

End: Friday, 26 Nov 2021 17:00

  • Course Objectives

    Course Language: English!

    This two-day online course advances participants knowledge of state-of-the-art partial least squares structural equation modeling (PLS-SEM) using the SmartPLS 3 software. The first day of the course starts with a brief recap of the more basic and advanced model evaluation criteria and some useful additional modelling tools like IPMA, higher-order constructs and mediation. The second day will cover the assessment of data heterogeneity in different forms, i.e., observed (e.g., multi-group, moderation, non-linear effects) and unobserved (e.g., segmentation using FIMIX-PLS and PLS-POS).

    PLS-SEM 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-SEM 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.

    PLS-SEM has recently received considerable attention in a variety of disciplines, including

    • marketing (Hair et al 2011, according to Google scholar the most-cited article ever published in Journal of Marketing Theory and Practice; Hair et al. 2012a, according to Google scholar the most-cited Journal of the Academy of Marketing Science article since 2012),
    • strategic management (Hair et al. 2012b, according to Google scholar the most-cited Long Range Planning article since 2012),
    • management information systems (Ringle et al. 2012, according to Google scholar the fifth-most cited MIS Quarterly article since 2012), and
    • business administration in general (Sarstedt et al. 2016, according to Google scholar the second-most cited article published in the Journal of Business Research since 2016).

    Also, several review studies across different disciplines substantiate that PLS-SEM has become a standard method in the multivariate analysis toolbox: e.g., Higher Education (Ghasemy et al. 2020), Human Resource Management (Ringle et al., 2018), Hospitality Research (Ali et al., 2018), Information Systems Research (Hair et al., 2017), Management Accounting (Nitzl, 2016), International Business (Richter et al., 2016), Tourism (do Valle and Assaker, 2016), Psychology (Willaby et al., 2015), Supply Chain Management (Kaufmann and Gaeckler, 2015), Family Business (Sarstedt et al., 2014), Operations Management (Peng and Lai, 2012), Strategic Management (Hair et al., 2012), Marketing (Hair et al., 2012), Management Information Systems (Ringle et al., 2012), Accounting (Lee et al., 2011), and International Marketing (Henseler et al., 2009).

    Take a look at recent PLS-SEM publications!


  • Learning Outcomes

    This course has been designed to familiarize participants with the potentials of using the multivariate analysis method PLS-SEM in their research. The objectives of this course are to (1) provide advanced knowledge on the PLS-SEM approach, (2) gain insights on additional analysis methods in the PLS-SEM modelling framework that increase publication success, and (3) improve PLS-SEM modeling and analytical skills. More specifically, participants will understand the following topics:

    • Short recap on the fundamentals of PLS-SEM model evaluation
    • Importance-performance map analysis (IPMA) of PLS-SEM results
    • Higher-order constructs (e.g., second-order models)
    • Mediating effects
    • Moderating effects (interaction effects)
    • Nonlinear relationships (quadratic effects)
    • Measurement invariance testing (MICOM)
    • Multigroup analysis (MGA)
    • Segmentation and uncovering unobserved heterogeneity by FIMIX-PLS and PLS-POS

    This course continues where we left off with the Foundations of PLS-SEM using Smart-PLS course. It has been designed to advance the PLS-SEM knowledge of full-time faculty and PhD students who want to master the PLS-SEM method for their own research applications. Basic knowledge of PLS-SEM method and the nature of latent variable modeling is required.

    Participants will receive a certificate of attendance. Universities and academic institutions usually acknowledge this course with a workload of 3 ECTS.

  • Teaching and learning methods

    • The course is based on the PLS-SEM textbooks:
                                     Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. 2017. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd edition. 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.
    • Presentations: The session will cover theory and its application.
    • Computer exercises using the latest SmartPLS 3 version: Specifically, theoretical explanations underlying the software procedures and practical exercises where participants will apply their learning to real-world examples provided by the instructor.
           Course participants will receive a 90-days fully
    functional version of the software SmartPLS 3.

Short event description

This two-day course advances participants knowledge of partial least squares structural equation modeling (PLS-SEM) using the world-leading PLS-SEM software SmartPLS.


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