Introduction to Basic Structural Equation Modeling (SEM) for Survey Research Using SmartPLS: A Hands-on Approach

This is a 2-day workshop that will introduce the basic use of structural equation modeling (SEM is a family of statistical models that seek to explain the relationships among multiple variables) which is the most popular analysis software at the moment. This workshop will help postgraduate students/new researchers on how to do basic analysis using the SmartPLS software and how to present them professionally. This workshop will use practical hands on approach with real research data sets with research questions that can be answered using the data available. Some useful tips on how and where to get published will be given.


  1. Lecturers and Postgraduate students in the Institutions of Higher learning.
  2. Aspiring researchers who have intention to embark on empirical research.


  1. Basics of SEM
  1. Formative vs Reflective Measurement
  1. Second Order Factors
  1. Measurement Model Evaluation
  • Convergent validity – three approaches:
  • Factor loadings.
  • Variance extracted.
  • Reliability.
  • Discriminant validity
  • Cross Loadings
  1. Structural Model analysis & evaluation
  1. Moderating Effect Analysis

    7.  Mediating Effect Analysis


Overall, PLS can be an adequate alternative to CBSEM (covariance based SEM) if the problem has the following characteristics (Chin, 1998; Chin & Newsted, 1999):

  • PLS makes fewer demands regarding sample size than other methods.
  • PLS does not require normal-distributed input data.
  • The phenomenon to be investigated is relatively new and measurement models need to be newly developed,
  • The structural equation model is complex with a large number of LVs and indicator variables,
  • Relationships between the indicators and LVs have to be modeled in different modes (i.e., formative and reflective measurement models),
  • The conditions relating to sample size, independence, or normal distribution are not met, and/or
  • Prediction is more important than parameter estimation.
  • PLS is better suited for theory development than for theory testing.


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  • DAY 1

    29th September 2019
    09.00 am    -     10.00 am Introduction and Recap Statistics           
    10.00 am -     10.30 am Coffee Break
    10.30 am -     12.45 pm Issues in SEM Modeling
    12.45 pm -     02.00 pm Lunch
    02.00 pm -     03.30 pm SEM Modeling with PLS
    03.30 pm -     04.00 pm Coffee Break
    04.00 pm -     05.00 pm          Formative versus Reflective Measurement             
  • DAY 2

    30th September 2019
    09.00 am    -     10.00 am Second Order Factors and Measurement Model Evaluation          
    10.00 am -     10.30 am Coffee Break
    10.30 am -     12.45 pm Structual Model Evaluation (First Order and Second Order)
    12.45 pm -     02.00 pm Lunch
    02.00 pm -     03.30 pm Moderating Effect Analysis
    03.30 pm -     04.00 pm Coffee Break
    04.00 pm -     05.00 pm          Mediating Effect Analysis      
Organized by
Manufacturing Technology Management (MTM) and Service & Operation Management (SOM)
Department of Production and Operations Management (JPPO),
Faculty of Technology Management and Business (FPTP)
Universiti Tun Hussein Onn Malaysia (UTHM)
Copyright © IETechS 2019 Universiti Tun Hussein Onn Malaysia UTHM