Five Common Mistakes for Using Partial Least Squares Path Modeling (PLS-PM) in Management Research


  • Asyraf Afthanorhan University Sultan Zainal Abidin
  • Zainudin Awang University Sultan Zainal Abidin
  • Nazim Aimran Universiti Teknologi MARA



PLS-PM, CBSEM, Exploratory research, Structural Equation Modeling


The value of Partial Least Squares Path Modeling (PLS-PM) in management research has now been acknowledged, although the PLS-PM was developed for a reason. First, the PLS-PM was developed as an alternative to Covariance based Structural Equation Modeling (CBSEM) when exploratory research is conducted. As far as this method concerned, many researchers are misused or overuse the application of PLS-PM without understanding the basic knowledge in structural equation modeling. Thus, the purpose of this paper is to discuss the five common mistakes (data distributions, sample size limitations, unsatisfactory fitness index, misunderstanding between confirmatory and exploratory research, and poor factor loadings) for using PLS-PM over CB-SEM in management research. We concluded that the researchers should respect these methods and justify their use when conducting the research projects because some of the projects might be better for CB-SEM or PLS-PM.

Author Biographies

Asyraf Afthanorhan, University Sultan Zainal Abidin

Dr. Asyraf Afthanorhan (Corresponding author) is a lecturer at the Faculty of Business and Management, University of Sultan Zainal Abidin (UniSZA). He received PhD in Management Statistics at UniSZA in 2017. He also received a master of Science in Mathematical Sciences at the Faculty of Science and Technology, Universiti Malaysia Terengganu (UMT) in 2013. His main interest is Covariance Based Structural Equation Modeling, Partial Least Squares Path Modeling, Generalized Structured Component Analysis, Unobserved Heterogeneity Modelling and Scientific Literature Review. He is actively engaged in several Scopus journals, and most of his publications can be found in Researchgate, Google Scholar, and Scopus websites (Author ID: 5718433730). He also editor-in-chief of The Journal of Management Theory and Practice (JMTP).

Zainudin Awang, University Sultan Zainal Abidin

Dr. Zainudin Awang is a professor at  Faculty of Business and Management, Universiti Sultan Zainal Abidin (UniSZA), Kuala Terengganu. Before UniSZA, he was with UiTM since 1989. He was more than 25 years of experience lecturing in various statistical courses at the first degree as well as postgraduate level. Among the courses are regression analysis and structural equation modeling (SEM). He appointed as research consent in a few public and private organizations in the country.

Nazim Aimran, Universiti Teknologi MARA

Dr. Nazim Aimran is a Senior Lecturer at Faculty of Computer and Mathematical Sciences, UiTM. Before joining UiTM, he worked as a consultant at Frost & Sullivan, a statistician at National Population and Family Development Board Malaysia, Central Bank of Malaysia, Human Resources Development Fund Malaysia and Ministry of Human Resources Malaysia. His expertise is in Multivariate Analysis, Structural Equation Modeling (SEM) and Research Methodology, besides experience in national-level studies related to population, well-being, housing, wages, and public opinion.




How to Cite

Afthanorhan, A., Awang, Z., & Aimran, N. (2020). Five Common Mistakes for Using Partial Least Squares Path Modeling (PLS-PM) in Management Research. Contemporary Management Research, 16(4), 255–278.