PLS vs. SEM: Choosing the Right Path for Your Research
PLS vs. SEM Dr. Engr. Md. Abdur Rashid Director (Research & Publication) NAPD, Bangladesh In the research world and data analysis, researchers often face the challenge of choosing the right structural equation modeling technique. Two popular approaches a) Partial Least Squares (PLS-SEM) b) Covariance-Based SEM (CB-SEM) Both above may look similar at first glance, but they serve very different purposes. Understanding their distinctions is crucial for anyone working with complex models in social sciences, management, or governance. PLS-SEM is often described as a prediction-oriented method. It thrives in situations where the researcher’s goal is to explain variance, explore new theories, or deal with formative constructs. Because it does not rely on strict assumptions of normality, PLS-SEM is flexible and can handle smaller sample sizes and highly complex models. This makes it particularly useful in early-stage theory de...