Why Use PLS-SEM (Partial Least Square Structural Equation Modeling)

PLS-SEM is a powerful and versatile tool that is well-suited for research scenarios where traditional SEM methods may not be applicable or effective. It allows researchers to build and test complex models, even with small samples and non-normal data, making it a valuable technique in many fields of study. Here are some of the key advantages and reasons for using PLS-SEM:
1. Small Sample Sizes: PLS-SEM is particularly useful when the sample size is small relative to the number of parameters to be estimated. Unlike covariance-based SEM, which requires large sample sizes to obtain reliable results, PLS-SEM can handle smaller samples effectively.
2. Complex Models: PLS-SEM can manage complex models with many constructs, indicators, and relationships. It is suitable for models with multiple layers and hierarchical constructs, allowing researchers to explore complex theoretical frameworks.
3. Exploratory Research: PLS-SEM is ideal for exploratory research where the goal is to identify key driver constructs and develop theories. It allows researchers to build and test theoretical models even when the theoretical foundation is not well-established.
4. Formative Constructs: PLS-SEM handles formative constructs (where indicators cause the construct) effectively. Traditional SEM methods typically assume reflective constructs (where the construct causes the indicators), making PLS-SEM more versatile in certain research contexts.
5. Non-normal Data: PLS-SEM does not require data to be normally distributed, making it robust to deviations from normality. This is particularly useful in social sciences and business research where data often do not follow a normal distribution.
6. Flexibility: PLS-SEM is flexible in handling different types of data and model specifications. It can accommodate continuous, ordinal, and categorical data, as well as handle complex path models with multiple mediators and moderators.
7. Software Availability: There are several user-friendly software options available for PLS-SEM, such as SmartPLS, WarpPLS, and ADANCO, which make it accessible for researchers with varying levels of statistical expertise.