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This paper is written in a standard empirical/social science research paper format (APA-inspired structure). You can use this as a template or a draft for a course assignment or methodological review. Leveraging the SmartPLS Student Version for Structural Equation Modeling: A Practical Guide for Emerging Researchers

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Partial Least Squares Structural Equation Modeling (PLS-SEM) has become a cornerstone methodology in marketing, management, and social sciences. SmartPLS is the leading software for PLS-SEM, but its full commercial license is costly for students. The SmartPLS Student Version offers a no-cost alternative. This paper evaluates the functional capabilities, technical restrictions, and pedagogical utility of the SmartPLS Student Version. We find that while limitations on sample size and the number of variables exist, the student version robustly supports core analytical algorithms (PLS, Bootstrapping, IPMA, FIMIX-PLS) necessary for bachelor’s and master’s level research. We provide a decision framework to determine when the student version is appropriate and discuss workarounds for its constraints. This paper is written in a standard empirical/social

PLS-SEM, SmartPLS, Student Version, Methodology, Research Limitations, Software Tutorial 1. Introduction Structural Equation Modeling (SEM) is a multivariate statistical technique used to analyze structural relationships between measured variables and latent constructs (Hair et al., 2019). Among SEM approaches, Partial Least Squares (PLS) is preferred for exploratory research, complex models, and non-normal data (Ringle et al., 2015). SmartPLS has emerged as the most user-friendly graphical interface for PLS-SEM. SmartPLS is the leading software for PLS-SEM, but

However, the commercial license for SmartPLS Professional is often prohibitively expensive for students (approximately $1,500–$3,000 annually). In response, SmartPLS GmbH offers a free . While accessible, the student version imposes technical restrictions that students and supervisors must understand before adopting it for thesis or dissertation work.