THEORETICAL JUSTIFICATION FOR USING PLS-SEM IN PUBLIC SECTOR RESEARCH ON INNOVATIVE WORK BEHAVIOR

Abstract

This paper explores the use of Partial Least Squares Structural Equation Modeling (PLS-SEM) as a methodological approach in public sector research, specifically in studying innovative work behavior (IWB). Given the complexity of relationships within public administration, traditional regression-based methods often struggle to capture the nuances of employee behavior and organizational influences. PLS-SEM offers a flexible alternative, allowing researchers to analyze complex models, accommodate small sample sizes, and incorporate both formative and reflective constructs.  This study reviews the increasing application of PLS-SEM in public sector research and highlights its methodological advantages. By examining previous studies, the paper demonstrates how PLS-SEM has been effectively utilized to explore factors influencing innovation, employee engagement, and organizational performance in government agencies. It also discusses best practices for applying PLS-SEM, including considerations for model assessment and reporting standards. The findings suggest that PLS-SEM enhances the analytical rigor of public administration research by enabling more precise predictions and theoretical advancements. This paper advocates for its wider adoption and provides recommendations for future research, including expanding theoretical models, applying PLS-SEM across different government contexts, and improving methodological standards to strengthen empirical evidence.