The purpose of this study is to analyze the relationships between project leadership style and performance, innovation work behavior and performance, and openness to experience and performance. A quantitative research method was employed, and the analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) via SmartPLS software version 4.0.9.9. PLS-SEM was chosen for its suitability in analyzing complex models with multiple constructs and pathways, particularly in exploratory research contexts. The study surveyed 430 SME employees, selected through snowball sampling based on the accessibility of reliable participants—those who had already completed the questionnaire. PLS-SEM is especially effective for handling small to medium sample sizes, non-normal data distributions, and both reflective and formative constructs. It also prioritizes maximizing the explained variance of dependent variables and is well-suited for testing relationships between latent constructs. A five-point Likert scale was used to measure respondents’ agreement with statements related to the variable indicators, ranging from 1 (strongly disagree) to 5 (strongly agree). The data analysis included validity testing, reliability testing, significance testing, and hypothesis testing. The results indicate that project leadership style has a positive and significant relationship with performance. Similarly, innovation work behavior and openness to experience both show positive and significant associations with performance.