The purpose of this study is to analyze the relationships between Project management leadership pattern and performance, innovation work behavior and performance, and receptiveness to innovation and performance. A quantitative research method was employed, and the analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) via Smart PLS 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 289 Gulf project-based companies, selected through snowball sampling based on the accessibility of reliable participants who had already completed the questionnaire. PLS-SEM is especially effective for handling different 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 management leadership pattern has a positive and significant relationship with performance. Similarly, innovation work behavior and receptiveness to innovation both show positive and significant associations with performance.