This study explores the key determinants of field engineer efficiency in the field service industry by analyzing the impact of self-efficacy, resource management, and time management on operational performance. Employing a quantitative research approach, data were collected using saturated sampling from 102 field engineers and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The measurement model showed robust psychometric properties, satisfying the thresholds for convergent validity, discriminant validity, and internal consistency reliability. The structural model results indicate that all three independent variables significantly influence field engineer efficiency. Self-efficacy was found to have the strongest effect (? = 0.421, p < 0.001), followed by resource management (? = 0.347, p < 0.001) and time management (? = 0.289, p < 0.001). The model accounts for 68.7% of the variance in field engineer efficiency, reflecting strong explanatory power and predictive accuracy. Among these variables, self-efficacy emerged as the most dominant factor, suggesting that field engineers' belief in their ability to perform tasks is a critical driver of operational success. High self-efficacy enhances motivation, resilience, and effective problem-solving under pressure, making it essential in dynamic and unpredictable field environments. Resource and time management also play crucial roles in supporting engineers' ability to complete tasks efficiently by ensuring optimal allocation of tools, equipment, and time. The findings provide practical implications for field service organizations aiming to improve workforce performance. Investing in training programs that strengthen self-efficacy, combined with systematic improvements in resource and time management practices, can significantly enhance operational outcomes. By prioritizing these factors, organizations can boost engineer efficiency, reduce operational costs, and improve service delivery, ultimately gaining a stronger competitive advantage in the industry.