<![CDATA[Road maintenance is an important aspect of maintaining the level of service of transportation infrastructure. However, its implementation still faces various obstacles that lead to declining road quality, cost overruns, and low effectiveness of maintenance programs. This study aims to analyze the factors influencing road maintenance cost estimation and to develop a road maintenance model based on Structural Equation Modeling–Partial Least Squares (SEM-PLS). The study used a quantitative approach through a survey of 226 respondents consisting of construction service providers, supervisory consultants, and government agencies involved in road maintenance work. Data were collected using a five-point Likert-scale questionnaire and analyzed with SmartPLS. The analysis included measurement model (outer model) testing through convergent validity, discriminant validity, and construct reliability tests, as well as structural model (inner model) testing to examine the relationships among variables. The results show that all constructs met the validity and reliability criteria, with outer loading > 0.70, Average Variance Extracted (AVE) > 0.50, and Composite Reliability and Cronbach's Alpha > 0.70. Structural model testing shows that material and equipment costs, labor, traffic conditions, planning/design quality, drainage conditions, and external factors have a significant effect on road maintenance cost estimation, with maintenance strategy acting as a mediating variable. The resulting model is expected to serve as a basis for decision-making in formulating more effective, efficient, and sustainable road maintenance strategies. The findings are expected to serve as a reference for local governments and road managers in improving the quality of data-driven decision-making in road maintenance programs]]>
