This study aims to develop a systematic understanding of a decision-making model for material selection based on Systems Engineering Management (SEM), Multicriteria Decision Making (MCDM), and Value Engineering (VE) in road infrastructure projects in Timor Leste. Given the strategic role of road infrastructure in supporting economic growth in developing countries, appropriate material selection is a critical factor influencing cost efficiency, technical performance, and project sustainability. However, current material selection practices tend to be subjective and often fail to adequately consider multidimensional aspects such as life-cycle costs and environmental impacts. Therefore, the application of MCDM- and VE-based approaches is necessary to improve the quality and objectivity of decision-making in optimal material selection. Using a scoping review methodology, this study identifies and synthesizes existing literature on the application of SEM, MCDM, and VE in infrastructure projects, with a specific focus on material selection processes. The findings reveal that although MCDM methods such as AHP, TOPSIS, and VIKOR have been widely applied in infrastructure projects, the integration of SEM, MCDM, and VE into a structured and unified decision-making system remains limited, particularly in the context of developing countries such as Timor Leste. This gap indicates a significant opportunity to develop a more comprehensive decision-support model capable of enhancing cost efficiency, material quality, and the sustainability of infrastructure projects.From a theoretical perspective, this study contributes to the engineering management literature by strengthening the conceptual integration of SEM, MCDM, and VE in infrastructure material selection decision-making. From a practical standpoint, the findings are expected to provide a valuable foundation for the Roads Fund Infrastructure Timor Leste in developing a value-based decision model to support optimal material selection in their infrastructure projects. Future research is recommended to validate the proposed model through case studies or empirical simulations to assess its effectiveness and feasibility in real-world applications.
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