Data-Driven Decision Support for Construction Method Selection in Linear Infrastructure Projects: A Systematic Review

Abstract: The selection of construction methods is a critical factor in linear infrastructure projects, yet current practice remains largely experience-driven. As is evident from the extant literature, multi-criteria decision-making, rule-based and algorithmic approaches are applied to support method selection. The present systematic literature review analyses these approaches with respect to input parameters, output structures and validation strategies. The findings indicate a predominance of project-level ranking models and limited spatial resolution. Key deficiencies identified include inadequate scalability, deficient integration of costs and restricted applicability to corridor-scale decision-making. The review identifies these gaps as central challenges for future data-driven decision-support systems.