A phase-based analytic hierarchy process–decision–making trial and evaluation laboratory approach for prioritizing building information modelling–enabled digital transformation criteria in geotechnical projects: the case of Türkiye

Abstract

Building information modelling (BIM) has become increasingly important for Türkiye's large-scale geotechnical projects; however, its adoption remains limited owing to inconsistent data-sharing standards, varying organizational readiness and challenges in integrating geological and geotechnical models into design environments. To address this issue, a four-stage decision support framework was developed using the analytic hierarchy process and the decision-making trial and evaluation laboratory (DEMATEL) methods to determine the relative importance and perceived causal-influence roles of criteria associated with BIM-enabled digital transformation in geotechnical projects in Türkiye. Expert evaluations show that adoption level holds the highest importance in the initial stage. In the planning and implementation stages, the importance of data compatibility (weights = 0.31) and technical feasibility (weights ranging from 0.29 to 0.31) increases. In the integration stage, sustainability impact has the highest importance (weight = 0.30). The DEMATEL results indicate that adoption capacity is the main cause factor in the initial stage (D−R = +1.24), while sustainability impact becomes the primary cause factor in the integration stage (D−R = +0.88). Moving beyond static prioritization, the unique value of this study lies in conceptualizing geotechnical digital transformation as a dynamic causal network. It demonstrates how criteria shift from organizational enablers to sustainability drivers, providing a quantified roadmap for engineering management. The four-phase structure is employed as an analytical guide rather than a generalizable transformation sequence, and the reported weights and cause–effect patterns represent the exploratory, aggregated judgments of a six-member expert panel; they are specific to the Türkiye context and should be read as expert-derived indications rather than stable, generalizable sector-wide measurements.