Modeling of Factors Influencing the Adoption of Digital Twins Infrastructure to Support Construction Project Automation in Indonesia

Abstract

The construction industry continues to face persistent challenges related to project delays, cost overruns, low productivity, safety risks, and limited integration of digital technologies, particularly in developing countries such as Indonesia. In response to these issues, Infrastructure Digital Twins (IDTs) have emerged as an advanced digital approach capable of integrating real-time data, simulation, prediction, and optimization to support construction project automation. This study aims to develop and test an empirical model of the factors influencing IDT adoption in Indonesian construction projects by integrating technical, organizational, and external environmental perspectives. The research applies a confirmatory quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM), supported by Focus Group Discussions to validate findings and formulate strategic recommendations. The study examines constructs including digital infrastructure readiness, system interoperability, data security and quality, top management support, human resource competence, organizational readiness, regulatory support, competitive pressure, external ecosystem support, adoption intention, and adoption rate. The findings indicate that IDT adoption is shaped not only by technological readiness but also by managerial commitment, organizational capacity, regulatory alignment, and industry ecosystem support. The study concludes that successful IDT implementation requires an integrated strategy involving construction organizations, project stakeholders, and policymakers to accelerate digital transformation, strengthen data-driven decision-making, and enhance sustainable construction project automation in Indonesia.