A Structural Modeling Approach to Digital Twin Infrastructure Adoption for Automated Construction Projects in Indonesia

Abstract

The construction industry in Indonesia continues to face persistent structural challenges, including project delays and low productivity. Infrastructure Digital Twins (IDTs) have emerged as strategic innovations to support project automation through real-time data integration; however, their adoption remains significantly limited. This study aims to identify and model the determinants of IDTs adoption by integrating the Technology-Organization-Environment (TOE) framework and the Technology Acceptance Model (TAM). A mixed-methods sequential explanatory approach was employed, consisting of a quantitative phase involving 75 construction practitioners analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS), followed by a qualitative phase involving in-depth interviews with five industry experts to validate and contextualize the statistical results. The quantitative analysis reveals that Organizational Factors are the strongest predictors of Adoption Intention, while Technical Factors serve as essential operational prerequisites that directly influence the actual level of adoption. Although External Factors significantly trigger intention, they fail to exert a direct executive impact in the field. Furthermore, the qualitative findings demonstrate that IDTs' adoption is economically sustainable only when corporations transform from mere general contractors into integrated asset lifecycle managers. This research contributes to the Construction 4.0 literature and provides strategic managerial guidance for both government and industry stakeholders in formulating national construction digital transformation policies.