Structural Equation Model (SEM)-Based Productivity Evaluation for Digitalization of Construction Supervision

The construction industry continues to face declining productivity due to its heavy reliance on labor and the repetitive, non-value-adding nature of supervision tasks. This study provides an exploratory, practitioner-based evaluation of how selected digital technologies, PDF-based documentation systems, object recognition algorithms, and 3D vision technology may contribute to productivity improvements in construction supervision. A total of 82 valid responses from field engineers were collected to examine perceived task substitution effects across major construction work types and management functions. The findings indicate that higher work-adoption rates of digital technologies are generally associated with improved supervisory productivity, with the strongest perceived benefits observed for PDF-based documentation in reinforced concrete and formwork tasks. However, other expected relationships, particularly those involving work responsibility, did not appear consistently in the practitioner data, suggesting that such perceptions may be influenced by task context and adaptation burden. This study offers a practical and context-specific framework for understanding how digital tools may support productivity enhancement in supervision work. While the results reflect tendencies based on a limited sample, they provide field-grounded insights that can inform the phased and targeted application of digital technologies in construction supervision and guide future empirical model development.