Bridging Robotics Implementation and Operational Efficiency via Agile Management: Evidence from Commercial Residential Projects

Unlocking operational efficiency gains from construction robotics (CR) in commercial residential projects (CRPs) hinges critically on agile management rather than technology deployment alone. We propose the Construction Robotics Agile Success Model (CR-ASM), which formalizes feedback-driven, subproject-level mechanisms that convert localized CR productivity into project-wide gains. To test CR-ASM, we analyze 224 CRPs across 37 Chinese provinces using a dual-stage methodology combining partial least squares-structural equation modeling (PLS-SEM) and artificial neural networks (ANNs). Key findings reveal that time/budget/security constraints significantly compel top management commitment (β=0.723), which is the most significant driver of project success (β=0.702) through the sociotechnical capabilities of middle management. By contrast, direct CR work efficiency demonstrates a negligible influence on management commitment, positioning robotics as a catalyst rather than a direct efficiency driver. Multigroup analysis indicates core management pathways remain statistically indifferent between CR adopters and nonadopters, underscoring the primacy of agile practices. Complementary ANN results confirm project success as the overwhelming predictor of operational efficiency (57% normalized importance), validating the model's nonlinear dynamics. By bridging technology and organizational strategy, CR-ASM advances understanding of how the construction management field can achieve project-wide efficiency gains and provides an empirical foundation for future research in construction engineering and management.

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