Abstract: The global construction industry confronts the intersecting imperatives of digital transformation and environmental sustainability, with concrete supply chains representing a critical nexus where material carbon intensity, equipment fleet management, and logistics coordination converge. Despite substantial advances in low-carbon concrete technology, construction equipment optimization, and digital systems such as artificial intelligence, the Internet of Things, and building information modeling, these domains have developed in relative isolation. The empirical validation employed a one-way factorial experimental design with three treatment levels, comprising Baseline Sequential Optimization, Static Integrated Optimization, and Dynamic IoT-Informed Integrated Optimization, each executed across thirty independent stochastic replications. Statistical analysis using hyper volume indicators, Mann-Whitney U tests with Bonferroni correction, and Kruskal-Wallis tests with Dunn’s post-hoc comparisons revealed that the Dynamic Integrated condition achieved a mean hyper volume of 0.859, representing a statistically significant improvement of 33.6 percent over the Baseline condition and 10.0 percent over the Static Integrated condition. Disaggregated performance metrics demonstrated a mean cost reduction of 16.7 percent, a mean carbon emissions reduction of 15.7 percent, and a mean schedule deviation reduction of 53.8 percent for the Dynamic condition relative to Baseline. The Dynamic condition reduced rejected concrete loads from a mean of 8.4 to 1.6 per simulation run and virtually eliminated the logistics performance differential between theologically challenging and forgiving low-carbon mixes, demonstrating that real-time sensor feedback serves as a technological equalizer, enabling the safe deployment of carbon-ambitious formulations. Sensitivity analyses confirmed that the value proposition of the dynamic framework is maximized under conditions of high traffic congestion, reduced equipment reliability, and elevated material variability. TOPSIS multi-criteria decision analysis demonstrated that Dynamic Integrated solutions achieved the highest closeness coefficients across cost-prioritizing, carbon-prioritizing, and balanced stakeholder weighting scenarios. Expert panel validation identified contractual and procurement structure modification as the principal adoption barrier, with a mean rating of 4.67 on a five-point scale, underscoring that the remaining challenges are institutional rather than technological. The research contributes an empirically validated architectural synthesis that bridges low-carbon material science, equipment fleet management, and digital construction technologies, providing a pre-commercial decision-support prototype and an evidence-based implementation roadmap for achieving simultaneous cost, carbon, and schedule performance improvements in complex urban construction projects.
Dizaji* et al. (Thu,) studied this question.