Resilience Analysis of EPC Project Cost Data Transmission Based on Complex Networks and Monte Carlo Simulation

Intelligent cost control in engineering, procurement, and construction (EPC) projects depends on the continuous transmission, updating, warning, correction, and reuse of cost data across multiple project stages. To analyse the resilience of this process, this study constructs an EPC project cost-data transmission network using complex network theory and Monte Carlo simulation. Eighteen core nodes and 27 directed weighted edges are identified according to EPC cost-management logic and expert evaluation. Node importance is analysed using weighted degree centrality, betweenness centrality, and PageRank, while network efficiency is used to evaluate cost-data reachability and transmission-path efficiency. Node failure, edge-weight perturbation, random edge failure, random failure and targeted attack, feedback enhancement, critical-node failure–recovery, and robustness checks are then conducted. The results show that Dynamic cost, Cost deviation warning, and Historical cost database are the three most critical nodes. Their failures reduce network efficiency by 44.54%, 37.43%, and 45.27%, respectively. Random edge failure has a stronger effect on network efficiency than edge-weight perturbation; when the edge failure probability increases from 5% to 20%, the average efficiency loss rate rises from 10.54% to 37.30%. Feedback-link enhancement increases network efficiency from 0.1858 to 0.2009 and produces a larger improvement than forward-link enhancement and random seven-edge enhancement. Robustness checks under alternative network assumptions indicate the relative stability of the critical-node identification results within the proposed network structure. The findings provide a scenario-based network perspective for identifying structurally critical nodes, vulnerable transmission links, and feedback-improvement priorities in EPC cost-data transmission. They also offer a methodological basis for future project-level calibration using BIM/5D BIM records, procurement data, cost-management platform logs, and settlement audit data.