A fuzzy DEMATEL–ISM framework for unpacking barriers to digital twin adoption in high-density crowd management

Digital Twin (DT) technology promises to revolutionize the management of large gatherings by coupling physical assets with their virtual counterparts to enable real–time situational awareness. However, adoption in safety–critical crowd scenarios remains limited. This work introduces a hybrid framework combining fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) and Interpretive Structural Modeling (ISM) to systematically identify, interrelate, and prioritize the obstacles to DT deployment for hyper–dense events such as Hajj and Umrah. By embedding fuzzy logic, the method captures the vagueness and variability of expert assessments, while ISM organizes barriers into a hierarchical structure. Analysis of ten barriers (BR1–BR10) identifies the nascent stage of domain implementation (BR10) as the deepest root cause, occupying the base of the interpretive structural hierarchy and exhibiting the largest net causal effect. The shortage of specialized expertise (BR6) occupies the second hierarchical level, mediating between domain immaturity and the remaining barriers. Crowd dynamics and behavioral diversity, legacy system integration, and regulatory and governance frameworks are net causes in the DEMATEL sense but occupy the upper hierarchical level as members of a mutually reinforcing cluster. Infrastructure requirements and cost emerge as the most strongly dependent barriers, followed by resistance to change and privacy concerns. The findings invert the intervention priorities transferred from industrial digital twin deployment, where cost and infrastructure are treated as binding constraints, and provide a cause-and-effect roadmap for policymakers and technology providers.