AIoT-Driven Digital Twin Capability and Adaptive Supply Chain Resilience: A Cross-Sectional Study of European Industrial Ecosystems

European industrial ecosystems face growing supply chain disruptions, increasing the importance of adaptive resilience. This study examines how Artificial Intelligence of Things (AIoT)-driven digital twin capability relates to adaptive supply chain resilience (ASCR), focusing on real-time data integration, predictive analytics capability, autonomous decision support, and collaborative digital ecosystem integration. A quantitative, cross-sectional design was adopted. Data was collected through a structured five-point Likert questionnaire from 384 respondents across European industrial ecosystems. Descriptive statistics, Spearman’s rank correlation, and binary logistic regression were applied. All four capability dimensions were positively and significantly associated with resilience outcomes. Predictive analytics capability showed the strongest association with resilience, indicating that proactive risk identification and intelligent forecasting are closely linked to adaptive resilience. Because the design is cross-sectional and all measures are self-reported, the results describe associations and do not establish causal effects. The findings indicate that AIoT-enabled digital twin capabilities are relevant to resilient European industrial ecosystems. Integrated real-time data, predictive analytics, intelligent decision support, and digital collaboration are relevant to the Industry 5.0 agenda, although the design does not identify an investment sequence.