When Does AI Capability Pay Off? Absorptive Capacity, Supply Chain Visibility, and Resilience in Construction

Abstract

This study examines how digital twin adoption influences supply chain performance and supply chain resilience while investigating the mechanisms and boundary conditions underlying these relationships. Specifically, the study examines AI-driven supply chain capability and supply chain visibility as mediators and absorptive capacity as a moderator. A quantitative cross-sectional survey design was employed to collect data from supply chain professionals. A total of 350 questionnaires were distributed, yielding 279 usable responses and a response rate of 79.71%. Measurement scales were adopted and adapted from established previous research. The data were analyzed using ADANCO through partial least squares structural equation modeling to assess reliability, validity, direct effects, mediation, and moderation. The findings demonstrate that digital twin adoption positively influences supply chain performance, supply chain resilience, AI-driven supply chain capability, and supply chain visibility. AI-driven supply chain capability and supply chain visibility significantly enhance both performance and resilience and mediate the relationships between digital twin adoption and the two outcomes. Absorptive capacity positively strengthens the relationships between digital twin adoption and both supply chain performance and resilience. This study extends digital supply chain research by integrating technological, informational, analytical, and knowledge-based capabilities within a unified framework. Drawing on dynamic capability theory, it demonstrates how digital twin adoption generates supply chain benefits through complementary capabilities and under varying levels of absorptive capacity. The findings provide managers with guidance for developing integrated digital transformation strategies.