Digital Twins for Sustainable and Low-Carbon Supply Chains in Industry X.0: Crossing the Fragmented Bridge Between Academic Research and Industrial Adoption

Abstract

Digital twins (DTs) offer transformative potential for shaping low-carbon, resilient, and circular supply chains by providing real-time virtual monitoring and decision-support capabilities. However, despite growing theoretical interest in technology-driven frameworks, translations into scalable, standards-aligned industrial implementations remain limited. To address this gap, we conducted a comprehensive bibliometric and thematic analysis of 229 DT-related research articles published between late 2019 and mid-2025, focusing on sustainability outcomes. The dataset was systematically compiled from three major academic databases, Scopus, ScienceDirect, and Web of Science, which ensured both consistency and robustness of the review. We mapped trends across research themes, geographies, and journal outlets and identified key clusters spanning AI-powered optimization, circular-economy frameworks, and built-environment lifecycle modeling. Our findings reveal that, although nearly 40% of studies are conceptual, only one-third present practical deployment and fewer than 30% adopt a mixed approach. Critically, interoperability standards (for example, ISO 23247 and OPC UA) and lifecycle metrics (Scope 3 emissions, LCA, Digital Product Passports) are seldom fully integrated within empirical work. This fragmentation underscores a bridge in progress between academic innovation and industrial practice. We conclude by highlighting opportunities to accelerate adoption, namely, designing DTs that are empirically validated, multi-objective, and grounded in stakeholder ecosystems, which would enable DTs to evolve from theoretical promise to operational tools for sustainable supply network transformation.