Global maritime supply chains, which facilitate over 90% of international trade, face pressure to minimise environmental impacts while increasing operational efficiency and competitiveness. Digital Twin (DT) technology (real-time virtual representations of physical systems) has emerged as a transformative enabler for sustainable port and vessel operations. While the adoption of DTs in the manufacturing and energy sectors is well-documented, their integration within maritime contexts and the associated sustainability implications remain fragmented. This paper aims to address this gap by establishing a conceptual framework for the deployment of DT in maritime supply chains, linking environmental, economic, and operational benefits to sustain-able development and marketing differentiation. The case studies of Rotter-dam, Qingdao, and Singapore demonstrate technological frameworks and their sustainability outcomes. The Singapore case, presented here for the first time, highlights the use of AI-driven DT capabilities for managing congestion and reducing carbon emissions. A comparative analysis shows that successful adoption of digital twins requires high levels of interoperability, predictive analytics, and strong collaboration among stakeholders. The sustainability benefits include significant reductions in vessel waiting times, lower emissions, decreased energy consumption, improved throughput, and cost savings. However, challenges such as data integration, cybersecurity, and the need for substantial capital investment are also discussed, along with strategies for overcoming these obstacles and identifying marketing opportunities. The paper concludes with suggestions for future research that integrates digital twins with AI, blockchain technology, and autonomous shipping. It emphasises the role of digital twins as both an operational and strategic marketing tool for fostering sustainable supply chains.