Digital Twin Technology, Predictive Analytics, and Sustainable Project Management in Global Supply Chains for Risk Mitigation, Optimization, and Carbon Footprint Reduction through Green Initiatives
Joy Onma Enyejo, Ololade Peter Fajana, Irene Sele Jok, Chidimma Judith Ihejirika, Babatunde Olusola Awotiwon, Toyosi Motilola Olola
Abstract
This review explores the integration of digital twin technology, predictive analytics, and sustainable project management to enhance global supply chain efficiency, resilience, and environmental sustainability. Digital twins provide real-time virtual representations of physical supply chain systems, enabling predictive analytics to identify potential disruptions and optimize decision-making processes. By combining these advanced technologies with sustainable project management practices, such as circular supply chains and green logistics, organizations can proactively address risks while reducing their carbon footprint. The focus on data- driven insights and scenario analysis facilitates informed risk mitigation and resource optimization. The integration of frameworks like the Triple Bottom Line emphasizes the importance of balancing economic, social, and environmental objectives in project management. This approach aims to improve supply chain performance, drive sustainability efforts, and create a resilient logistics network that adapts effectively to market uncertainties and environmental challenges.