Program Management Model for End-to-End Reverse Logistics Optimization in Cloud Infrastructure Networks
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The rapid expansion of cloud infrastructure networks has transformed global supply chain operations, yet reverse logistics processes remain fragmented and inefficient. Reverse logistics—the return, repair, recycling, or disposal of digital and physical assets—is critical in maintaining service continuity, reducing operational costs, and advancing sustainability goals. This review explores a program management model for optimizing end-to-end reverse logistics in cloud infrastructure networks. By integrating program management principles with advanced digital tools such as artificial intelligence, blockchain, and digital twins, organizations can streamline asset recovery, enhance transparency, and enable predictive decision-making. The study emphasizes the importance of cross-functional governance structures, standardized workflows, and real-time monitoring to mitigate bottlenecks across data centers, cloud hardware, and distributed service ecosystems. Key focus areas include lifecycle management of servers and networking equipment, secure data decommissioning, and sustainable recycling pathways. Additionally, the review highlights the role of performance metrics and program-level alignment in ensuring scalability and resilience. The proposed model contributes to bridging gaps between technical, environmental, and business objectives, offering a holistic approach to reverse logistics. Ultimately, this framework supports both economic efficiency and environmental stewardship in the evolving landscape of cloud infrastructure networks.
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