Conceptual framework for ship-from-hub and ship-from-spoke fulfillment strategies to reduce cycle time

Authors

  • Oladipupo Fasawe Google LLC, USA
  • Opeyemi Morenike Filani Proburg Ltd, Lagos, Nigeria
  • Christiana Onyinyechi Makata The Dove and Flies Continental Limited, Nigeria

DOI:

https://doi.org/10.51594/gjabr.v3i10.167

Abstract

The increasing complexity of e-commerce and global supply chains has intensified the need for efficient fulfillment strategies that reduce cycle time while maintaining service quality. Traditional hub-and-spoke distribution models have evolved into more dynamic configurations, with ship-from-hub and ship-from-spoke strategies emerging as critical levers for responsiveness and cost optimization. This review paper develops a conceptual framework for analyzing and comparing these fulfillment strategies, emphasizing their role in reducing cycle time across diverse market environments. The ship-from-hub approach leverages centralized inventory consolidation, enabling economies of scale but often at the expense of longer delivery lead times. Conversely, ship-from-spoke models decentralize fulfillment through local or regional nodes, allowing faster last-mile delivery while increasing inventory management complexity. The paper synthesizes theoretical models, industry practices, and case examples to identify trade-offs in efficiency, agility, and sustainability. It further explores enabling technologies, including predictive analytics, warehouse automation, and digital twin modeling, which enhance decision-making in both hub and spoke networks. By outlining a structured framework, this study provides scholars and practitioners with insights into how hybrid strategies can be designed to balance cost, speed, and resilience. The findings highlight the importance of adaptive fulfillment models in addressing growing consumer expectations and volatile supply chain conditions.

Keywords: Fulfillment Strategies, Ship-from-Hub, Ship-from-Spoke, Cycle Time Reduction, Supply Chain Agility, Distribution Network Optimization.

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Published

14-10-2025 — Updated on 18-10-2025

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Articles