Papers

Papers Logistics & Transportation Networks

Digital Transformation: A Thematic Review and Future Research Opportunities

This paper provides a comprehensive review of digital transformation, synthesizing 58 peer-reviewed studies and integrating insights from technological disruption and corporate entrepreneurship. The study identifies nine core themes within two aggregate dimensions—technology and actor—highlighting the importance of an integrated approach to digital transformation.

2026-09-16

Papers Logistics & Transportation Networks

Network Mode Optimization Tool Increases DHL’s Profits by More Than 15%

Dang, Singh, and Allen developed the Network Mode Optimization Tool (NMOT) to address the Vehicle Routing Problem with Time Regulations and Common Carriers (VRPTRCC) for DHL Supply Chain. The tool, which uses ant-colony optimization (ACO), has significantly reduced transportation costs, improved bidding processes, and increased profits by more than 15%.

2026-09-12

Papers Logistics & Transportation Networks

Transaction Cost Economics: The Governance of Contractual Relations

Oliver E. Williamson's Nobel lecture on transaction cost economics (TCE) addresses the fundamental question of why and when firms choose to produce goods or services internally rather than outsourcing them. This paper delves into the historical context, the shortcomings of prior approaches, and the industry context of supply chain and AI decision-making.

2026-08-29

Papers Logistics & Transportation Networks

Deep Reinforcement Learning Enhances Demand-Driven Services in Logistics and Transportation

The paper "Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey" by Zefang Zong, Jingwei Wang, et al. explores the application of deep reinforcement learning (DRL) to improve demand-driven services (DDS) such as on-demand delivery, ridesharing, express systems, and warehousing. The authors highlight the challenges in managing these services and how DRL can provide more flexible and efficient solutions compared to traditional methods.

2026-08-16