Recently, the focus of the international business has been shifted from a country-level to a sub-national level, with the better availability of more fine-grained data and new interdisciplinary research. Especially, “global city” has become a key topic in international business due to their superior economic performance. Their superior can be explained by 1) well-developed infrastructure attracts many different people and firms to be concentrated in a dense area, and 2) global connectivity of the global cities provides access to more opportunities and knowledge outside the metropolitan area. These two factors are very closely related. World-class firms and talented people in the metropolitan area provide more chances to be connected, both within a city and across different cities across co

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Robotic warehouses have transformed logistics, prioritizing speed and efficiency. However, traditional static priority systems often leave low-priority customers facing excessive delays, raising concerns about fairness. This research, based on Invia, a robotic warehouse company, proposes a dynamic priority allocation model to balance efficiency and fairness. By adjusting order priorities over time, this approach ensures that both high-priority and long-waiting low-priority orders receive timely fulfillment. Through stochastic modeling and simulations, we demonstrate that dynamic prioritization reduces delays compared to static and first-come, first-served (FCFS) models. Case studies in e-commerce and healthcare logistics illustrate the broader impact of fairness in automation. As industries increasingly rely on AI-driven decision-making, the balance between efficiency and equity becomes critical. This research challenges the assumption that robotic warehouses should optimize for speed alone and advocates for a future where fairness plays a central role in automated commerce.
YUAN Zhe - EMLV |
- Research
- Digital Transformation, Logistics and Supply Chain