La business history est née dans les années 1920 aux Etats-Unis. Elle s’intéresse à l’histoire du monde des affaires au sens large. La business history a été initialement développée pour faire connaître aux étudiants en management les problèmes qui ont marqué le monde des affaires par le passé et les solutions mises en place pour y faire face. Les premières études en la matière portaient sur des études de cas individuelles mais Alfred Chandler a ouvert la voie vers des études historiques comparatives proposant des explications théoriques susceptibles d’expliquer la croissance des entreprises. Le périmètre d’études de la business history est large car il recouvre l’histoire des processus, acteurs, organisations, parties prenantes et contextes du management.

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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 |
- Recherche
- Logistique et Supply Chain, Transformation Digitale