Online shopping satisfaction hinges on two major factors: “fairness and security.” Customers want fair pricing, transparent processes, and respectful treatment—what researchers call distributive, procedural, and interactional “justice.” When customers feel valued and protected, they’re more satisfied and less likely to complain. Data security, especially, is a critical factor, as shoppers look for “secure transactions and safe handling of personal information”. Positive experiences lead to word-of-mouth recommendations, while negative ones often result in complaints that can harm a brand’s reputation. For eCommerce, “making fairness and security a top priority is essential for customer loyalty and avoiding the complaining behaviour”. These elements build lasting relationships and promotes a strong, competitive presence in the digital market.
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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.
- Research
- Digital Transformation, Logistics and Supply Chain
