题　目：Power of Waste-Aware Display Policies in Online Grocery Retail: A Unified Framework

嘉　宾：梁佳欣 助理教授 麦吉尔大学

主持人：许欢 教授 上海交通大学安泰经济与管理学院

时　间：2026年1月9日（周五）10:00-11:30

地　点：安泰楼A305室

内容简介：

With online grocery shopping rapidly becoming the norm, retailers are increasingly focused on boosting demand through optimizing product displays, specifically assortment and ranking decisions. This, however, poses several intertwined challenges, such as coordinating assortment-ranking-inventory decisions, tailoring product displays to evolving inventory, and managing quality decay across products of varying ages. Beyond these operational complexities, sustainability pressures are mounting, as policymakers push retailers to curb food waste and improve societal outcomes. In this paper, we propose a unified inventory-adaptive framework for online grocery shopping that explicitly captures these operational and environmental interdependencies. (i) We introduce a novel fluid reformulation which, although not directly equivalent to the original deterministic problem, can be systematically transformed, via a series of transformations, to recover the true optimal policy of the original deterministic formulation. (ii) We show that the fluid solution is asymptotically optimal in the stochastic system. (iii) Our proposed algorithm is computationally scalable and operationally stable (a) requiring only minimal daily adjustments to maintain a smooth shopping experience, (b) ensuring nearly uniform display lengths for consistent online operations, and (c) recovering the optimal solution in polynomial time with respect to the number of products. (iv) A full welfare analysis comparing firm profit, waste and customer surplus across different policy regimes (waste ban vs. no ban) and operational strategies (static vs. adaptive), shows that our adaptive display policies outperform static policies across all dimensions: higher profit, lower waste, and greater customer surplus, providing a win-win-win framework, a rare outcome in public policy design where trade-offs are typically inevitable. (v) Our numerical simulations further reveal that adaptive display policies can render the organic waste bans nearly redundant, or even counter-productive. In particular, with adaptive systems in place, bans yield negligible additional waste reduction while introducing inefficiencies (lower profits) or compliance burdens (increasing regulatory costs). Overall, this suggests that promoting internally adaptive policies, rather than rigid regulatory bans, can achieve superior outcomes in a more flexible, cost-effective, and scalable manner.

演讲人简介：

Alys Liang is an Assistant Professor of Operations Management at McGill University’s Desautels Faculty of Management. Her research integrates customer behaviour modelling and data-driven optimization to address challenges in sustainable retail operations, including product return management and food waste mitigation. Beyond retailing, her recent work extends these methodologies to enhance efficiency, equity, and sustainability in resource-constrained humanitarian operations, such as donor engagement and medical waste reduction. Alys obtained her PhD degree on Technology and Operations at the Stephen M. Ross School of Business, University of Michigan.

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