供应链
采购
业务
私人信息检索
说服
完美信息
报童模式
微观经济学
规划师
背景(考古学)
贝叶斯推理
社会规划师
利润(经济学)
稳健性(进化)
供应链管理
信息不对称
期望效用假设
计算机科学
库存管理
贝叶斯概率
消费者行为
不完美的
理性
经济
社会成本
激励
营销
风险分析(工程)
最优决策
消费者选择
运筹学
决策模型
库存控制
情境伦理学
相关性(法律)
作者
Tianqi Song,Biying Shou,Pengfei Guo
标识
DOI:10.1177/10591478261480296
摘要
We consider the information design and inventory management problem in the context of consumer stockpiling under supply chain disruption risk. Employing a Bayesian persuasion framework, we characterize consumers’ rational stockpiling behavior and examine the strategic information disclosure of a profit-maximizing retailer versus a welfare-maximizing social planner. Our analysis reveals that when the disruption risk is low, retailers may deliberately induce mild stockpiling to shift holding costs onto consumers, increasing profit at the expense of customers’ utility. By contrast, when disruption risk is high, proper information design can curb excessive stockpiling, yielding a win-win outcome for both the retailer and customers. We further analyze the joint optimization of inventory and information design, deriving optimal strategies for both the retailer and the social planner. Compared to the retailer, the social planner orders more inventory and allocates holding costs more efficiently, which systematically improves consumer welfare. We also consider several extensions to better capture real-world complexities. Specifically, we incorporate boundedly rational customers to examine cascading behaviors, analyze settings where the retailer possesses imperfect private information, and explore cases with alternative assumptions on purchasing behavior and different decision sequences. These extensions demonstrate the robustness of our main results and highlight the practical relevance of our insights. Overall, our research deepens the understanding of the drivers of stockpiling behavior and provides actionable guidance for retailers and policymakers on managing information disclosure and inventory decisions during supply chain disruptions.
科研通智能强力驱动
Strongly Powered by AbleSci AI