考虑顾客选择行为的BOPS自提门店个性化推荐  

Personalized Recommendation of BOPS Self-Pickup Store Considering Customer Choice behavior

作　　者：陈亚静 CHEN Yajing(Antai College of Economics&Management,Shanghai Jiao Tong University,Shanghai 200030,China)

机构地区：[1]上海交通大学安泰经济与管理学院,上海200030

出　　处：《上海管理科学》2024年第4期86-92,共7页Shanghai Management Science

摘　　要：针对全渠道零售中的BOPS(在线购买门店提货)模式,给出了考虑顾客选择行为的自提门店推荐方法。此方法构建了结合商圈、距离以及预计送达时长的不同收货方式下顾客的效用函数,通过MNL选择模型来刻画顾客的选择行为,建立考虑顾客选择行为的以零售商利润最大化为目标的混合整数规划模型。其次,将模型转换成易于求解器求解的混合整数二阶锥规划模型。数值实验表明本文提出的自提门店的推荐方法可提升零售商的利润。最后,探讨了预计送达时长、顾客的距离敏感度与收益的关系。数值实验结果表明,零售商的总利润与预计送达时长呈正相关关系,零售商的总利润与顾客对距离的敏感度呈负相关关系。In the context of omnichannel retail,a method for recommending self-pickup locations for customers in the BOPS(Buy Online,Pick Up in Store)model has been proposed.This method constructs utility functions for customers under different delivery options,taking into account factors such as the shopping district,distance,and estimated delivery time.Customer choice behavior is characterized using an MNL(Multinomial Logit)selection model,and a mixed-integer programming model is formulated with the objective of maximizing retailer profit while considering customer choice behavior.Furthermore,the model is transformed into a mixed-integer second-order cone programming model that is amenable to solver-based solutions.Numerical experiments demonstrate that the recommended self-pickup location method proposed in this article can enhance the retailer's profit.Finally,the relationship between estimated delivery time,customer distance sensitivity,and revenue are explored.Numerical experimental results reveal a positive correlation between the retailer’s total profit and estimated delivery time,as well as a negative correlation between the retailer’s total profit and customer sensitivity to distance.

关 键 词：全渠道零售 BOPS Multinomial Logit模型 二阶锥规划 

分 类 号：F252[经济管理—国民经济]