摘要
针对策略型消费者,考虑时尚服装销售周期中的新品上市和打折销售两个阶段,以及线上零售商提供体验服务的情形,研究线上时尚服装零售商的动态定价和服务决策。通过分析消费者对不同阶段时尚服装功能价值和时尚价值的估值,建立相应的消费者效用函数和需求函数以及零售商利润函数模型;通过Lagrange函数,利用KKT(Karush-Kuhn-Tucher)条件和逆向求解法得到时尚服装线上零售商的最优服务水平和销售价格。通过算例仿真,证实了模型的合理性。研究结果表明,当时尚服装的功能价值敏感系数、时尚价值敏感系数、体验服务成本系数、打折促销期折扣满足一定条件时,线上零售商可在控制订购成本的同时,通过调整两阶段的服装售价和新品上市期的最优服务水平,实现收益的最大化。
This paper focuses on the strategic customer,considers the two stages of fashion apparel sales cycle,i.e.,new arrivals and discount sales,as well as the experiential service provided by online fashion retailers,to explore the dynamic pricing and service decision-making of online fashion apparel retailers.By analyzing the consumers'valuation of the functional value and fashion value of fashion apparel products at two stages,the corresponding consumer utility function,demand function and retailer profit function models were established.Then the Lagrange function was used to obtain the best service level and pricing decision-making of online retailers through the KKT(Karush-Kuhn-Tucker)condition and inverse solution method.The rationality of the model was verified using the numerical simulation.The results show that when the functional value sensitivity coefficient,fashion value sensitivity coefficient,experience service cost coefficient and price discount of fashion clothing meet certain conditions,online clothing retailers can achieve the expected revenue maximization through adjusting the clothing price at the two stages and providing the optimal service for the new arrivals while controlling the ordering cost.
作者
徐琪
赵婉
XU Qi;ZHAO Wan(Glorious Sun School of Business and Management,Donghua University,Shanghai 200051,China)
出处
《东华大学学报（自然科学版）》
CAS
北大核心
2020年第5期810-818,共9页
Journal of Donghua University(Natural Science)
基金
国家自然科学基金资助项目(71572033)
国家自然科学基金重点资助项目(71832001)。
关键词
时尚服装
线上零售商
体验服务
策略型消费者
动态定价
fashion apparel
online retailer
experiential service
strategic customer
dynamic pricing
