需求学习下考虑顾客策略行为的供应链决策

doi:10.16381/j.cnki.issn1003-207x.2015.04.011

摘要/Abstract

摘要： 顾客策略行为对企业的经营绩效带来了巨大的负面影响, 本文基于供应链背景, 探讨需求学习应对顾客策略行为的作用与价值。构建了由单一制造商、单一零售商和一组顾客群组成的两周期分散式供应链系统的博弈模型, 将顾客划分为短视型和策略型两种类型。采用数理模型和数值分析, 研究了需求学习对于供应链的定价决策、订货决策及整体绩效的影响, 得到如下主要研究结论:第一, 无论面对何种类型的顾客, 零售商均偏好需求学习获取需求更新信息;第二, 面对短视顾客时, 制造商偏好于不获取更新信息, 而当顾客为策略型时, 制造商偏好于获取更新信息;第三, 需求学习有助于提高零售商和供应链系统的利润, 特别当面对策略型顾客时, 需求学习带来的利润增值更大。以上研究结论表明, 需求学习可以有效地缓解顾客策略行为的负面影响, 提高企业的运营绩效。

关键词: 顾客策略行为, 需求学习, 供应链, 斯坦尔伯格博弈

Abstract: Strategic customer behavior is verified to bring about great impacts on firms' profits. The value of demand learning on the strategic customer behavior is discussed by formulating a game model of a two-period decentralized supply chain consisting of one manufacturer, one retailer and a group of customers, in which customers are divided into two types:myopic customer and strategic customer. The impacts of demand learning on pricing and order policies as well as the whole performance of the supply chain are analyzed by mathematical models and numerical studies. The main results are as follows:Firstly, the retailer always prefers to gain demand update information no matter what types of customers are. In addition, the manufacturer does not prefer to gain demand update information when selling to myopic customers while prefers to gain demand update information when selling to strategic customers. Finally, demand learning helps to improve both the retailer's profit and the supply chain's profit, especially, when customers are strategic, supply chain's profit is enhanced more greatly by demand learning. In summary, a conclusion can be drawed that demand learning can reduce negative impacts from the strategic customer behavior and improve firms' performance effectively.

Key words: strategic customer behavior, demand learning, supply chain, stackelberg game

中图分类号:

F273

申成霖, 张新鑫, 侯文华. 需求学习下考虑顾客策略行为的供应链决策[J]. 中国管理科学, 2015, 23(4): 86-95.

SHEN Cheng-lin, ZHANG Xin-xin, HOU Wen-hua. Supply Chain Decision Considering Strategic Customer Behavior under Demand Learning[J]. Chinese Journal of Management Science, 2015, 23(4): 86-95.

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