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在负信用期允许情况下供应商最优信用期决策
引用本文:郑锦川,刘会,唐燕. 在负信用期允许情况下供应商最优信用期决策[J]. 物流科技, 2008, 31(9): 127-131
作者姓名:郑锦川  刘会  唐燕
作者单位:复旦大学,上海,200433
摘    要:
在许多采购活动中,买家被允许经过一段时间后再付货款,而在这段时间内买家并不需要支付任何利息费用.这段时间被称为信用期(credit period)。国内外有许多关于这个问题的研究。然而。如今负信用期逐渐兴起,即供应商先收款后发货,尤其是在网络交易或者供应链中处于强势地位的供应商很多采用了这种方式。文章研究了基于负信用期条件下的供应商最优信用期决策。首先.假设商品的终端需求对价格是敏感的,即其价格需求弹性小于-1。其次.采用Stackelberg模型来界定买家与供应商的关系,即供应商先制定其策略,买家再根据供应商的策略做出反应进而做出自己的决策。然后通过建立模型分别给出供应商提供正信用期和负信用期时供应商和买家为了使得各自利润最大化的决策制定方法。通过数学算例得出供应商做出的最优信用期决策随着条件变化而变化.并通过灵敏度分析.找出影响供应商做出决策的一些重要因素。

关 键 词:负信用期  需求弹性  STACKELBERG模型  灵敏度分析

The Optimal Credit Period for A Supplier When Negative Credit Period Is Allowed
ZHENG Jin-chuan,LIU Hui,TANG Yan. The Optimal Credit Period for A Supplier When Negative Credit Period Is Allowed[J]. Logistics Management, 2008, 31(9): 127-131
Authors:ZHENG Jin-chuan  LIU Hui  TANG Yan
Affiliation:(Fudan University, Shanghai 200433, China)
Abstract:
In many procurement activities,the buyer is allowed to settle the account a period of time after the purchase without paying any interest charges.This time period is known as the credit(credit period).There are many researches on this issue.Today,however,negative credit period which means the buyer settles the account first then receives the goods is becoming popular,particularly in the online transactions or the situation in which the supplier is strong.This paper researches the optimal credit period for the supplier when negative credit period is taken account of.This paper first assumes the end demand is price sensitive then uses Stackelberg model to define the relationship between buyer and supplier.Through the model the decision-making methods which maximize both parties' profits are given under positive and negative credit period circumstances.The paper figures out that the optimal credit period varies under different conditions.The paper also finds some important factors which influence the supplier's decision-making through sensitive analysis.
Keywords:negative credit period  demand elasticity  stackelberg model  sensitive analysis
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