多级供应链中库存不准确性对牛鞭效应的影响

目前大多数关于牛鞭效应的研究聚焦于两级供应链,极少数文献研究多级供应链系统中的牛鞭效应问题,且这些文献鲜有考虑到库存不准确的问题.本文通过建立解析模型量化分析在库存信息不准确的多级、分散供应链中的牛鞭效应,揭示牛鞭效应在高阶段供应链中的放大情况,以及库存准确性对牛鞭效应的影响.本文研究表明,库存误差会进一步恶化信息的扭曲,该信息扭曲随着订单传播过程被逐级放大和累积,使得牛鞭效应在高阶段供应链中成指数增长.共享信息可以缓解信息的扭曲,将牛鞭效应减低为线性增长.本文通过将供应链建模从两级拓展到多级,同时考虑到信息准确性问题,旨在更加完整的勾勒出需求信息在供应链中的传播情况.     

基于APIOBPCS模式VMI下牛鞭效应仿真研究

运用系统动力学构建基于APIOBPCS采购模式和供应商管理库存的七成员供应链模型,通过该模型研究8个因素对牛鞭效应的影响.研究表明,平滑指数越小牛鞭效应越弱:库存初始值影响牛鞭效应的具体数值,但不能根本改变牛鞭效应;牛鞭效应受APIOBPCS模式库存调节系数影响巨大,DE-APIOBPCS模式下牛鞭效应相对较弱;在库存调节系数设定为1、某成员的所有下游成员提前期已经确定的前提下,该成员需求的标准方差只与紧邻上游成员的提前期有关,其余成员的提前期对该成员需求标准方差没有影响;库存检查周期越短牛鞭效应越弱;在供应链信息共享以及成员合作的前提下,瓶颈取适当值情况下的牛鞭效应与没有瓶颈情况下的牛鞭效应相比,前者更小;最低采购数量影响牛鞭效应,并且牛鞭效应对此因素表现出比较强的敏感性.     

基于控制工程的牛鞭效应建模与仿真研究

"牛鞭效应"对供应链性能和绩效产生了严重的影响.本文基于控制理论建立了多级线性供应链的模型,分别利用噪声带宽和Matlab/simulink对一个可扩展多主体线性供应链系统的牛鞭效应进行了建模与仿真研究,分析了实施信息共享前后供应链系统的牛鞭效应,探讨了物流延迟时间参数和指数平滑预测参数对牛鞭效应的影响,并给出了减弱牛鞭效应影响的相应策略.     

基于小波域隐马尔可夫模型的时间序列分析-平滑、插值和预测

提出一种基于小波域隐马尔可夫模型的时间序列分析方法.首先介绍了离散小波变换;并针对小波系数进行统计建模,分别讨论了单个小波系数的混合高斯模型、不同尺度小波系数之间的隐马尔可夫树结构、模型训练及似然计算等问题;其次,提出了关于时间序列插值、平滑和预测的统一数学模型,并运用极大后验概率估计和贝叶斯原理,将小波域隐马尔可夫模型作为先验知识给出了一种分析时间序列的新方法;然后,详细推导了时间序列重建问题的Euler-Lagrange方程及对数似然的导数计算,将时间序列的插值、平滑和预测归结为一个简单线性方程的求解;最后通过期望极大化(EM)算法和共扼梯度算法进行交替迭代来计算小波域隐马尔可夫模型参数和重建时间序列.实验结果表明该方法在经济领域时间序列分析中的有效性.     

基于DE-APIOBPCS策略的牛鞭效应和库存方差

本文就一般补充规则即APIOBPCS策略,从控制理论的角度,推导出牛鞭效应的一个分析表达式,由该式知道,采用增大预测平均时间和库存差异(或者渠道差异)增益以及减少生产提前期的控制手段,可以减少牛鞭效应,本文还推导出库存方差的一个分析表达式,把它与牛鞭效应分析表达式一起使用时,就两种方差之间一系列权重值,讨论了牛鞭效应和库存方差之间的平衡,基于这种平衡,生产和库存控制者可以设计一些恰当的供应链系统。     

信息共享下库存量牛鞭效应的影响因素研究

目前的研究多从供应链上游角度出发考虑传统牛鞭效应,而本文从供应链下游的角度研究库存量牛鞭效应得到了不一样的管理学启示.在需求函数方面,建立的需求模型包括市场规模、价格敏感性系数等更有现实意义的要素.在此,本文建立了包括一个零售商和一个制造商的简单两级供应链,得出了制造商在采用补充至订货点策略和最小均方差预测技术,在两种不同的信息共享模式下的库存量牛鞭效应表达式,并对他们的影响因素进行了分析.而且通过数值分析对模型进行了验证并得到新的结果.通过研究发现,信息共享能够显著降低制造商的库存量牛鞭效应;零售商和制造商的库存量牛鞭效应都不受市场规模的影响;零售商的库存量牛鞭效应在一定条件下不存在;相比于零售商提前期,制造商提前期对制造商的库存量牛鞭效应影响更大.同时,价格敏感性系数、价格自相关系数等因素对制造商库存量牛鞭效应也有不同程度的影响.     

非平稳需求状态下虚拟企业牛鞭效应的存在性分析

本文从供应链管理的角度出发,将牛鞭效应的概念和模型引入虚拟企业的运营过程中,运用可变系数的自回归移动平均(ARIMA)模型对虚拟企业上下游成员企业需求信息进行预测,研究非平稳需求状态下虚拟企业内上下游企业订货水平的差异,证明了虚拟企业运营中牛鞭效应的存在性,最后提出除虚拟企业的敏捷经营、信息共享对牛鞭效应的影响以外,需求的波动也是影响牛鞭效应的重要因素,并讨论了信息完全共享的情况下牛鞭效应存在的条件.     

在ARIMA(0,1,1)需求下的牛鞭效应与信息共享的评价

本文考虑一个包含一个供应商和一个零售商的两级供应链,研究在需求模型ARIMA(0,1,1)下牛鞭效应的量化和信息共享的价值,比较信息共享之前和之后的差异,其结果表明信息共享能给供应商带来减轻牛鞭效应、减少现有平均库存以及降低成本等好处。     

需求信息预测与处理中的牛鞭效应分析与控制

研究了不稳定的市场需求下一个生产商和一个零售商所组成的两层次的简单供应链系统.提出当零售商预测信息的过程中并不存在牛鞭效应现象,而在生产商和零售商利用库存策略处理需求信息的过程中却显著存在牛鞭效应现象.证明了利用信息共享的方式可以控制牛鞭效应,但不能完全消除牛鞭效应.     

基于CPFR模型供应链"牛鞭效应"分析

牛鞭效应对企业产能与库存方面的影响很大。在不完全预先需求信息条件下,从CPFR的角度,通过建立模型对供应链各节点成员间缺乏对需求预测造成的供应链中牛鞭效应进行分析,并提出减少牛鞭效应影响的相应策略。     

Order Stability in Supply Chains: Coordination Risk and the Role of Coordination Stock

The bullwhip effect describes the tendency for the variance of orders in supply chains to increase as one moves upstream from consumer demand. We report on a set of laboratory experiments with a serial supply chain that tests behavioral causes of this phenomenon, in particular the possible influence of coordination risk. Coordination risk exists when individuals' decisions contribute to a collective outcome and the decision rules followed by each individual are not known with certainty, for example, where managers cannot be sure how their supply chain partners will behave. We conjecture that the existence of coordination risk may contribute to bullwhip behavior. We test this conjecture by controlling for environmental factors that lead to coordination risk and find these controls lead to a significant reduction in order oscillations and amplification. Next, we investigate a managerial intervention to reduce the bullwhip effect, inspired by our conjecture that coordination risk contributes to bullwhip behavior. Although the intervention, holding additional on‐hand inventory, does not change the existence of coordination risk, it reduces order oscillation and amplification by providing a buffer against the endogenous risk of coordination failure. We conclude that the magnitude of the bullwhip can be mitigated, but that its behavioral causes appear robust.     

基于认知风险度量的ISC牛鞭效应分析

在行为金融范式下,以DHS(Daniel-Hirshleifer-Subrahmanyam)模型描述了ISC(集成供应链)参与者的过度自信心理,建立了含有过度自信心理的ISC需求均衡模型;并且,从损失概率和期望损失两个角度,基于认知风险度量揭示了ISC牛鞭效应的作用机理。“有限理性人”更符合ISC系统运作的实际情形,本研究为在行为金融范式下度量ISC牛鞭效应提供了一种新的思路。     

Decision Making and Cognition in Multi‐Echelon Supply Chains: An Experimental Study

Supply chain performance often depends on the individual decisions of channel members. Even when individuals have access to relevant information, order variation tends to increase when moving up the supply chain, a phenomenon known as the bullwhip effect. While prior research has investigated several structural/environmental factors which can mitigate the bullwhip effect, the underlying behavioral factors contributing to it are an open question. Using a production and distribution decision‐making simulation representing a four‐stage serial supply chain, we find that the cognitive profile of decision makers contributes to the bullwhip effect. We found that the specific decision tendency to underweight the supply line is linked to an individual's level of cognitive reflection. Furthermore, performance differs for entire supply chains and for specific echelons, and holds under standard mitigation efforts. The findings have implications for supply chain design, education, and industry.     

供应链网络系统的牛鞭效应时滞因素分析与库存控制策略研究

牛鞭效应的存在严重影响了供应链系统的运作效率,增加了供应链管理的复杂性。本文基于供应链网络库存状态的内部系统动力学机制,构建了供应链网络库存系统的状态转移模型,并引入时滞影响因素,通过供应链网络库存系统的波动状态描述牛鞭效应。在此模型基础上,针对供应链网络系统的牛鞭效应问题,提出了一类新的基于库存波动状态的动态供应链库存控制策略,并运用系统稳定性理论,将该策略的参数优化求解问题转化成线性矩阵不等式的求解问题。最后通过系统仿真深入分析了供应链网络库存系统对库存控制策略参数以及系统时滞因素的敏感性,并验证了该动态库存控制策略可以有效地抑制牛鞭效应。     

On variance amplification in a three-echelon supply chain with minimum mean square error forecasting

We analyse a three echelon supply chain model. First-order autoregressive end consumer demand is assumed. We obtain exact analytical expressions for bullwhip and net inventory variance at each echelon in the supply chain. All of the three supply chain participants employ the order-up-to policy with the minimum mean square error forecasting scheme. After demonstrating that the character of the stochastic ordering process observed at each level of the supply chain is mathematically tractable, we show that the upper stream participants have complete information of the market demand process. Then we quantify the bullwhip produced by the system, together with the amplification ratios of the variance of the net inventory levels. Our analysis reveals that the level of the supply chain has no impact upon the bullwhip effect, rather bullwhip is determined by the accumulated lead-time from the customer and the local replenishment lead-time. We also find that the conditional variance of the forecast error over the lead-time is identical to the variance of the net inventory levels and that the net inventory variance is dominated by the local replenishment lead-time.     

Price promotions,operations cost,and profit in a two-stage supply chain

The phenomenon in which demand variability increases as one moves upstream in the supply chain has been often observed in practice. This so-called “bullwhip effect” often increases upstream operations costs, including inventory holding and transportation costs. Price variations are considered to be one of the primary causes of the bullwhip effect, and thus everyday low price (EDLP) strategies are commonly recommended to counter the negative impacts of the bullwhip effect. However, trade promotions continue to play an important role in the U.S. supermarket industry as well as other industries. This paper investigates this apparent inconsistency between the literature and practice by employing a deterministic, two-stage supply chain model composed of a single supplier and a single retailer. We demonstrate that even though the use of trade promotions can indeed increase a retailer's and supplier's operations costs, these costs may be more than offset by increased revenues, even in the absence of explicit coordination. That is, if the supplier judiciously applies a trade promotion strategy and the retailer passes some of this discount to its customers, then under certain conditions, the resulting supply chain profit can exceed that under an EDLP strategy. We provide a broad set of computational results that validate this conclusion and discuss the resulting managerial insights.     

供应链中断下顾客缺货反应对牛鞭效应的影响研究

传统的关于供应链牛鞭效应的研究,仅关注供应链上游成员间（供应商、制造商或零售商）的协调运作,而忽略缺货发生后顾客缺货反应对供应链动态性的影响。本文利用高层级Petri-net对包含两个制造商、两个零售商的供应链系统进行建模与仿真,定量地研究不同的缺货强度下顾客缺货反应对两条相互竞争的供应链牛鞭效应的影响。研究结果表明,顾客缺货反应对缺货品牌及其竞争品牌的牛鞭效应均存在显著影响,但各种缺货反应对牛鞭效应的影响程度有所差异,且供应链中断强度（主要体现为发生缺货的品牌市场份额以及缺货持续时间）亦对牛鞭效应产生显著影响。我们建议不同产品类型（对应不同的顾客反应组合）的管理者根据品牌的市场占有率、缺货持续时间等因素对不同类型的顾客进行购买行为的引导,以缓解牛鞭效应并保持市场份额。