Information sharing in supply chains

Supply chain is defined as a system of suppliers, manufacturers, distributors, retailers and customers where material, financial and information flows connect participants in both directions. Most supply chains are composed of independent agents with individual preferences. It is expected that no single agent has the power to optimise the supply chain. Supply chain management is now seen as a governing element in strategy and as an effective way of creating value for customers. The so-called bullwhip effect, describing growing variation upstream in a supply chain, is probably the most famous demonstration that decentralised decision making can lead to poor supply chain performance. Information asymmetry is one of the most powerful sources of the bullwhip effect. Information sharing of customer demand has an impact on the bullwhip effect. Information technology has lead to centralised information, shorter lead times and smaller batch sizes. The analysis of causes of the bullwhip effect has lead to suggestions for reducing the bullwhip effect in supply chains by strategic partnership. Supply chain partnership leads to increased information flows, reduced uncertainty, and a more profitable supply chain. The cooperation is based on contacts and formal agreements. Information exchange is very important issue for coordinating actions of units. New business practices and information technology make the coordination even closer. Information sharing and strategic partnerships of units can be modelled by different network structures.     

IMPACT OF POS DATA SHARING ON SUPPLY CHAIN MANAGEMENT: AN EXPERIMENTAL STUDY

We examine the impact of point of sale (POS) data sharing on ordering decisions in a multi‐echelon supply chain. In particular, we focus on how exposure to POS data may help reduce the “bullwhip effect,” the tendency of orders to increase in variability as one moves up a supply chain. Theoretical studies have shown that exposure to POS data can lead to a reduction in the bullwhip effect when suppliers have no prior knowledge of the demand distribution. The benefit of sharing POS data in stable industries, where the demand distribution is commonly known, is less clear. We study this phenomenon from a behavioral perspective in the context of a simple, serial, supply chain subject to information lags and stochastic demand. We find, using a controlled simulation experiment, that sharing POS information does help reduce some components of the bullwhip effect in a stable demand setting, namely the order oscillation of upstream members. We offer one possible explanation for this improvement by examining the relationship between order decisions and demand line information.     

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.     

基于两单链合作下的集群式供应链牛鞭效应的H∞控制研究

以集群式供应链跨链间库存合作为背景,针对两单链情形,考察零售商的紧急库存补充渠道来自于另一供应链的零售商,建立了集群式供应链跨链间库存合作下的库存模型和牛鞭效应量化方法。并用H_∞控制理论来寻求最优订货系列,以达到降低安全库存水平,提高顾客满意度和减弱牛鞭效应的目的。仿真实验表明,实施H_∞控制和跨链间库存互补策略可以有效抑制牛鞭效应。     

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.     

Supply Chain Inventory Replenishment: The Debiasing Effect of Declarative Knowledge

Previous experimental research demonstrates that inefficient replenishment decision making in the supply chain can be caused by specific judgment and decision biases. Based on the literature we use controlled experiments involving both student subjects and supply chain managers to test debiasing interventions that provide declarative knowledge, which is theorized to enhance the acquisition of procedural knowledge. We first investigate the effects of three debiasing components in a single‐echelon setting: knowledge of bullwhip, inventory position (IP), and use of a target order‐up‐to quantity. Experiment 1 (N = 1,608 decisions by 67 student subjects) using a 2 × 2 × 2 factorial design for the three components finds that the conceptual understanding of IP is salient for efficient replenishment decisions. We next examine the effects of the components in a simulated, multi‐echelon, serial supply chain, which introduces the additional complexity of coordination risk. Experiment 2 (N = 3,072 decisions by 128 student subjects) using a 2 × 2 × 2 factorial design finds that although subjects benefit from training components, there is evidence of cognitive overload with an increased quantity of information. Finally we test whether these debiasing components may be an effective training program for practicing supply chain managers who can be expected to have higher levels of procedural knowledge through experience gained in the field. Experiment 3 (N = 864 decisions by 36 supply chain managers) using a 2 × 1 design investigates the effects of an instructional training intervention which includes all three debiasing components and finds the intervention to reduce costs by 14%. We provide avenues for future research and successful practice.     

The impact of stochastic lead times on the bullwhip effect under correlated demand and moving average forecasts

We quantify the bullwhip effect (which measures how the variance of replenishment orders is amplified as the orders move up the supply chain) when both random demands and random lead times are estimated using the industrially popular moving average forecasting method. We assume that the lead times constitute a sequence of independent identically distributed random variables and the correlated demands are described by a first-order autoregressive process. We obtain an expression that reveals the impact of demand and lead time forecasting on the bullwhip effect. We draw a number of conclusions on the bullwhip behaviour with respect to the demand auto-correlation and the number of past lead times and demands used in the forecasts. We find maxima and minima in the bullwhip measure as a function of the demand auto-correlation.     

基于风险规避和公平偏好的供应链收益共享契约协调研究

在一个简单的二级供应链系统中,建立了供应商和零售商同时具有风险规避和公平偏好的收益共享契约协调模型,通过修正、扩展FS效用收益模型,先后考察并分析了分散决策和集中决策下供应链的协调状态,研究发现,供应商和零售商的风险规避系数和公平偏好系数及收益份额必须满足特定的条件,收益共享契约才能使系统供应链整体达到协调状态;在此基础上,对风险规避和公平偏好因素进行敏感度分析,得到供应商和零售商行为偏好系数对供应链及成员最优订货量的影响;最后进行演化博弈算例分析和结论验证,体现了该协调模型的有效性和实用性。由此说明供应商和零售商的风险规避和公平偏好因素同时作用会改变系统供应链协调时的最优订货量,并对决策人的决策行为产生很大的影响。     

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。     

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。     

考虑随机市场需求的双渠道供应链风险补偿策略研究——从质量与价格竞争视角

在由两个供应商和单个零售商构成的二级双渠道供应链系统中，分析了随机市场需求以及供应商之间同时存在价格与质量竞争的情形下的双渠道供应链协调问题。在供应链集中决策、无风险补偿及有风险补偿三种情境下，构建了基于质量和价格的风险补偿模型并求得纳什均衡解。研究结果表明：存在可行的需求风险补偿策略使得供应链达到协调水平，并且需求风险补偿策略对零售商更加有利；在需求风险补偿策略下，需求风险补偿价格与其对应批发价格正相关，与其产品质量水平负相关；价格竞争程度对零售商订货量具有负向影响作用，对供应链总利润影响作用随着竞争程度增加而减弱，质量竞争程度对零售商订货量和供应商产品质量水平具有正向影响作用，对供应链总利润影响呈倒U型关系；需求风险补偿策略能够激励零售商的订货行为，强化价格竞争程度和质量竞争程度对供应商订货量和供应链总利润的影响；在供应链系统中双渠道营销模式下的供应链总利润要优于单渠道营销模式下的供应链总利润。本文结论不仅详细剖析了风险补偿策略对双渠道供应链协调的影响关系，也理清了价格与质量竞争对各方行为策略的影响机理。     

供应链信息管理研究现状及展望

供应链信息管理问题已涉及的研究范围包括供应链上信息流特点的研究,信息分类的研究,牛鞭效应的存在、成因及弱化措施的研究,牛鞭效应以外的其它类型信息失真的研究,由信息失真引起的信息风险问题的研究,以及利用信息共享相关技术支持解决信息管理问题的研究等。对供应链上的信息分类、信息失真、信息风险和信息共享等信息管理问题的国内外研究成果进行了全面的回顾和总结。通过对供应链上信息管理问题的研究方法进行的分析和总结,针对供应链中普遍存在的信息管理问题指出了进一步研究的方向。     

Product Design and Supply Chain Coordination Under Extended Producer Responsibility

Extended Producer Responsibility (EPR) legislation focuses on the life‐cycle environmental performance of products and has significant implications for management theory and practice. In this paper, we examine the influence of EPR policy parameters on product design and coordination incentives in a durable product supply chain. We model a manufacturer supplying a remanufacturable product to a customer over multiple periods. The manufacturer invests in two design attributes of the product that impact costs incurred by the supply chain—performance, which affects the environmental impact of the product during use, and remanufacturability, which affects the environmental impact post‐use. Consistent with the goals of EPR policies, the manufacturer and the customer are required to share the environmental costs incurred over the product's life cycle. The customer has a continuing need for the services of the product and optimizes between the costs of product replacement and the costs incurred during use. We demonstrate how charges during use and post‐use can be used as levers to encourage environmentally favorable product design. We analyze the impact of supply chain coordination on design choices and profit and discuss contracts that can be used to achieve coordination, both under symmetric and asymmetric information about customer attributes.     

库存水平影响需求的变质性产品的供应链协调模型

在考虑市场需求是库存水平线性分段函数、变质性产品和零售商采用(S,s)订货策略的情形下,本文研究了由一个供应商和一个零售商构成的供应链系统运作协调问题。给出了可以实现供应链完美协调的数量折扣策略,理论证明了模型最优解的存在性和唯一性,同时提供了相应的求解方法。数值算例结果表明该折扣模型对于改善供需双方绩效和供应链运作协调是十分有效的。     

航运供应链上的品牌价值、公平关切与契约协调

航运供应链上的船公司提高企业品牌价值需要付出大量的投资成本,因此将会更加关注供应链上利润分配的公平。本文以单个船公司和单个货代公司构成的两级航运供应链为研究对象,运用博弈论分析船公司的公平关切行为和品牌投入意愿对航运供应链上各方利润的影响,探讨决策者非理性条件下航运供应链的合作模式和协调机制。研究表明：1）船公司的公平关切提高了其在供应链上利润分配占比,但降低了整个航运供应链的利润和效率;2）随着品牌投入意愿的提高,船公司的公平关切对航运供应链上各方决策的负作用就越明显;3）"收益共享成本共担"式契约能够消除公平关切的负作用,达到航运供应链纵向联盟的最优收益和整体效率。     

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.     

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.     

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。