Decentralised decision-making with information sharing vs. centralised decision-making in supply chains

In recent years, implementing coordination mechanisms in decentralised supply chains to reduce the well-known negative effects of decentralisation, such as the ‘bullwhip effect’, has become a considerable challenge. Furthermore, with the dramatic developments in information and communication technologies, real-time information sharing has become increasingly easier to implement. In this work, we study a mono-product divergent supply chain composed of a supplier, a warehouse, retailers and customers in the context of decentralised and centralised decisions. The main objective of this study is to compare a decentralised supply chain combined with different scenarios of simultaneous upstream and downstream information sharing vs. a centralised supply chain. A mathematical model is developed to compare the logistics costs in the two decision contexts. The experimental results clearly show that the simultaneous sharing of customer demand and supplier-warehouse lead time information in a decentralised supply chain yields nearly equivalent logistics costs as the centralised supply chain context. However, the main beneficiary of the sharing is the warehouse, which receives approximately two-thirds of the benefit. Thus, incentives and revenue sharing contracts should be implemented to motivate and balance the benefits between supply chain partners.     

Measure of the bullwhip effect considering the market competition between two retailers

In order to consider the market competition, a new supply chain with one supplier and two retailers is established in this paper. Two retailers employ different AR(1) demand processes, respectively, and an order-up-to inventory policy characterises the inventory decisions. The bullwhip effect in this supply chain is measured under the moving average forecasting technique. We investigate the effects of the lead time, the span of forecast, market competition and the consistency of demand volatility on the bullwhip effect using the algebraic analysis and numerical simulation. Conclusions indicate that different factors lead to the bullwhip effect following different patterns in the supply chain. Moreover, some suggestions are present to help managers to control parameters that yield the lower bullwhip effect.     

Bullwhip effect and inventory oscillations analysis using the beer game model

This work examines the bullwhip effect generated and suffered by each level of a four-stage beer game supply chain when different demand scenarios are considered. The paper shows that the actors who generate lower bullwhip are those who suffer more from its effects. Moreover, a new definition of an inventory oscillations measure based on bullwhip definition is introduced. Finally the paper verifies that the new measure of inventory oscillations provides more information on supply chain performance than the bullwhip measure.     

基于提前期的需求信息放大效应定量研究

在m个分销商和一个制造商的两级供应链中考虑提前期对信息放大效应的作用,推导出分销商需求信息与最初客户群的需求信息之间的需求信息放大效应的表达式.实例分析证明在即使不存在提前期(或者提前期为零)的情况下仍然存在信息放大效应,单纯地压缩提前期不能真正减少信息放大效应的影响,提出实现企业之间的合作与实时信息共享是关键.     

制造企业库存长鞭效应影响因子分析及控制方法

长鞭效应是供应链管理中由于供应链合作伙伴之间缺乏合作与协调的结果。从理论上刻画了长鞭效应的内在本质,分析了产生长鞭效应的原因,以一个跨国公司的库存管理为例,详细分析了影响长鞭效应三个方面的因子：（1）集中式与分散式管理;（2）需求与供应特征;（3）产品类型与库存再订货点。还从供需合作关系的角度提出了改善长鞭效应的几个控制方法。     

Effective bullwhip metrics for multi-echelon distribution systems under order batching policies with cyclic demand

A large number of problems in a distribution supply chain require that decisions are made in the presence of the bullwhip effect phenomenon. The impact of the order batching policies on the bullwhip effect is analysed in this paper, when cycle demand on a multi-echelon supply chain operating is considered. While investigating which bullwhip effect metrics are more adequate to measure the bullwhip effect in these type of systems, the optimal reordering plan that minimises the operation costs of the overall system is calculated. A Mixed Integer Linear Programming (MILP) model is developed that takes into account an inventory and distribution system formed by multiple warehouses and retailers with lateral transshipments. The bullwhip effect is measured through four metrics: the echelon average inventory; the echelon inventory variance ratio; the echelon average order; and the echelon order rate variance ratio. As conclusion the inventory metrics suggest that (i) using batching policy reduces instability; (ii) batching may reduce in general order variance if using larger batches and (iii) cycle demand length has no major impact in the bullwhip effect. A motivational example and a real word case study are used and tested.     

基于遗传算法的供应链需求预测优化模型研究

整体优化是供应链管理的核心问题之一.为降低供应链的整体运作成本,减小"长鞭效应"的影响,建立了多级供应链的Multi-agent模型,并运用遗传算法(GA)对其需求预测进行优化研究.最后利用算例进行分析,表明提出的方法能有效减小"长鞭效应",有效降低供应链的整体运作成本.     

On the Bullwhip Avoidance Phase: supply chain collaboration and order smoothing

This paper provides an assessment of the impact of collaboration and smoothing replenishment rules on supply chain operational performance and customer service level. Three supply chain configurations (i.e. Traditional, Information Exchange and Synchronised) in which orders are generated by smoothing (S, R) inventory control policies are studied for different proportional controllers. A supply chain stress test is performed through a sudden and intense change in demand. A structured and extended supply chain assessment framework is adopted. The main conclusions of this paper are the following. (i) The impact of Supply Chain Collaboration on overall supply chain performance is greater than that of order smoothing. Order smoothing mitigates the bullwhip effect, but it may have a negative impact on customer service. Supply Chain Collaboration mitigates the bullwhip effect, provides inventory stability, limits lumpy orders and enhances customer service level. (ii) The negative effect on customer service level of order smoothing is almost eliminated in synchronised supply chains.     

Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain†

The ripple effect refers to structural dynamics and describes a downstream propagation of the downscaling in demand fulfilment in the supply chain (SC) as a result of a severe disruption. The bullwhip effect refers to operational dynamics and amplifies in the upstream direction as ordering oscillations. Being interested in uncovering if the ripple effect can be a driver of the bullwhip effect, we performed a simulation-based study to investigate the interrelations of the structural and operational dynamics in the SC. The results advance our knowledge about both ripple and bullwhip effects and reveal, for the first time, that the ripple effect can be a bullwhip-effect driver, while the latter can be launched by a severe disruption even in the downstream direction. The findings show that the ripple effect influences the bullwhip effect through backlog accumulation over the disruption time as a consequence of non-coordinated ordering and production planning policies. To cope with this effect, a contingent production-inventory control policy is proposed that provides results in favour of information coordination in SC disruption management to mitigate both ripple and bullwhip effects. The SC managers need to take into account the risk of bullwhip effect during the capacity disruption and recovery periods.     

两种库存管理方法下的牛鞭效应比较分析

建立了ARIMA供应链需求模型,利用订货量方差和需求方差的比值,分别对Order-up库存管理方法和基于MRP的库存管理方法下的牛鞭效应进行了量化.比值大于1则牛鞭效应存在且与比值成正比,反之则牛鞭效应不存在.模拟试验对两种库存管理方法作了对比,结果表明基于MRP的库存管理方法在多数情况下产生了较小的牛鞭效应.     

供应链设计、供应链整合、信息共享与供应链绩效的关系研究

构建了供应链设计、供应链整合、信息共享及供应链绩效之间关系的理论模型,并以广东省珠三角地区162家制造企业为调查对象,对供应链设计、供应链整合、信息共享及供应链绩效之间的关系进行实证研究。研究结果表明,供应链设计对供应链整合、供应链绩效均有显著的正向影响;供应链设计对信息共享的直接影响并不显著,却会以供应链整合为中介对信息共享产生间接影响;供应链整合对信息共享、供应链绩效有显著的正向影响;而低层次的信息共享对供应链绩效并无显著影响。根据上述实证研究结果,本研究结合中国情境给出了相关管理启示。     

Analysis of the bullwhip effect in multi-product,multi-stage supply chain systems–a simulation approach

This research aims to develop a simulation approach based on system dynamics modelling (SDM) and adaptive network based fuzzy inference system (ANFIS) for quantifying and reducing the bullwhip effect in a multi-product, multi-stage supply chain. The proposed model is comprised of three groups of variables influencing the bullwhip effect, namely the structure of a supply chain network, supply chain contributions (ordering process in regular situation or when a supplier has a promotion or shortage gaming) and supply chain performances (the number of defects and ordering lead time). As a result, a two layer simulation model is developed with three generic models. The flexibility of this proposed approach is its ability to model various types of ordering policies which are basic inventory policies, material requirement planning (MRP) system and just in time (JIT) approach. The supply chain of a beverage company was selected to validate and demonstrate the flexibility of the proposed model. The findings of the proposed simulation model are consistent with the results obtained from the case study. The error magnitude of the bullwhip effect level varied between 0 and 9% resulting in bullwhip effect reductions of up to 92%. Accordingly, the bullwhip effect levels are significantly decreased by using the proposed simulation model.     

Information management strategies and supply chain performance under demand disruptions

The operations management literature presents inadequate comprehensive understanding on information management strategies of mitigating supply chain disruption risks. By using control theory modelling and simulation, this study compares the disruption mitigation effects of three information management strategies. From the aspect of stability, the existing stability boundaries are revised by a new method in a two-echelon case. It shows that supply chains (SC) with popular information management strategies are not evidently more stable than traditional ones. From the aspect of disruption recovery time, an innovative two-echelon swiftest response problem under these information management strategies is formulated and solved. Results show that a collaborative planning, forecasting and replenishment (CPFR) SC with complete SC information performs the best. However, in a later operational risk mitigation test, an information sharing (IS) SC with partial information has the smallest bullwhip effect. From the aspect of demand amplification and frequency response, an innovative frequency–response plot of order amplification is proposed in a time-continuous SC with moving average forecasts. It implies the best frequency response for concurrently mitigating both operational and disruption risks coming from a CPFR SC. But for a certain SC structure there is still a balance between mitigating bullwhip effect and quick response. Moreover, it also implies that anti-bullwhip should exist in a certain condition, as realised in our numerical experiments.     

An extension to fuzzy estimations and system dynamics for improving supply chains

Campuzano, Mula, and Peidro (“Fuzzy estimations and system dynamics for improving supply chains.” Fuzzy Sets and Systems 161: 1530–1542) evaluate the behaviour of fuzzy estimations of demand instead of exponential smoothing for demand forecasts in a two-level (manufacturer and end customer) supply chain and demonstrate how the bullwhip effect and the amplification of inventory variance (NSAmp) can be effectively reduced. In this note, we extend and test the previous model to a three-level supply chain which consists of an end consumer, a retailer and a manufacturer. Here, the model is tested by using both Gaussian and autoregressive demand patterns. We show that the bullwhip effect and NSAmp also reduce at the level where fuzzy orders exist with good fill rate values.     

Serial vs. divergent supply chain networks: a comparative analysis of the bullwhip effect

The amplification of demand variation in a supply chain network (SCN) is a well-known phenomenon called the bullwhip effect, which creates inefficiencies due to high variation in the order quantities placed between companies, leading to a flow of a larger number of units than the actual need, increasing stock and generating stock-outs. Since this phenomenon has been recognised as one of the main obstacles for improving SCN performance, recently it has received a lot of attention by SCN managers and researchers. One of the most common simplifying assumptions in the literature is to assume that the SCN adopts a serial structure. The present work addresses a comparative analysis of the bullwhip effect between a serial SCN and a more complex divergent SCN. To do so, we analyse the response of both SCNs under two different input demands: a stationary demand and an impulse demand. The results reveal that there are not significant differences in terms of bullwhip effect between both SCNs for a stationary demand. Nevertheless, we show how for a violent disturbance in customer demand there is a great different between the two SCNs.     

Supply chain disruption risk management through strategic information acquisition and sharing and risk-sharing contracts

In this paper, we develop a framework that captures the effects of information management and risk-sharing contracts in supply chain networks. In particular, we analyse the impact of strategic information acquisition and sharing on supply chain disruption risks and costs and we evaluate the supply chain performance of risk-sharing contracts. Risk-sharing contracts specify who needs to incur the costs when supply chain disruptions occur. We develop a model that consists of three tiers of multi-criteria decision-makers, manufacturers, retailers, and demand markets. We describe the behaviour or each decision-maker, derive the finite-dimensional variational inequality formulation of the equilibrium conditions of the supply chain and present numerical examples. The numerical examples highlight that it is not a priori clear which participant in the supply chain network will benefit from increased information-sharing activities. Our models indicate that the beneficiary of reduced information-sharing costs is in some cases dependent on the negotiation power of participants and that it is also dependent on the type of risk-sharing contract used. Furthermore, the numerical examples show that, in some cases, information-sharing and risk-sharing contracts are complements while in other cases they are substitutes.     

供应链中牛鞭效应的控制与弱化研究

为了弱化供应链中的牛鞭效应,本文剖析了其危害及形成机理,指出供应链的系统属性和管理运作两方面因素构成了牛鞭效应产生的主要原因,进而着眼于供应链的整体竞争力,有针对性地提出了控制牛鞭效应的系列策略,即强化战略协作及信息共享,消减供应链级数,开展敏捷管理,减少订货批量,控制安全库存,平衡库存责任和弱化最终需求的变异性.     

Bullwhip and anti-bullwhip effects in a supply chain

The anti-bullwhip effect, coined by Li et al. in 2005 based on the findings in a simulation study, is the contrary effect of the well-known bullwhip effect. Although there is ample empirical evidence that suggests both effects exist, current literature has not yet provided an integrated framework to address how the two effects are related with each other. By extending the classic work of Lee, Padmanabhan, and Whang of 1997 to a multi-stage supply chain, we derive closed-form formula to analytically describe how the two effects originate initially and then evolve over time and space in the supply chain. Our results show both the bullwhip effect and the anti-bullwhip effect can occur when facing different end-customer demands. However, the magnitude of these effects gradually decreases when moving upstream. We also show the impact of long lead-time on increasing the magnitude of information transformation at the next stage and simultaneously decreasing the magnitude at higher stages. These analytical results provide a theoretical explanation to most simulation findings of Li et al.'s 2005 work and can be used by researchers and practitioners to examine the empirical data and design innovate marketing strategies to convert the unwelcome bullwhip effect into the anti-bullwhip effect.     

The bullwhip effect in supply chains: a study of contingent and incomplete literature

The bullwhip effect (BWE) describes a phenomenon that involves the increasing amplification of demand variability along a supply chain (SC). The BWE has been a subject that has received continuous attention from researchers over the past 15 years and is a concern for SC managers because it is a major cause of efficiency and effectiveness loss in SCs. Information sharing between actors in an SC is usually considered to be one of the primary means to minimise the BWE. Approximately 50 articles published in major journals on these topics are studied in this article. An analytical framework is used to highlight the contingent character of the conclusions proposed by the authors. In this review, we identify the existence of significant gaps in the literature, especially concerning the BWE when it occurs in the productive part of the SC.