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.     

Issues on the reduction of demand variance in the supply chain

To streamline an agile manufacturing system of a global firm facing a high demand of market service, supply chain management (SCM) plays an important role. In SCM, a phenomenon called ‘the bullwhip effect’ has attracted considerable attention. This study examines the bullwhip effect caused by order variance from retailers. It shows that based on portfolio theory, supplier's demand variance can be reduced by adjusting the order quantities of retailers through co-ordination. The results indicate that our approach can be a useful means for alleviating the 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.     

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.     

考虑随机市场需求和不同博弈地位的双渠道供应链策略分析

为研究供应链成员不同博弈地位下双渠道定价及随机库存问题,分别构建制造商主导、零售商主导及双方同等博弈地位的双渠道供应链博弈模型,考察随机市场需求对定价、库存及利润的影响,分析具有不同博弈地位的供应链策略差异,并通过数值仿真探讨最佳响应策略。结果表明,主导方凭借地位优势拥有更强的价格把控权及库存调配能力,获得更高收益;制造商主导型供应链具有更强的渠道整合能力,供应链的整体利润水平高于零售商主导型;同等博弈地位情形的博弈双方可根据共同市场信息及竞争对手策略更新自身策略,具有较低的库存风险,渠道定价越低,但双重边际效应降低了双方收益;市场需求波动越大,渠道定价、库存量及供应链利润均越大,此时主导方利润增幅大于追随者。     

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.     

Using simulation-based system dynamics and genetic algorithms to reduce the cash flow bullwhip in the supply chain

The bullwhip effect (BWE) is a phenomenon, which is caused by ineffective inventory decisions made by supply chain members. In addition to known inefficiencies caused by the bullwhip effect within a supply chain product flow, such as excessive inventory, it can also lead to inefficiencies in cash flow such as the cash flow bullwhip (CFB). The CFB reduces the efficiency of the supply chain (SC) through heterogeneous distribution of cash among supply chain members. This paper aims to decrease both the BWE and the CFB across a SC through applying a simulation-based optimisation approach, which integrates system dynamics (SD) simulation and genetic algorithms. For this purpose, cash flow modelling is incorporated into the SD structure of the beer distribution game (BG) to develop the CFB function. A multi objective optimisation model is then integrated with the SD-BG simulation model. Finally, a genetic algorithm (GA) is applied to determine the optimal values for the inventory, supply line, and financial decision parameters. Results show that the proposed integrated framework leads to efficient liquidity management in the SC in addition to cost management.     

The bullwhip effect on product orders and inventory: a perspective of demand forecasting techniques

Demand forecasting is one of the key causes of the bullwhip effect on product orders. Although this aspect of order oscillation is not ignored, the current study focuses on another critical aspect of oscillation: the bullwhip effect on inventory, i.e. the net inventory variance amplification. In particular, this paper studies a two-level supply chain in which the demand is price sensitive, while the price follows a first-order autoregressive pricing process. We derive the analytical expressions of the bullwhip effect on product orders and inventory using minimum mean-squared error, moving average and exponential smoothing forecasting techniques. We also propose the conditions under which the three forecasting techniques would be chosen by the retailer to minimise the sum of the bullwhip effect on product orders and inventory under different weightings. These observations are used to develop managerial insights regarding choosing an appropriate forecasting technique after considering certain distinct characteristics of the product.     

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。     

Inventory performance of some supply chain inventory policies under impulse demands

This paper attempts to study the impact of impulsive demand disturbances on the inventory-based performance of some inventory control policies. The supply chain is modelled as a network of autonomous supply chain nodes. The customer places a constant demand except for a brief period of sudden and steep change in demand (called demand impulse). Under this setting, the behaviour of each inventory policy is analysed for inventory performance of each node. It is found that the independent decision-making by each node leads to a bullwhip effect in the supply chain whereby demand information is amplified and distorted. However, under a scenario where the retailer places a constant order irrespective of the end customer demand, the inventory variance was actually found to decrease along the supply chain. The variance of the inventory remained constant along the chain when only the actual demands are transmitted by each node. The results also showed that the inventory policy which is best for one supply chain node is generally less efficient from a supply chain perspective. Moreover, the policy which performs poorly for one node can be most efficient for the supply chain. In a way, our results also provide a case for coordinated inventory management in the supply chain where all members prepare a joint inventory management policy that is beneficial for all the supply chain nodes. The results have significant industrial implications.     

Supply chain design and cost analysis through simulation

This paper is grounded on a discrete-event simulation model, reproducing a fast moving consumer goods (FMCG) supply chain, and aims at quantitatively assessing the effects of different supply configurations on the resulting total supply chain costs and bullwhip effect. Specifically, 30 supply chain configurations are examined, stemming from the combination of several supply chain design parameters, namely number of echelons (from 3 to 5), re-order and inventory management policies (EOQ vs. EOI), demand information sharing (absence vs. presence of information sharing mechanisms), demand value (absence vs. presence of demand ‘peak’), responsiveness of supply chain players. For each configuration, the total logistics costs and the resulting demand variance amplification are computed. A subsequent statistical analysis is performed on 20 representative supply chain configurations, with the aim to identify significant single and combined effects of the above parameters on the results observed. From effects analysis, bullwhip effect and costs outcomes, 11 key results are derived, which provide useful insights and suggestions to optimise supply chain design.     

The impact of consumer price forecasting behaviour on the bullwhip effect

As prices fluctuate over time, a strategic consumer may buy more in advance to reduce his or her future needs in anticipation of higher prices in the future, or may choose to postpone a purchase in anticipation of lower prices in the future. We investigate the bullwhip effect from a consumer price forecasting behavioural perspective in the context of a simple two-level supply chain composed of a supplier and a retailer. We consider two different forms for the demand function – linear and iso-elastic demand functions, both depending on the prices in multiple periods. Assuming that the retailer employs an order-up-to inventory policy with exponential smoothing forecasting technology, we derive analytical expressions for the bullwhip effect under the two demand functions, and extend the results to the multiple-retailer case. We find that consumer forecasting behaviour can reduce the bullwhip effect, most significantly when the consumer sensitivity to price changes is medium (approximately 0.5) for both the demand forms. In addition, for iso-elastic demand, the mitigation of the bullwhip effect induced by consumer price forecasting behaviour becomes more significant as the product price sensitivity coefficient and standard deviation of the price decrease. These findings are applicable to the development of managerial strategies by supply chain members that are conducive to bullwhip effect reduction through customer behaviour.     

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.     

资金约束时零售商融资与订货决策及价值分析

针对供应链中存在资金约束的情形,建立了包含制造商（M）、零售商（R）双层结构、不考虑残次品率、库存成本和融资周期长短的简洁供应链决策模型。研究了当市场需求不确定和零售商资金不足情形下,零售商选择是否融资这两种情况下,其订货决策的变化,以及零售商和制造商的收益变化。通过有无融资条件下零售商不同数量自有资金时订货量和期望收益对比和零售商自有资本一定时订货量随周期变化的数值分析,证明了零售商的融资决策与订货量决策会随着其自有资金及市场需求的变化而变化;验证了融资可以提高零售商和供应链的收益,而且能够使得供应链的总产品尽快达到最佳产量,有效满足消费者需求。     

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.     

The bullwhip effect on inventory under different information sharing settings based on price-sensitive demand

Information sharing (IS) is proved to be a valid method to counter demand variability amplification along the supply chain, or bullwhip effect (BWE). Different from the traditional way of measuring the BWE based on order quantity, we measure the BWE on inventory in different IS settings and try to find the best IS approach. In this paper, the retailer will face the market demand which is price-sensitive, and the price follows a first-order autoregressive process. This demand model includes some indexes that can provide more useful managerial insights than previously studied parameters. Our study identifies the best IS setting under any conditions, and clarifies that the benefits of IS will be evident when the overall market product pricing process is highly correlated over time, the demand shocks to the retailer are high, the price sensitivity coefficient is small, the overall market shocks are low, the retailer’s lead-time is long and the manufacturer’s lead-time is short.     

Revisiting rescheduling: MRP nervousness and the bullwhip effect

We study the material requirements planning (MRP) system nervousness problem from a dynamic, stochastic and economic perspective in a two-echelon supply chain under first-order auto-regressive demand. MRP nervousness is an effect where the future order forecasts, given to suppliers so that they may plan production and organise their affairs, exhibits extreme period-to-period variability. We develop a measure of nervousness that weights future forecast errors geometrically over time. Near-term forecast errors are weighted higher than distant forecast errors. Focusing on replenishment policies for high volume items, we investigate two methods of generating order call-offs and two methods of creating order forecasts. For order call-offs, we consider the traditional order-up-to (OUT) policy and the proportional OUT policy (POUT). For order forecasts, we study both minimum mean square error (MMSE) forecasts of the demand process and MMSE forecasts coupled with a procedure that accounts for the known future influence of the POUT policy. We show that when retailers use the POUT policy and account for its predictable future behaviour, they can reduce the bullwhip effect, supply chain inventory costs and the manufacturer’s MRP nervousness.     

多供应商、多销售商的两级供应链库存模型研究

研究多个供应商、多个销售商组成的两级供应链的库存系统,在具有价格弹性的市场需求、允许供应商和销售商产生缺货的条件下,针对有无价格折扣的两种情况,分别建立了供应商、销售商各自的库存模型;结合满足供应商和销售商Pareto有效性,建立了含价格折扣的供应链系统整体盈利最大的库存模型.     

Dynamic analysis and design of a semiconductor supply chain: a control engineering approach

The combined make-to-stock and make-to-order (MTS-MTO) supply chain is well-recognised in the semiconductor industry in order to find a competitive balance between agility, including customer responsiveness and minimum reasonable inventory, to achieve cost efficiency while maintaining customer service levels. Such a hybrid MTS-MTO supply chain may suffer from the bullwhip effect, but few researchers have attempted to understand the dynamic properties of such a hybrid system. We utilise a model of the Intel supply chain to analytically explore the underlying mechanisms of bullwhip generation and compare its dynamic performance to the well-known Inventory and Order-Based Production Control System (IOBPCS) archetype. Adopting a control engineering approach, we find that the feedforward forecasting compensation in the MTO element plays a major role in the degree of bullwhip and the Customer Order Decoupling Point (CODP) profoundly impacts both the bullwhip effect and the inventory variance in the MTS part. Thus, managers should carefully tune the CODP inventory correction and balance the benefit between CODP inventory and bullwhip costs in hybrid MTS-MTO supply chains.     

Bullwhip and inventory variance in a closed loop supply chain

A simple dynamic model of a hybrid manufacturing/remanufacturing system is investigated. In particular we study an infinite horizon, continuous time, APIOBPCS (Automatic Pipeline Inventory and Order Based Production Control System) model. We use Åström’s method to quantify variance ratios in the closed loop supply chain. Specifically we highlight the effect of a combined “in-use” and remanufacturing lead-time and the return rate on the inventory variance and bullwhip produced by the ordering policy. Our results clearly show that a larger return rate leads to less bullwhip and less inventory variance in the plant producing new components. Thus returns can be used to absorb demand fluctuations to some extent. Longer remanufacturing and “in-use” lead-times have less impact at reducing inventory variance and bullwhip than shorter lead-times. We find that, within our specified system, that inventory variance and bullwhip is always less in supply chains with returns than supply chains without returns. We conclude by separating out the remanufacturing lead-time from the “in-use” lead-time and investigating its impact on our findings. We find that short remanufacturing lead-times do not qualitatively change our results.