A supply chain as a series of filters or amplifiers of the bullwhip effect

The bullwhip effect refers to the phenomenon of amplification and distortion of demand in a supply chain. By eliminating or controlling this effect, it is possible to increase product profitability reducing useless costs such as stock-out and obsolescence costs. The main focus of this work is to study a single-product serial supply chain in which a control parameter can switch the chain from a series of filters to a series of amplifiers of the bullwhip effect and to analyse how the optimal values of the parameters change when discontinuities in order policy are considered. Furthermore, it is also shown that the bullwhip itself it is not a good index of the chain's performance, because it does not consider the oscillations that occur in the inventories, which also may affect the supply-chain performance.     

An analysis of the main factors affecting bullwhip in reverse supply chains

The bullwhip effect has drawn the attention of supply chains researchers due to the inefficiencies that this phenomenon generates upstream in the supply chain. Various factors that facilitate its appearance have been identified in the literature. However, in spite of current practices and new environmental regulations having increased the importance of returned material chains, this phenomenon has not been studied in detail in the context of closed loop networks. Here we present an analysis of the influence of factors identified as significant with regard to the bullwhip effect in forward chains on the appearance of the bullwhip effect in environments of reverse logistics and its pattern of evolution along the chain. We do so by using a simulator that extends the logic of the Beer Game to this type of environment. The results confirm the influence of the majority of the factors considered, especially the stock and WIP adjustment controllers, as well as the forecasting technique used, the sharing of information among the links, and the final customer demand variability. With respect to specific reverse supply chains factors, the only significant one identified is the percentage of units returned. We have also studied the factors that in this closed loop environment give rise to the classical upstream growing pattern of the bullwhip effect, observing that an increase in the percentage of material returned reduces the likelihood of finding a growing bullwhip pattern. In addition, it is more likely for this pattern to appear when the demand variation is low.     

基于促销行为的供应链牛鞭效应分析

供应链中的牛鞭效应起源于管理者追求利润最大化的理性决策,价格波动是产生牛鞭效应的主要原因之一,而价格波动常常是由零售商周期性地采取一些特殊促销行为引起的.本文通过考虑在动态需求环境下,存在一个包含有一个供应商与一个零售商的简单供应链,当下游零售商有促销行为时与无促销行为时进行定量分析比较,并分析基于促销行为的零售商收益大于库存成本时的牛鞭效应,结果表明,零售商的促销行为很大程度上加剧了牛鞭效应,只有当产品价格比较稳定时,才能尽量避免和减少牛鞭效应.     

The role of elasticity in supply chain performance

This paper develops a model that describes the performance of supply chains based on their elasticities of supply and demand. The model can be used to predict a supply chain's ability to respond to supply interruptions, cost increases, and demand shifts, while also quantifying the degree to which it is prone to the bullwhip effect. The bullwhip effect is a behavioral phenomenon by which orders are distorted as they are transmitted through the chain. Four types of supply chains are identified and their distinct operating characters are examined. The impact of rival firms and the impact of a decoupling point on supply chain performance are also examined.     

基于SD的牛鞭效应建模与仿真分析

通过建立一个三级供应链系统的SD模型,研究探讨牛鞭效应的产生机制及弱化途径。仿真结果表明,牛鞭效应很大程度上是供应链体系自身的特点和结构造成的,而采用具有信息共享机制的VMI订货模式可以大大弱化牛鞭效应,能够有效降低供应链各节点的库存成本。     

The analysis of bullwhip effect in a HMMS-type supply chain

The aim of the paper is to investigate the well-known bullwhip effect of supply chains. Control theoretic analysis of bullwhip effect is extensively analyzed in the literature with the Laplace transform. This paper tries to examine the effect for an extended Holt-Modigliani-Muth-Simon model. A two-stage supply chain (supplier-manufacturer) is studied with quadratic costs functional. It is assumed that both firms minimize the relevant costs. The order of the manufacturer is delayed with a known constant. Two cases are examined: supplier and manufacturer minimize the relevant costs decentralized, and a centralized decision rule. The question is answered, how to decrease the bullwhip effect.     

Ordering and pricing policies in a manufacturing and distribution supply chain for fashion products

In the paper, we develop a model of manufacturing and distribution supply chains that are operating to meet price-sensitive random demand for products with short life cycles such as fashion products. Two specific scenarios are considered. The manufacturer-controlled scenario is one where the distributor shares price-sensitive random demand with the manufacturer, and the manufacturer controls the supply chain stocking decisions and bears the risk of overstocking costs. The distributor-controlled scenario works in the opposite direction. Prevailing wisdom suggests that the manufacturer should control supply chain decisions (e.g., via vendor-managed inventory). Our results indicate that such an arrangement is against the interest of a distributor selling short life-cycle products. Furthermore, we find that the total supply chain profit is generally higher when the distributor controls the supply chain stocking decisions and bears the risk of overstocking costs.     

Robust supply chain management

Faced with uncertainty, researchers have explored concepts such as robustness, flexibility, information structure, options, and market power for supply chain management. Despite many influential findings, such as the presence of the bullwhip effect and channel power, the literature in supply chain management is a bit confusing with regard to these concepts, including how they are related to each other. In light of this, we discuss the meaning of the terms in a supply chain management context. We indicate what questions are at stake and some pitfalls to be aware of if the phenomenon we are concerned about is affected by strategic players. This paper is modelling focused.     

Efficient versus Responsive Supply Chain Choice: An Empirical Examination of Influential Factors

Contemporary strategies in operations management suggest that successful firms align supply chain assets with product demand characteristics in order to exploit the profit potential of product lines fully. However, observation suggests that supply chain assets often are longer lived than product line decisions. This suggests that alignment between supply chain assets and demand characteristics is most likely to occur at the time of initial market entry. This article examines the association between product demand characteristics and the initial investment in a supply chain at the time of market entry. We characterize supply chains as responsive or efficient. A responsive supply chain is distinguished by short production lead‐times, low set‐up costs, and small batch sizes that allow the responsive firm to adapt quickly to market demand, but often at a higher unit cost. An efficient supply chain is distinguished by longer production lead‐times, high set‐up costs, and larger batch sizes that allow the efficient firm to produce at a low unit cost, but often at the expense of market responsiveness. We hypothesize that a firm's choice of responsive supply chain will be associated with lower industry growth rates, higher contribution margins, higher product variety, and higher demand or technological uncertainty. We further hypothesize that interactions among these variables either can reinforce or can temper the main effects. We report that lower industry growth rates are associated with responsive market entry, but this effect is offset if growth occurs during periods of high variety and high demand uncertainty. We report that higher contribution margins are associated with responsive market entry and that this effect is more pronounced when occurring with periods of high variety. Finally, we report that responsive market entry also is correlated positively with higher technological demand uncertainty. These results are found using data from the North American mountain bike industry.     

A holistic network model for supply chain analysis

Supply chain researchers are experiencing a conceptual and analytical paradox. They are asked to move beyond dyadic analyses and investigate larger network effects with only a limited analytical toolkit. This research proposes the use of bilinear mixed-modeling to holistically analyze supply chain phenomena. Through this approach, researchers are able to account for multiple supply chain relationships, higher-order dependencies among member firms, and simultaneously evaluate covariates from buyer and seller perspectives. The model is validated through the lens of a pervasive supply chain problem commonly referred to as the bullwhip effect. A sample of firms from the US apparel industry in 2004 is analyzed and then the findings are confirmed using data from 2005. In addition to validating the model through the presence of the bullwhip effect, the bilinear model illuminates variables such as advertising, price deals, inventory turnover, and inventory backlogs that exacerbate or diminish inventory differences between firms in a supply chain. The results extend research on supply networks and supply efficiency to a more holistic level and show that higher-order dependencies are important drivers of supply chain phenomena.     

Optimization analysis of supply chain scheduling in mass customization

How to deal with the contradiction between scale production effect and customized demand is the key problem on studying mass customization (MC). When MC is operating in supply chain environment, on one hand, the excellent operating character of the supply chain will give conditions for solving this problem. On the other hand, it will bring out several complicated contradictions and increase the difficulties of the analysis and research on the supply chain operating and scheduling, so it is important to settle the contradictions. Based on our earlier work, the dominant contradictions of the supply chain scheduling in MC and the ways to relieve them are briefly summarized in this paper. A dynamic and multi-objective optimization mathematical model and the appropriate solving algorithm are set up by introducing these relieving methods into the operating process. It is pointed out that the characteristics of the model and algorithm cannot only reflect the unique operating requirements for this special production mode, but also merge with the thought of relieving the dominant contradictions. The feasibility of the model and algorithm in practical application to improve the scheduling efficiency and to settle the key problem mentioned above ultimately gets validated through the analysis of an application case we followed and through the algorithm simulation of a numerical scheduling case.     

The Impact of Recent Gas Market Developments on Long-Term Projections for Global Gas Supply

Production from unconventional resources, increases in upstream development costs and sluggish demand growth have significantly impacted the global natural gas market in the recent past; and will likely continue to do so during the next decade. Taking these developments into account, we provide a projection of global natural gas supply until 2030 applying the MAGELAN world gas model by the Institute of Energy Economics at the University of Cologne (EWI). Apart from presenting the results of this simulation, the focus of this paper is thereby on the effects of recent supply, midstream and demand side trends on future gas supply compared to earlier studies and projections. While lower demand growth generally leads to relatively less international gas trade, pipeline exports are affected more strongly than trade in liquefied natural gas. In terms of gas output, this volume effect is found to mainly affect high cost gas producers at the upper end of the supply curve. Exports of suppliers with lower production costs and abundant reserves actually benefit.     

A dynamic model for the optimization of decoupling point and production planning in a supply chain

In this paper, we propose a dynamic model to simultaneously determine the optimal position of the decoupling point and production-inventory plan in a supply chain such that the total cost of the deviation from the target production rate and the target inventory level is minimized. Using the optimal control theory, we derive the closed form of the optimal solution when the production smoothing policy and the zero-inventory policy are applied. The result indicates that under the production smoothing policy, the overestimation of demand rate during the pre-decoupling stage guarantees the existence of the optimal decoupling point; meanwhile the optimal decoupling point exists under zero-inventory policy when the demand rate is underestimated. Also we perform mathematical analysis on the behavior of the optimal production rate and the inventory level and the effect of problem parameters such as the length of the product life cycle and the forecast error on the performance.     

Service-based capacity strategy for manufacturing service duopoly of differentiated prices and lognormal random demand

Globalization of production has ushered in vibrant manufacturing service industries whose business is to serve the production needs of product engineering firms. In these engineering–manufacturing chains, risk of capacity supply is an important concern for product firms as manufacturers are normally conservative in capacity expansion, especially when demand uncertainty and investment risk are high. To provide quality manufacturing services, this risk must be taken into consideration in formulating a capacity strategy. This paper presents a competition analysis method based on supply risk for a manufacturing duopoly of differentiated prices and lognormal random demand. A novel service-based demand rationing rule is first proposed. Reaction curves and equilibrium of capacity strategy are next derived. Finally, competition behavior of the duopoly is analyzed.     

云制造环境下制造能力共享的动态策略分析

本文在物联网环境下,考虑制造商剩余制造能力共享的动态性及对需求产生的影响,借助微分博弈研究了单个云平台和制造商构成的两级供应链制造能力共享问题。分析了供应链中制造商占主导的Stackelberg博弈、纵向合作以及云平台提出成本分担契约的情形,构建了相应的动态模型,得到反馈均衡策略及利润;发现合作共享能提高供应链整体利润,一定条件下实施的成本分担契约能实现供应链的协调;最后,通过数值分析,验证了结论的有效性。     

A firm's capability to calibrate supply chain knowledge—Antecedents and consequences

This paper proposes a conceptual model for a firm's capability to calibrate supply chain knowledge (CCK). Knowledge calibration is achieved when there is a match between managers’ ex ante confidence in the accuracy of held knowledge and the ex post accuracy of that knowledge. Knowledge calibration is closely related to knowledge utility or willingness to use the available ex ante knowledge: a manager uses the ex ante knowledge if he/she is confident in the accuracy of that knowledge, and does not use it or uses it with reservation, when the confidence is low. Thus, knowledge calibration attained through the firm's CCK enables managers to deal with incomplete and uncertain information and enhances quality of decisions. In the supply chain context, although demand- and supply-related knowledge is available, supply chain inefficiencies, such as the bullwhip effect, remain. These issues may be caused not by a lack of knowledge but by a firm's lack of capability to sense potential disagreement between knowledge accuracy and confidence. Therefore, this paper contributes to the understanding of supply chain knowledge utilization by defining CCK and identifying a set of antecedents and consequences of CCK in the supply chain context.     

Integration of financial statement analysis in the optimal design of supply chain networks under demand uncertainty

Models that aim to optimize the design of supply chain networks have become a mainstream in the supply chain literature. This paper aims to fill a gap in the literature by introducing a mathematical model that integrates financial considerations with supply chain design decisions under demand uncertainty. The proposed Mixed-Integer Linear Programming (MILP) problem enchases financial statement analysis through financial ratios and demand uncertainty through scenario analysis. The applicability of the model is illustrated by using a case study along with a sensitivity analysis on financial parameters expressing the business environment. The model could be used as an effective and convenient strategic decision tool by supply chain managers.     

Competition under capacitated dynamic lot-sizing with capacity acquisition

Lot-sizing and capacity planning are important supply chain decisions, and competition and cooperation affect the performance of these decisions. In this paper, we look into the dynamic lot-sizing and resource competition problem of an industry consisting of multiple firms. A capacity competition model combining the complexity of time-varying demand with cost functions and economies of scale arising from dynamic lot-sizing costs is developed. Each firm can replenish inventory at the beginning of each period in a finite planning horizon. Fixed as well as variable production costs incur for each production setup, along with inventory carrying costs. The individual production lots of each firm are limited by a constant capacity restriction, which is purchased up front for the planning horizon. The capacity can be purchased from a spot market, and the capacity acquisition cost fluctuates with the total capacity demand of all the competing firms. We solve the competition model and establish the existence of a capacity equilibrium over the firms and the associated optimal dynamic lot-sizing plan for each firm under mild conditions.     

Variance amplification and the golden ratio in production and inventory control

A discrete linear control theory model of a generic model of a replenishment rule is presented. The replenishment rule, which we term a “Deziel Eilon—automatic pipeline, inventory and order-based production control system”, is guaranteed to be stable. From a z-transform model of the policy, an analytical expression for bullwhip is derived that is directly equivalent to the common statistical measure often used in simulation, statistical and empirical studies to quantify the bullwhip effect. This analytical expression clearly shows that we can reduce bullwhip by taking a fraction of the error between the target and actual inventory and pipeline (or work in progress (WIP) or “orders placed but not yet received”) positions. This is in contrast to the common situation where ordering policies account for all of the error every time an order is placed. Furthermore, increasing the average age of the forecast reduces bullwhip, as does reducing the production/distribution lead-time. We then derive an analytical expression for inventory variance using the same procedure to identify the closed form bullwhip expression.We assume that a suitable objective function is linearly related to the bullwhip and inventory variance amplification ratios and then optimise the PIC system for different weightings of order rate and inventory level variance. We highlight two forms of the objective function, one where “the golden ratio” can be used to determine the optimal gain in the inventory and WIP feedback loop and another that allows the complete range of possible solutions to be visualised. It is interesting that the golden ratio, which commonly describes the optimum behaviour in the natural world, also describes the optimal feedback gain in a production and inventory control system.     

国内精对苯二甲酸产业的发展及供需预测

精对苯二甲酸(PTA)是聚酯生产的重要原料,也是聚酯产业链中的关键产品。重点分析了十一五期间国内PTA产业供需及盈利情况,对十二五期间国内PTA产业的供需趋势进行了预测,并对PTA产业的健康发展提出了建议。