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.     

The bullwhip effect in capacitated supply chains with consideration for product life-cycle aspects

This paper presents an analysis of the bullwhip effect and net-stock amplification in a three-echelon supply chain considering step-changes in the production rates during a product's life-cycle demand. The analysis is focused around highly complex and engineered products (e.g., automobiles), that have relatively long production life-cycles and require significant capital investment in manufacturing. Using a simulation approach, we analyze three stages of the product life-cycle including low volumes during product introduction, peak demand, and eventual decline toward the end of the life-cycle. Parts of the simulation model have been adopted by a major North-American automotive OEM as part of a scenario analysis tool for strategic supply network design and analysis. The simulation results show that performance of a system as a whole deteriorates when there is a step-change in the life-cycle demand. While restriction in production capacity does not significantly impact the bullwhip effect, it increases the net stock amplification significantly for the supply chain setting under consideration. Furthermore, a number of important managerial insights are presented based on sensitivity analysis of interaction effect of capacity constraints with other supply chain parameters.     

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.     

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.     

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。     

An empirical analysis of supply chain risk management in the German automotive industry

The purpose of this paper is the empirical analysis of supply chain risk management practices. The analysis is based on a survey with 67 manufacturing plants conducted in the German automotive industry. After investigating the vulnerability of supply chains in general and examining key drivers of supply chain risks, the paper identifies supply chain risks by analyzing their likelihood to occur and their potential impact on the supply chain. The results are visualized in the probability-impact-matrix distinguishing between internal and external supply chain risks. Furthermore, instruments for dealing with supply chain risks are investigated. Therefore, the impact of supply chain risk management on performance is tested. In order to distinguish between companies with a high degree of supply chain risk management and those with no or only limited implementation the plants are grouped by means of a cluster analysis based on factors reflecting the instruments of supply chain risk management. In particular, groups are created representing two different approaches to deal with supply chain risks, i.e. reactive and preventive supply chain risk management. The clusters are investigated concerning differences in terms of performance criteria. The analyses reveal that companies with a high implementation degree show a better supply chain performance. Furthermore, the results show that the group using reactive supply chain risk management has higher average value in terms of disruptions resilience or the reduction of the bullwhip effect, whereas the group pursuing preventive supply chain risk management has better values concerning flexibility or safety stocks.     

Inventory performance under pack size constraints and spatially-correlated demand

Motivated by a problem facing a large retailer, we consider the impact of pack size on the performance of a periodic review inventory system in the presence of spatial (i.e., between retailers) correlation of demand—which we model using an equicorrelated multivariate Poisson distribution. Employing simulation, we utilise a full factorial experiment to provide support for decisions on product and supplier selection, and whether or not packs should be split during distribution. We consider variables such as pack size, correlation, and the number of branches, and discuss how they and their interactions impact performance metrics such as inventory and shortage levels and the bullwhip effect.     

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.     

A comparative analysis of greening policies across supply chain structures

In this paper, we examine an apparel serial supply chain whose players initiate product “greening.” We consider situations in which the players cooperate or act individually. Our problem is motivated by recent developments in the supply chains of global apparel players. We build game theoretic models and show how greening levels, prices and profits are influenced by channel structures. We also study the impact of greening costs and consumer sensitivity towards green apparels. We propose a two-part tariff contract to coordinate the green channel. Our key contribution lies in the model of decision making of various supply chain structures and analyzing its impact on the players and supply chain. The problem throws interesting insights into the strategies of apparel players and their key decisions.     

How should you stabilise your supply chains?

This case based research paper examines the stabilisation strategies used within seven supply chains and presents a framework to help practitioners stabilise their chains. The findings show that organisations should first select a cushioning strategy and then reduce demand uncertainty to lower the level of cushion held. However, they need to recognise that other organisations within the supply chain are making similar decisions and the whole supply chain needs to be stabilised. Despite this, businesses seem to only share information about their demand uncertainty-reducing mechanisms and not their cushioning strategies. This means that companies often make decisions in isolation of each other, which can then destabilise the chain.     

Facilitating artificial intelligence powered supply chain analytics through alliance management during the pandemic crises in the B2B context

The COVID-19 pandemic has disrupted global supply chains and exposed weak links in the chains far beyond what most people have witnessed in their living memory. The scale of disruption affects every nation and industry, and the sudden and dramatic changes in demand and supply that have occurred during the pandemic crisis clearly differentiate its impact from other crises. Using the dynamic capabilities view, we studied alliance management capability (AMC) and artificial intelligence (AI) driven supply chain analytics capability (AI-SCAC) as dynamic capabilities, under the moderating effect of environmental dynamism. We tested our four research hypotheses using survey data collected from the Indian auto components manufacturing industry. For data analysis we used Warp PLS 7.0 (a variance-based structural equation modelling tool). We found that alliance management capability under the mediating effect of artificial intelligence-powered supply chain analytics capability enhances the operational and financial performance of the organization. Moreover, we also observed that the alliance management capability has a significant effect on artificial intelligence-powered supply chain analytics capability under the moderating effect of environmental dynamism. The results of our study provide a nuanced understanding of the dynamic capabilities and the relational view of organization. Finally, we noted the limitations of our study and provide numerous research directions that may help answer some of the questions that arise from our study.     

Aligning the sustainable supply chain to green marketing needs: A case study

The research explores the challenges facing organisations in aligning sustainable procurement requirements and marketing needs and the attendant shifts in supply chain management practices. Whilst external influences are readily understood (e.g. regulation and customer demand), less is understood about the implications for suppliers trying to meet sustainable procurement requirements and the organisational challenges of aligning marketing with sustainable supply chain management. An exploratory case study of a UK University catering department has been undertaken, to explore the strategies, processes and relationships associated with synthesising sustainable supply chain and green marketing needs. The empirical findings illustrate the divergence between organisational perspectives on sustainability and procuring sustainable products with marketing demands. Thus, the findings extend the theoretical discussion on sustainable supply chains by providing empirical data based on real-life implementation and from this an emergent aligned supply chain model is proposed, which confirms two drivers for alignment, ‘lean and resource efficient’ and ‘local and seasonal’ — contingent on market demand. The findings emphasise the benefits of a reverse information flow, the importance of intermediaries, and relationships in its fulfilment, while indicating the resurgence of a supply ‘push’ of sustainable products into core markets. Future research directions are also posited.     

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.     

In Chains? An Empirical Study of Antecedents of Supplier Product Development Activity in the Automotive Industry*

In the literature on interorganizational collaboration in product development, considerable attention is given to supplier role classifications. Such classifications often link to a supplier's position in the overall supply chain, but the claim that this position has a substantial impact on its product development activities has seldom been empirically validated. The results from the present survey among Swedish automotive suppliers demonstrate that supplier product development activity is significantly affected by the position of the supplier in the supply chain and the supplier's strategic focus on innovation. While the latter has a stronger impact on product development activities, there is also an interaction effect implying that the effects of a supplier's innovation strategy are contingent on its supply chain position. Contrary to expectations, customer development commitment does not have any significant direct effect on supplier product development activities. Instead, this relation is fully mediated by supplier innovation strategy. These findings imply that, in contrast to conventional wisdom, product development activities are not strictly organized in “chains.” Although supply chains can be useful metaphors for understanding the distribution of regular production activities between firms, they arguably apply less to the distribution of product development activities.     

Structuring and contracting in competing supply chains

This paper considers two competing supply chains, each with multiple upstream suppliers producing complementary products and selling to a single buyer (e.g., assembler or retailer), who then sells the finished assembled product to a market that involves both demand uncertainty and competition. Our main research questions focus on what supply chain structure (integration vs. decentralization) and which contracting strategy a business should choose. We find that supply chains that decentralize perform better under strong market competition (i.e., high degree of product substitution between supply chains). However, when a large number of suppliers exist, supply chains that integrate perform better. When decentralized structures are used for both supply chains, a consignment with revenue sharing contract generally outperforms a wholesale price contract from the downstream retailer's point of view. Interestingly, for a supplier, a wholesale price contract, which pushes all demand risks to the downstream retailer, might not be preferred. For the entire supply chain, one contract strategy can outperform another depending on the degree of competition, the cost share of the buyer, and the number of suppliers.     

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.     

Impact of demand uncertainty on supply chain cooperation of single-period products

Cooperation is an approach of improving competitive advantages of a supply chain. A two-echelon supply chain consisting of a manufacturer and a retailer for a single-period product is studied, and retail-market demand uncertainty is described by coefficient of variation. We develop a cooperation mechanism to address the cooperation and its implementation between the manufacturer and the retailer, two market situations are considered: (i) the wholesale price and the order quantity are decision variables, (ii) the wholesale and the retail prices as well as the order quantity are decision variables. In both market situations, our research shows that: (1) the cooperation mechanism can improve the overall channel profits and the supply chain members’ allocated profits, (2) the described cooperation is conditional on retail-market demand uncertainty: it can be implemented if, and only if, the fluctuation of retail-market demand is relatively small and coefficient of variation of retail-market demand does not exceed an upper bound. Impacts of retail-market demand uncertainty on wholesale price, order quantity and/or retail price have also been investigated through analytical and numerical analyses. Although our research is based on the assumption that the manufacturer dominates the supply chain in the non-cooperative situation, which is not the case for most retailer-driven supply chains, this research is still significant on providing guidelines for practitioners in current China mid-level car market that is similar to situations described in the paper.     

A hierarchical process industry production–distribution planning model

Global and multinational companies are subject to government regulations in addition to other international uncertainties due to operation in diverse geographic locations. Such government regulations often affect the cost of raw materials adversely which in turn creates adverse impact on product cost and forces the decision makers to re-evaluate current production–distribution plan. This paper presents an integrated supply chain model for simultaneous strategic and operational planning of a strategic business unit (SBU) in a global supply chain affected by government regulations. The model incorporates impact of changes in cost of inputs on expected product cost and solves for an optimal strategic and operational plan for the entire supply chain. In addition, the model includes exchange rates, border crossing costs and solves a multi-period model with due consideration of uncertainties in demand and transportation time.