CAMPBELL SOUP'S CONTINUOUS REPLENISHMENT PROGRAM: EVALUATION AND ENHANCED INVENTORY DECISION RULES

Campbell Soup's continuous replenishment (CR) program is a novel innovation designed to improve the efficiency of inventory management throughout the supply chain. With CR (1) retailers pay a constant wholesale price but continue to participate in consumer promotions, (2) retailers transmit to the supplier daily inventory information via electronic data interchange (EDI), and (3) the supplier assumes responsibility for managing retailer inventories, i.e., vendor managed inventories (VMI). We develop simple inventory management rules to operate CR, and we test these rules with a simulation using actual demand data provided by Campbell Soup. On this sample we find that retailer inventories were reduced on average by 66% while maintaining or increasing average fill rates. This improvementreduces a retailer's cost of goods sold by 1.2%, which is significant in the low profitmargin grocery industry. Furthermore, these savings could have been achieved without VMI.     

Beyond Information Sharing: An Empirical Analysis of Vendor‐Managed Inventory

Using a unique, item‐level data set, we examined benefits to downstream firms (distributors) from the decision‐transfer component of vendor‐managed inventory (VMI), the feature that distinguishes VMI from other information‐sharing, collaborative supply chain programs. Our major findings are that the decision‐transfer component of VMI adds significant benefits to the downstream firm in terms of inventory and stockout reductions above and beyond information sharing, and that these two benefits may be realized at different times following VMI implementation; that is, inventory reduction, initially, may be the major benefit to distributors from VMI, while the benefits of stockout reduction may more likely be realized after the first year of implementation. In addition, VMI provides benefits to the upstream firm (manufacturer) by reducing the downstream firm's inventory variability, a likely contributor to the bullwhip effect. Based on our empirical analysis, the decision‐transfer component of VMI, on average, reduces inventory levels by 7%, stockouts by 31%, and inventory variability by 9%.     

Contracting in a Supply Chain with Stochastic Demand and Substitute Products

Retailers often stock competing products from multiple manufacturers. When the retailer stocks out of a particular item, customers who prefer the item are likely, with some probability, to switch to a substitute product from another manufacturer at the same store. In such an event, a “lost sale” for the manufacturer is not a “lost sale” for the retailer. This exacerbates differences in manufacturer's and retailer's stockout costs for the item. Such differences in stockout cost influence the optimal contract between the manufacturer and the retailer and also impose agency costs on the channel. Such contracts, in turn, determine equilibrium inventory levels and fill rates. We study these issues in a single‐period supply chain, consisting of a manufacturer and a retailer, under three different scenarios (when the two firms are integrated into a single entity, when the retailer makes stocking decisions, and when the manufacturer makes stocking decisions). We compare, and present a methodology for comparing, stocking quantities, manufacturer efforts, and supply chain profits across different scenarios. We find that VMI performs better when manufacturer effort is a substantial driver of consumer demand and when consumers are unlikely to substitute to another brand in case of a stockout. On the other hand, if non‐contractible manufacturer effort is unimportant, or when substitution is significant, VMI can exacerbate, rather than mitigate, channel inefficiencies, and can perform worse than traditional Retailer Managed Inventory.     

Dynamic Pricing,Production, and Channel Coordination with Stochastic Learning

We consider a decentralized two‐period supply chain in which a manufacturer produces a product with benefits of cost learning, and sells it through a retailer facing a price‐dependent demand. The manufacturer's second‐period production cost declines linearly in the first‐period production, but with a random learning rate. The manufacturer may or may not have the inventory carryover option. We formulate the resulting problems as two‐period Stackelberg games and obtain their feedback equilibrium solutions explicitly. We then examine the impact of mean learning rate and learning rate variability on the pricing strategies of the channel members, on the manufacturer's production decisions, and on the retailer's procurement decisions. We show that as the mean learning rate or the learning rate variability increases, the traditional double marginalization problem becomes more severe, leading to greater efficiency loss in the channel. We obtain revenue sharing contracts that can coordinate the dynamic supply chain. In particular, when the manufacturer may hold inventory, we identify two major drivers for inventory carryover: market growth and learning rate variability. Finally, we demonstrate the robustness of our results by examining a model in which cost learning takes place continuously.     

库存成本变化的VMI供应链协调

提出了库存成本变化的经济订货批量(EOQ)模型，基于该模型研究了库存成本变化时供应商管理库存(VMI)系统的最优协议问题。在该系统中，订货商和供应商达成缺货成本共担协议：当缺货发生时，供应商需要向订货商支付缺货补偿。订货商和供应商分散决策，订货商通过设计协议来减少其成本，而供应商通过制定补货决策来缩小自身成本。通过与传统系统和整合系统的比较，得出了库存成本变化时VMI系统的最优补货决策和缺货成本共担协议。采用数值算例验证了分析结果。结果表明，当且仅当供应商预期成本等于整合系统的最小总成本与固定缺货罚金之和时，VMI系统与整合系统具有相同的补货决策和系统绩效，即能够实现供应链协调。     

Storage constrained vendor managed inventory models with unequal shipment frequencies

We consider a supply chain where a vendor manages its multiple retailers' stocks under a vendor managed inventory (VMI) contract that specifies upper stock limits at the retailers' premises and overstock costs for exceeding those limits. We formulate a mixed integer nonlinear program that minimizes total supply chain costs and allows unequal shipment frequencies to the retailers. We develop an algorithm to solve its relaxed version which provides a lower bound cost solution. We propose a cost efficient heuristic procedure to generate delivery schedules to the retailers. We conduct a sensitivity analysis to provide insights on the performance of the proposed heuristic. Results show that our heuristic finds optimal or near optimal solutions, and it proposes substantial savings compared to the total supply-chain cost in the cases where there is no VMI and where there is VMI but with equal shipment frequencies to retailers.     

供需不确定下基于MOI和VMI模式的供应链协同比较研究

为分析供应链运作机制对降低随机供应商产出和随机需求的影响,对比研究了两供应商-单制造商系统在MOI和VMI两种模式下的供应链协同模型。MOI模式下,制造商管理并持有库存,提出了供应风险共享的协同机制;VMI模式下,供应商管理并持有库存,提出了收益共享与额外惩罚的协同机制。分析了集中决策、MOI和VMI模式下的最优批量决策,证明了VMI模式下存在唯一的纳什均衡。研究还发现,VMI模式更容易协调供应链,有效降低供需不确定的影响。MOI模式下的供应链可实现帕累托改进,但不能实现协调;而当参数满足一定关系时,VMI模式下供应链的期望利润可达到集中决策。     

Flexibility or Cost Saving? Sourcing Decisions with Two Suppliers

This article studies a decentralized supply chain in which there are two suppliers and a single buyer. One supplier offers the quantity flexibility (QF) contract to the buyer, while the other offers the cheaper price. Under the QF contract, the buyer does not assume full responsibility for the forecast, yet the supplier guarantees the availability of the forecasted quantity with additional buffer inventory. On the other hand, the price‐only contract places full inventory burden on the buyer, but with a cheaper price. We study this problem from the buyer's perspective and solve for the buyer's optimal procurement and forecasting decisions. We identify areas where flexibility and cheaper price have an advantage, one over the other. Our results indicate that the buyer significantly benefits from having multiple sources of supply. We also find that, from the system's standpoint, a multisupplier system may outperform a single‐supplier supply chain under certain conditions. Interestingly, we observe that providing too much flexibility may benefit the low‐price supplier rather than benefiting the QF supplier. We discuss the managerial implications and provide directions for future research opportunities.     

易逝品VMI与TPL集成供应链研究

本文考虑易逝品VMI与TPL集成环境下的供应链,旨在分析引入TPL对VMI供应链性能的影响。文章分别讨论了供应商拥有库存决策权、TPL拥有库存决策权以及引入不允许缺货约束机制等三种情况下的供应链,分析结果表明,库存决策权的转移对供应链的绩效没有绝对的影响,而在加入不允许缺货的约束机制后,供应链库存水平、顾客满意度以及零售商和供应商的收益都会得到一定程度的改善,而TPL收益和供应链总收益的变化不确定。     

一类供应商管理库存供应链协调策略研究

对有确定需求、有初始库存和库存短缺的一种畅销商品,建立了供应商管理库存的供应链模型.然后,分别分析分散式、集中式和VMI三种供应链模式下的库存补充数量最优解及各方收益情况,得到VMI的实施将可能造成供应商收益下降.再运用委托-代理理论分别讨论了信息对称和信息不对称时的VMI数量折扣契约设计问题.最后,给出算例说明了,此协调策略有助于VMI的实施.     

VMI环境下收入共享契约分析

随着竞争的加剧,供应链成员之间需要更紧密的合作关系.供应商管理库存(Vendor Managed Inventory,VMI)成为加强供应链合作的方式日益收到重视,但单独利用VMI不能有效的提高供应链的效率.本文首先分析了中心控制模式下和VMI模式下的系统性能参数,并分析了其性质.而后,利用收入共享契约来协调供应链成员之间的活动,得出了此种方式的系统性能参数,并证明了利用此契约能够提高供应链效率.最后,利用数值分析方法对结果进行了验证.     

Revenue‐Sharing vs. Wholesale‐Price Contracts in Assembly Systems with Random Demand

Assembly and kitting operations, as well as jointly sold products, are rather basic yet intriguing A decentralized supply chains, where achieving coordination through appropriate incentives is very important, especially when demand is uncertain. We investigate two very distinct types of arrangements between an assembler/retailer and its suppliers. One scheme is a vendor‐managed inventory with revenue sharing, and the other a wholesale‐price driven contract. In the VMI case, each supplier faces strategic uncertainty as to the amounts of components, which need to be mated with its own, that other suppliers will deliver. We explore the resulting components' delivery quantities equilibrium in this decentralized supply chain and its implications for participants' and system's expected profits. We derive the revenue shares the assembler should select in order to maximize its own profits. We then explore a revenue‐plus‐surplus‐subsidy incentive scheme, where, in addition to a share of revenue, the assembler also provides a subsidy to component suppliers for their unsold components. We show that, by using this two‐parameter contract, the assembler can achieve channel coordination and increase the profits of all parties involved. We then explore a wholesale‐price‐driven scheme, both as a single lever and in combination with buybacks. The channel performance of a wholesale‐price‐only scheme is shown to degrade with the number of suppliers, which is not the case with a revenue‐share‐only contract.     

Quantifying the effectiveness of VMI and integrated inventory management in a supply chain with uncertain lead-times and uncertain demands

This article considers the inventory management problem in a supply chain with uncertain replenishment lead-times and uncertain demands. The optimal integrated inventory management (IIM) policy is developed using stochastic dynamic programming theory. The IIM policy is contrasted with two pull-type vendor-managed inventory policies (VMI-1 and VMI-2) and a traditional retailer-managed inventory policy (RMI). Computational results show that in such stochastic supply chains, IIM performs about 23, 15, and 3% better than the optimised RMI, VMI-1 and VMI-2 policies, respectively, while two VMI policies are about 8 and 20% better than the best RMI. The basestock-based VMI-2 is a very good form of VMI. The ANOVA analysis reveals that the replenishment lead-times have the largest effect on the relative performance between IIM and other policies. Numerical examples demonstrated that the IIM policy has good structural properties and can be characterised by a set of switching curves.     

Quantity Discount‐Based Inventory Coordination: Effectiveness and Critical Environmental Factors

It is understood that quantity discounts provide a practical foundation for coordinating inventory decisions in supply chains. The primary objective of this research is to test, under a variety of environmental conditions, the effectiveness of quantity discounts as an inventory coordination mechanism between a buyer and a supplier. A comprehensive simulation experiment with anova has been designed to investigate the impacts of (1) choice of quantity discount‐based inventory coordination policies, (2) magnitude of demand variation, (3) buyer's and supplier's relative inventory cost structure, and (4) buyer's economic time‐between‐orders on the effectiveness of supply chain inventory coordination. The analytical results confirm that the quantity discount policies have managerial properties as a mediator for inventory coordination. The results also show that the performance of quantity discount‐based inventory coordination policies is influenced significantly by environmental factors, such as the magnitude of demand variation, the buyer's and the supplier's inventory cost structure, and the buyer's economic time‐between‐orders.     

Managing Production and Distribution for Supply Chains in the Processed Food Industry

We develop and evaluate a modeling approach for making periodic review production and distribution decisions for a supply chain in the processed food industry. The supply chain faces several factors, including multiple products, multiple warehouses, production constraints, high transportation costs, and limited storage at the production facility. This problem is motivated by the supply chain structure at Amy's Kitchen, one of the leading producers of natural and organic foods in the United States. We develop an enhanced myopic two‐stage approach for this problem. The first stage determines the production plan and uses a heuristic, and the second stage determines the warehouse allocation plan and uses a non‐linear optimization model. This two‐stage approach is repeated every period and incorporates look‐ahead features to improve its performance in future periods. We validate our model using actual data from one factory at Amy's Kitchen and compare the performance of our model to that of the actual operation. We find that our model significantly reduces both inventory levels and stockouts relative to those of the actual operation. In addition, we identify a lower bound on the total costs for all feasible solutions to the problem and measure the effectiveness of our model against this lower bound. We perform sensitivity analysis on some key parameters and assumptions of our modeling approach.     

Emerging Market Penetration,Inventory Supply,and Financial Performance

Realizing potential benefits from emerging market penetration requires firms to address inherent supply chain challenges. A major challenge is for firms to manage costly inventories to address demand and supply risks in emerging markets. However, emerging market penetration may offer opportunities for firms to lower inventory levels, reduce costs, and improve operating performance. Using data for 482 manufacturing firms over the 5‐year period, 2003–2007, obtained from the COMPUSTAT Industrial and Segment Databases, this article examines the relationships between emerging market penetration, inventory supply, and financial performance. Our results show that a multinational firm's sales penetration into emerging markets is associated with fewer days of inventory supply and improved financial performance. As emerging market penetration may allow firms to operate with lower inventory supply, the positive effect from emerging market penetration, such as labor cost reductions, may be enhanced due to inventory cost savings.     

REENGINEERING CHANNEL REORDERING PROCESSES TO IMPROVE TOTAL SUPPLY-CHAIN PERFORMANCE

This paper discusses the relationship between business process reengineering and channel performance for firms implementing electronic data interchange (EDI) linkages within the U.S. grocery industry. Both quantitative and qualitative data sources are combined to test the hypothesis that channel transformation involving adoption of EDI and redesign of replenishment processes enables performance improvements more than an order of magnitude greater than implementation of EDI alone. This new process, enabled by EDI, provides retailers with 50- 100% higher inventory turns for products on continuous replenishment processes (CRP) relative to retailer performance using traditional ordering processes. Firms adopting EDI without using CRP to reengineer the ordering processes have failed to realize any statistically significant improvements in either inventory levels or warehouse stockouts. This research provides evidence to support the claims of process reengineering that are common in the popular business press, but for which statistically significant empirical evidence is minimal. The findings of the research also demonstrate the potential improvements that firms can realize through extending the business process reengineering concept to include the firms' entire supply chain.     

基于库存分担策略的装配系统准时供货模型研究

本文考虑一个由多供应商和单制造商构成的装配系统。当市场的需求时间无法确定时,制造商通过对供应商设定合理的库存分担策略来降低自身成本,供应商则需要自行决定对制造商的补货时间并承担相应的库存持有成本和延迟惩罚成本。文章同时建立了供应商之间的纳什博弈模型和以制造商为主方的主从博弈模型,以找到供应商的最佳供货时间和制造商最优的库存承担时限。通过对比不同模式下供应链的整体绩效,找到实现供应链协调运作的必要条件,并通过数据分析进一步证明相关结论。     

Willingness to Pay for Shifting Inventory Risk: The Role of Contractual Form

In order to reduce their inventory risk, firms can attempt to contract with their suppliers for shorter supply lead‐times, with their buyers for longer demand lead‐times, or both. We designed a controlled laboratory experiment to study contracts that shift a focal firm's inventory risk to its supply chain partners and address two questions. First, is it more effective if the cost of shifting inventory risk is framed as a fixed fee or in per‐unit cost terms? We find that, generally, our participants are willing to pay more to avoid supply–demand mismatches than the expected costs from such mismatches. This tendency to overpay is mitigated under fixed fee schemes. Second, does it matter whether the option to reduce inventory risk is the outcome of either increased responsiveness from the upstream supplier or advanced demand information from the downstream buyer? Our results suggest that this difference, when only a matter of framing, has no significant effect on willingness‐to‐pay.     

A Stochastic Inventory Model With Fast‐Ship Commitments

We present a multiperiod model of a retail supply chain, consisting of a single supplier and a single retailer, in which regular replenishment occurs periodically but players have the option to support fast delivery when customers experience a stockout during a replenishment period. Because expedited shipments increase the supplier's transportation cost, and possibly production/inventory costs, the supplier typically charges a markup over and above the prevailing wholesale price for fast‐shipped items. When fast shipping is not supported, items are backordered if customers are willing to wait until the start of the next replenishment period. We characterize the retailers and the supplier's optimal stocking and production policies and then utilize our analytical framework to study how the two players respond to changes in supply chain parameters. We identify a sufficient condition such that the centralized supply chain is better off with the fast‐ship option. We find a range of markups for fast‐ship orders such that the fast‐ship option is preferred by both the supplier and the retailer in a decentralized chain. However, a markup that is a win–win for both players may not exist even when offering fast‐ship option is better for the centralized chain. Our analysis also shows that depending on how the markup is determined, greater customer participation in fast‐ship orders does not necessarily imply more profits for the two players. For some predetermined markups, the retailer's profit with the fast‐ship option is higher when more customers are willing to wait. However, the retailer may not be able to benefit from the fast‐ship option because the supplier may choose not to support the fast‐ship option when fast‐ship participation increases due to the fact that the fast‐ship participation rate adversely affects the initial order size.