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。     

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.     

Multiple In‐Cycle Transshipments with Positive Delivery Times

We study a centralized inventory sharing system of two retailers that are replenished periodically. Between two replenishments, a unit can be transshipped to a stocked‐out retailer from the other. It arrives a transshipment time later, during which the stocked‐out retailer incurs backorder cost. Without transshipment, backorder cost is incurred until the next replenishment. Since the transshipment time is shorter than the time between two replenishments, transshipments can reduce the backorder cost at the stocked‐out retailer and the holding costs at the other retailer. The system is directed by a centralized inventory manager, who minimizes the long‐run average cost consisting of replenishment, holding, backorder, and transshipment costs. The transshipment policy is characterized by hold‐back inventory levels, which are nonincreasing in the remaining time until the next replenishment. The transshipment policy differs from those in the literature because we allow for multiple transshipments between replenishments, positive transshipment times, and backorder costs. We also discuss the challenges associated with positive replenishment time and develop upper and lower bounds of average cost in this case. Bounds are numerically shown to have an average gap of 1.1%. A heuristic solution is based on the upper bound and differs from the optimal cost by at most this gap.     

VMI供应链下考虑补货策略的的契约设计

结合(r,Q)和(s,S)两种库存补货策略,提出了货权属供应商的VMI供应链的契约设计问题。采用风险分担的思想,给出了两种可行的风险分担的契约形式。在离散需求下,通过参数试验的形式,分别研究了两种契约形式对供应链效率的影响。研究结果表明,两种契约能够使得供应链的效率达到满意,同时对于影响效率的参数有一定的鲁棒性,并且在一定情况下能协调供应链。相比收益分享契约,引入风险分享的契约形式能够使得供应链协作的效率更高。研究结论对VMI契约设计有参考意义。     

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.     

Quick response and supply chain structure with strategic consumers

This work explores the impact of quick response on supply chain performance for various supply chain structures with strategic customer behavior. By investigating pricing and inventory decisions in decentralized supply chains under revenue-sharing contracts and in centralized supply chains, we study the performance of four various systems and compare the value of quick response in different supply chain structures. The results show that if the extra cost of quick response is relatively low, the value of quick response would be greater in centralized systems than in decentralized systems. On the other hand, if the extra cost is high, decentralized supply chains reap more incremental profits from adopting quick response. We also find that revenue-sharing contracts enable a decentralized supply chain to outperform a centralized supply chain, but only allow limited flexibility of allocating total profits between a manufacturer and a retailer.     

Grocery Perishables Management

In this article, we study the joint pricing and inventory control problem for perishables when a retailer does not sell new and old inventory at the same time. At the beginning of a period, the retailer makes replenishment and pricing decisions, and at the end of a period, the retailer decides whether to dispose of ending inventory or carry it forward to the next period. The objective of the retailer is to maximize the long‐run average profit. Assuming zero lead time, we propose an efficient solution approach to the problem, which is also generalized to solve three extensions to the basic model. A feature of the present study is that we consider explicitly the influence of perishability on the demand. Among the insights gathered from the numerical analysis, we find that dynamic pricing aids extending shelf life and when disposal incurs a lower cost, or even a positive salvage value, the retailer is induced to dispose earlier since the benefit of selling new inventory offsets the loss due to disposal. We also observe that the faster the perceived rate of deterioration, the lower the threshold of the ending inventory for disposal. Perhaps a bit counter‐intuitive, maximizing profits does not mean eliminating disposals or expirations.     

Managing Slow‐Moving Perishables in the Grocery Industry

We address the value of information and value of centralized control in the context of a two‐echelon, serial supply chain with one retailer and one supplier that provide a single perishable product to consumers. Our analysis is relevant for managing slow‐moving perishable products with fixed lot sizes and expiration dates of a week or less. We evaluate two supply chain structures. In the first structure, referred to as decentralized information sharing, the retailer shares its demand, inventory, and ordering policy with the supplier, yet both facilities make their own profit‐maximizing replenishment decisions. In the second structure, centralized control, incentives are aligned and the replenishment decisions are coordinated. The latter supply chain structure corresponds to the industry practices of company‐owned stores or vendor‐managed inventory. We measure the value of information and value of centralized control as the marginal improvement in expected profits that a supply chain achieves relative to the case when no information is shared and decision making is decentralized. Key assumptions of our model include stochastic demand, lost sales, and fixed order quantities. We establish the importance of information sharing and centralized control in the supply chain and identify conditions under which benefits are realized. As opposed to previous work on the value of information, the major benefit in our setting is driven by the supplier's ability to provide the retailer with fresher product. By isolating the benefit by firm, we show that sharing information is not always Pareto‐improving for both supply chain partners in the decentralized setting.     

Inventory‐Based Dynamic Pricing with Costly Price Adjustment

We study an average‐cost stochastic inventory control problem in which the firm can replenish inventory and adjust the price at anytime. We establish the optimality to change the price from low to high in each replenishment cycle as inventory is depleted. With costly price adjustment, scale economies of inventory replenishment are reflected in the cycle time instead of lot size—An increased fixed ordering cost leads to an extended replenishment cycle but does not necessarily increase the order quantity. A reduced marginal cost of ordering calls for an increased order quantity, as well as speeding up product selling within a cycle. We derive useful properties of the profit function that allows for reducing computational complexity of the problem. For systems requiring short replenishment cycles, the optimal solution can be easily computed by applying these properties. For systems requiring long replenishment cycles, we further consider a relaxed problem that is computational tractable. Under this relaxation, the sum of fixed ordering cost and price adjustment cost is equal to (greater than, less than) the total inventory holding cost within a replenishment cycle when the inventory holding cost is linear (convex, concave) in the stock level. Moreover, under the optimal solution, the time‐average profit is the same across all price segments when the inventory holding cost is accounted properly. Through a numerical study, we demonstrate that inventory‐based dynamic pricing can lead to significant profit improvement compared with static pricing and limited price adjustment can yield a benefit that is close to unlimited price adjustment. To be able to enjoy the benefit of dynamic pricing, however, it is important to appropriately choose inventory levels at which the price is revised.     

Stockout Recovery under Consignment: The Role of Inventory Ownership in Supply Chains

We examine how a supply chain firm may implement an incentive contract under inventory consignment to recover stockouts and to retain customers. Inventory consignment allows an upstream firm (e.g., a manufacturer) to own and control inventory at a downstream firm (e.g., a retailer), representing a structural change in supply chain governance. Motivated by cases in pet toy and electronics component industries, we formulate principal–agent models based on the newsvendor framework to capture the strategic interactions in a supply chain. We find that consignment can be effective in reducing stockouts because the ownership and control of the product by the manufacturer allows better prevention of stockouts, which complements stockout recovery and leads to fewer stockouts. However, the lower level of stockout under consignment does not necessarily translate into profitability—when the manufacturer is highly opportunistic, that is, readily exploring outside opportunities for its product, consignment may lead to lower profitability for both the manufacturer and the supply chain. On the other hand, consignment will improve profitability for the manufacturer and the supply chain, if both the manufacturer opportunism and the retailer opportunism are moderate.      

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%.     

The Effects of Sharing Upstream Information on Product Rollover

The process of introducing new and phasing out old products is called product rollover. This paper considers a periodic‐review inventory system consisting of a manufacturer and a retailer, where the manufacturer introduces new and improved products over an infinite planning horizon using the solo‐roll strategy. We consider two scenarios: (1) the manufacturer does not share the upstream information about new‐product introduction with the retailer and (2) the manufacturer shares the information. For each scenario, we first derive the decentralized ordering policy and the system‐optimal ordering policy with given cost parameters. We then devise an optimal supply chain contract that coordinates the inventory system. We demonstrate that when the inventory system is coordinated, information sharing improves the performance of both supply chain entities. However, this may not be true if the inventory system is not coordinated. We also show that under the optimal contract, the manufacturer has no incentive to mislead the retailer about new‐product information in the information‐sharing model. When demand variability increases, information sharing adds more benefits to the coordinated supply chain. Our research provides insights about coordinating product, financial, and information flows in supply chains with product rollover.     

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.     

QUANTIFYING THE IMPACT OF INVENTORY HOLDING COST AND REACTIVE CAPACITY ON AN APPAREL MANUFACTURER'S PROFITABILITY

This paper was motivated by the operational problems faced by Northco, a school uniform manufacturer in the Northeastern United States. Northco was facing high working capital costs while also incurring high stockout and markdown costs. This paper models the impact of inventory holding cost and reactive capacity on Northco's targeted understocking and overstocking cost and offers a solution methodology for such problems. We quantify the impact of varying inventory carrying costs (and hence, high working capital costs) on stockout costs and the value of additional capacity. Our results illustrate that apparel manufacturers with high working capital costs, and hence high inventory carrying costs, should target higher stockout costs and achieve lower capacity utilization. The results presented have application beyond Northco because high working capital cost is endemic to many supply chains.     

Stockout risk of production-inventory systems with compound Poisson demands

Production-inventory systems with continuous production or continuous manufacturing have been implemented in a variety of manufacturing contexts. Most recently, the Commissioner of the FDA has called on drug and biological product manufacturers to begin switching from batch manufacturing processes to continuous production. Motivated by prevailing applications and the emerging and promising landscape in the healthcare and pharmaceutical industries, this paper studies a continuous-review production-inventory system with a constant production rate and compound Poisson demands, in which the cost of the system is assessed via inventory holding, stockout penalty and production costs. For any initial inventory, we derive a closed-form expression for the expected discounted cost function until stockout occurrence. We systemically quantify the stockout risk on four different dimensions (i.e., time, volume, frequency and percentage) and derive explicit expressions for each type of risk metric. The objective is to derive the production rate that minimizes the expected discounted system cost subject to a given risk tolerance level on stockouts. With the aid of the derived explicit forms of stockout risk and the cost function, we develop a computationally-efficient algorithm for the optimal solution. Extensive numerical studies are conducted to illustrate our results with rich insights. Numerically, we show that it is outrageously costly to reduce stockout risk, especially when this risk is relatively low; the value of risk is more sensitive to the stockout risk level if the demand distribution has a higher volatility.     

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.     

Order Progress Information: Improved Dynamic Emergency Ordering Policies

Technologies such as radio‐frequency identification and global positioning systems can provide improved real‐time tracking information for products and replenishment orders along the supply chain. We call this type of visibility order progress information. In this paper, we investigate how order progress information can be used to improve inventory replenishment decisions. To this end, we examine a retailer facing a stochastic lead time for order fulfillment. We characterize a replenishment policy that is based on the classical (Q, R) policy and that allows for releasing emergency orders in response to the order progress information. We show that the optimal structure of this policy is given by a sequence of threshold values dependent on order progress information. In a numerical study we evaluate the cost savings due to this improved replenishment policy.     

Demand Forecast Sharing in Supply Chains

This paper examines the incentives of a manufacturer and a retailer to share their demand forecasts. The demand at the retailer is a linearly decreasing function of price. The manufacturer sets the wholesale price first, and the retailer sets the retail price after observing the wholesale price. Both players set their prices based on their forecasts of demand. In the make‐to‐order scenario, the manufacturer sets the production quantity after observing the actual demand; in the make‐to‐stock scenario, the manufacturer sets the production quantity before the demand is realized. In the make‐to‐order scenario, we show that sharing the forecast unconditionally by the retailer with the manufacturer benefits the manufacturer but hurts the retailer. We also demonstrate that a side payment contract cannot induce Pareto‐optimal information sharing equilibrium, but a discount based wholesale price contract can. The social welfare as well as consumer surplus is higher under the discount contract, compared with under no information sharing. In the make‐to‐stock scenario, the manufacturer realizes additional benefits in the form of savings in inventory holding and shortage costs when forecasts are shared. If the savings from inventory holding and shortage costs because of information sharing are sufficiently high, then a side payment contract that induces Pareto‐optimal information sharing is feasible in the make‐to‐stock scenario. We also provide additional managerial insights with the help of a computational study.     

Design of Extended Warranties in Supply Chains under Additive Demand

We study the design of extended warranties in a supply chain consisting of a manufacturer and an independent retailer. The manufacturer produces a single product and sells it exclusively through the retailer. The extended warranty can be offered either by the manufacturer or by the retailer. The party offering the extended warranty decides on the terms of the policy in its best interest and incurs the repair costs of product failures. We use game theoretic models to answer the following questions. Which scenario leads to a higher supply‐chain profit, the retailer offering the extended warranty or the manufacturer? How do the optimum price and extended warranty length vary under different scenarios? We find that, depending on the parameters, either party may provide better extended warranty policies and generate more system profit. We also compare these two decentralized models with a centralized system where a single party manufactures the product, sells it to the consumer, and offers the extended warranty. We also consider an extension of our basic model where either the manufacturer or the retailer resells the extended warranty policies of a third party (e.g., an independent insurance company), instead of offering its own policy.     

决策者过度自信视角下考虑质量控制的供应链库存策略

研究了由单个供应商和零售商组成的供应链中,零售商进行质量控制的条件下,供应链成员对市场需求的过度自信如何影响其库存管理决策和供应商的质量投资。分析了零售商管理库存、供应商管理库存和集中决策三种供应链库存管理模式下供应链成员库存和质量投资决策的博弈均衡,并通过与完全理性下均衡结果的比较探讨了过度自信对供应链成员库存决策、质量投资和利润等的冲击。研究表明,在零售商管理库存模式下,过度自信的决策者对库存量的决策受其心理预期市场需求的正向影响,而在供应商管理库存和集中决策模式下则相反。