Price markdown scheme in a multi-echelon supply chain in a high-tech industry

This paper studies the price markdown scheme in a supply chain that consists of a supplier, a contract manufacturer (CM), and a buyer (retailer). The buyer subcontracts the production of the final product to the CM. The CM buys the components from the supplier and charges the buyer a service fee for the final product produced. The price markdown is made possible by the supplier with the development of new manufacturing technologies that reduce the production cost for the sourced component. Consequently, the buyer adjusts the retail price in order to possibly stimulate stronger demand that may benefit both the supplier and the buyer. Under this scenario, we identify the optimal discount pricing strategies, capacity reservation, and the stocking policies for the supplier and the buyer. We also investigate the optimal inventory decision for the CM to cope with the price discount by considering both demand and delivery uncertainties. Our results suggest that higher production cost accelerates the effects of higher price sensitivity on lowering the optimal capacity and stocking policies in the supply chain. The effect of mean demand error on the optimal prices is relatively marginal compared with that from price sensitivity. We also found that increasing the standard deviation of the random demand does not necessarily increase the stocking level as one would predict. The results show that delivery uncertainty plays an important role in the inventory carried beyond the price break. We discuss potential extensions for future research.     

Sourcing under incomplete information and negative capacity-cost correlation

We study a sourcing problem where a buyer reserves capacity from a set of suppliers. The suppliers have finite capacity and their unit production cost is a decreasing function of their capacity, implying scale economies. The capacity of each supplier and therefore the cost is his private information. The buyer and other suppliers only know the probability distribution of the supplier’s capacity. The buyer’s demand is random and she has to decide how much capacity to reserve in advance from a subset of suppliers and how much to source from marketplace. In this study we determine the buyer’s optimum reservation quantity and the size of the supply base. We find the presence of such capacity cost correlation leads to supply base reduction.     

Optimizing delivery lead time/inventory placement in a two-stage production/distribution system

In this paper we study a system composed of a supplier and buyer(s). We assume that the buyer faces random demand with a known distribution function. The supplier faces a known production lead time. The main objective of this study is to determine the optimal delivery lead time and the resulting location of the system inventory. In a system with a single-supplier and a single-buyer it is shown that system inventory should not be split between a buyer and supplier. Based on system parameters of shortage and holding costs, production lead times, and standard deviations of demand distributions, conditions indicating when the supplier or buyer(s) should keep the system inventory are derived. The impact of changes to these parameters on the location of system inventory is examined. For the case with multiple buyers, it is found that the supplier holds inventory for the buyers with the smallest standard deviations, while the buyers with the largest standard deviations hold their own inventory.     

Supply chain coordination for newsvendor-type products with two ordering opportunities and demand information update

This paper studies a coordination issue with two ordering opportunities in a two-echelon supply chain, where one manufacturer sells a single newsvendor-type product through one buyer. The manufacturer does not hold inventory and activates production or order with an infinite capacity and a fixed setup cost in response to the buyer’s order. The buyer places two orderings during the selling period of the product: one happens at the beginning of the period and the other at some specified time within the selling period. The whole selling period is divided into two stages or sub-periods by the buyer’s second order. The stochastic demands in the two sub-periods are assumed to be auto-correlated. The excess demand before the second order is partially backordered, whereas the excess demand at the end of the selling season is utterly lost. Under both the centralized and decentralized settings, we develop the models of how the buyer determines his two-ordering policies. We analyse the existence and uniqueness of the optimal solutions to the models and present the corresponding analytical solutions. Furthermore, we propose an improved revenue-sharing contract that can realize the perfect coordination of the supply chain and study how the revenue-sharing policies affect the supply chain members’ decisions. Finally, we show the superiority of the presented two-ordering strategy through numerical examples.     

Inventory control with an order-time constraint: optimality,uniqueness and significance

This paper analyzes a stochastic inventory problem with an order-time constraint that restricts the times at which a manufacturer places new orders to a supplier. This constraint stems from the limited upstream capacity in a supply chain, such as production capacity at a supplier or transportation capacity between a supplier and a manufacturer. Consideration of limited upstream capacity extends the classical inventory literature that unrealistically assumes infinite supplier/transporter capacity. But this consideration increases the complexity of the problem. We study the constraint under a Poisson demand process and allow for a fixed ordering cost. In presence of the constraint, we establish the optimality of an (s,S) policy under both the discounted and average cost objectives. Under the average cost objective, we show the uniqueness of the order-up-to level S. We numerically compare our model with the classical unconstrained model. We report significant savings in costs that can be achieved by using our model when the order time is constrained.     

Impact of supply base heterogeneity in electronic markets

Internet based marketplaces have enabled industrial buyers to locate suppliers from geographically diverse locations. This has resulted in increased variations in certain supplier parameters such as capacity and cost among the participating suppliers. However, the impact of this increased heterogeneity on the procurement practices are not well understood. In this paper we consider three supplier parameters that can affect the price the buyer pays and the number of suppliers that the buyer will select for award of contract. These attributes are capacity, production cost and demand for supplier’s capacity. We show how these parameters impact the price that a supplier quotes. We also show how the buyer will determine the optimum number of suppliers using a reverse auction mechanism when he does not have perfect knowledge of the suppliers’ parameters. Our model suggests that buyers need to adjust some of the input parameters while procuring capacity from a heterogeneous supply base. For instance, buyers need to pre-qualify more suppliers if the supply base has greater heterogeneity.     

Supplier–manufacturer coordination in capacitated two-stage supply chains

Manufacture-to-order is an increasingly popular strategy in commodity electronics and other similar markets where many different product configurations can be produced from common components. To succeed in this environment, manufacturers need to keep both cost and order fulfillment time low. In this article, we compare three different mechanisms that a manufacturer, whose revenues depend on order delays, may use to affect its component supplier’s inventory decisions. These mechanisms are specifying components inventory level, offering a share of the earned revenues to the supplier (called simple revenue sharing), and offering a two-part revenue-sharing scheme. We show that whereas the first two approaches do not lead to supply chain coordination, the two-part scheme does. We demonstrate with numerical experiments that up to a point, the component supplier benefits from having a high utilization of its production facility, whereas the manufacturer benefits from having excess production capacity.     

Endogenous information acquisition in supply chain management

In this paper, we analyze an endogenous determination of efforts put into information acquisition and its impact on supply chain management. More specifically, we consider a supplier who sells a product to a buyer during a single selling season. Prior to placing an order with the supplier, the buyer has an option to acquire additional information about the demand by hiring experts (who are capable of providing forecasts). Because a commission fee must be paid to each hired expert, there exists a tradeoff between the cost and the value of the information, and the buyer needs to determine how much information to acquire. We derive the optimal information-acquisition level in an integrated setting and compare it with that determined in a decentralized setting. We also analyze several types of supply contracts to examine if they can coordinate the supply chain and allow an arbitrary division of system profit between the supplier and the buyer.     

Design of contract parameters in a closed-loop supply chain

We study an extended joint economic lot size problem which incorporates the return flow of remanufacturable used products. The supply chain under consideration consists of a single supplier and a single buyer. The buyer orders a single product from the supplier, uses it for her own needs, and collects the remanufacturable items after use. The ordered items are shipped from the supplier to the buyer in the lot-for-lot fashion by a vehicle which also returns the collected used items from the buyer to the supplier for remanufacturing and subsequent service of the buyer’s demand in the next order cycle. For satisfying the total demand, the supplier manufactures new items or remanufactures used ones received from the buyer. For given demand, productivity, collection rate, disposal cost, setup cost, order cost, holding cost for serviceable and nonserviceable products at the supplier as well as the buyer the lot size (order size) for the supplier (buyer) has to be found which minimizes the total cost. Furthermore, we address a decentralised decision making of the parties under a two-part tariff and determine their equilibrium strategies within the Nash framework.     

A dynamic model of supplier switching

While a broad branch of literature deals with the development of buyer–supplier relationships, limited research exists under which circumstances a buyer should terminate such a relationship and switch to a new supplier. Recently, Wagner and Friedl (2007) have developed a framework to analyze a static one-shot supplier switching decision when the buyer has asymmetric information about the supplier’s production costs. We extend their basic framework to a dynamic one, assuming that the supplier learns the production costs over time when he sets up the production process. Since the supplier’s cost information at the individual stages crucially determines the setup and the switching decision, it becomes essential for supply chain management to provide proper incentives so that the supplier reveals his cost information truthfully over time. We characterize the optimal setup and switching strategy as well as the optimal supply chain contract. We also compare our findings with those of the static setting to provide further insights.     

Supply chain coordination with controllable lead time and asymmetric information

This paper considers coordinated decisions in a decentralized supply chain consisting of a vendor and a buyer with controllable lead time. We analyze two supply chain inventory models. In the first model we assume the vendor has complete information about the buyer’s cost structure. By taking both the vendor and the buyer’s individual rationalities into consideration, a side payment coordination mechanism is designed to realize supply chain Pareto dominance. In the second model we consider a setting where the buyer possesses private cost information. We design the coordination mechanism by using principal-agent model to induce the buyer to report his true cost structure. The solution procedures are also developed to get the optimal solutions of these two models. The results of numerical examples show that shortening lead time to certain extent can reduce inventory cost and the coordination mechanisms designed for both symmetric and asymmetric information situations are effective.     

Benefits of co-operation in a production distribution environment

We model co-operation in a typical production distribution setting that contains one capacitated supplier producing and distributing a single product to many identical retailers who are facing i.i.d. end-item demands from the consumers. We consider three inventory allocation mechanisms, representing varying degrees of co-operation, at the supplier: (1) the orders from the retailers are filled in a predetermined sequence; (2) the orders from the retailers are filled after taking into account their current inventories; and (3) the orders from the retailers are filled assuming that the product can also be shipped from one retailer to another. We estimate the benefits due to co-operation in this supply chain and study the effect of various system parameters on these benefits. An extensive computational study indicated that the benefits of co-operation in this production distribution environment decrease with increase in the supplier capacity, increase in the number of retailers, decrease in penalty cost, and decrease in consumer demand variance.     

Mitigating supply risk: an approach with quantity flexibility procurement

This paper considers a buyer that procures from its major supplier whose production is subject to random yield risk. To mitigate supply risk, the buyer can procure from another reliable supplier who provides quantity flexibility (QF) contract. Under both deterministic and stochastic demand, we study the buyer’s optimal procurement decisions. We analyze the structural properties of optimal solutions and identify the conditions under which the quantity flexibility procurement policy should be used. We also examine the effect of supply risk, flexibility, wholesale price and demand risk on the procurement decisions. We find that the higher supply risk and demand risk reduce the buyer’s profit but have different impact on the buyer’s order policy. For the QF supplier, it may not obtain more orders by providing larger flexibility to the buyer, on the contrary, doing this may benefit the risky supplier. For the QF supplier or risky supplier, given its competitor’s wholesale price, it can increase its order share by lower wholesale price.     

A mathematical model for a capacity reservation contract

It is common practice in many industries to use a replenishment contract with a mechanism of capacity reservation. In this paper, we focus on a multi-period capacity reservation contract practiced between a buyer, who buys a single type of product and sells it to end-customers, and two or more heterogeneous suppliers, who produce and replenish the product as agreed upon contractually.In this paper, a mathematical model including several key features of a real contract is developed for a single supplier situation from the buyer’s perspective. It is then extended to a multiple supplier model for a system in which there are several heterogeneous suppliers with different capacities and prices. A rolling-horizon implementation strategy is suggested for the efficient application of the models. Extensive computational experiments demonstrate that the model and strategy can produce cost effective contractual terms for the buyer within a few seconds.     

基于ROI,VMI和CS三种库存方式长短期绩效的对比研究

ROI、VMI和Cs是基于供应链的三种库存管理方式.本文以两层供应链的ROI、VMI和CS方式为例,通过数学模型和具体算例,比较分析了三种库存方式下买方和卖方成本和利润构成的不同之处.本文研究发现:在长期内相对于ROI方式而言,VMI方式下供应链的效率更高;如果卖方的单位存储成本大于买方,CS方式下供应链的长短期效率可能高于VMI更高于ROI方式.     

Optimal order size to take advantage of a one-time discount offer with allowed backorders

In this paper, we develop an inventory model for determining the optimal ordering policies for a buyer who operates an inventory policy based on an EOQ-type model with planned backorders when the supplier offers a temporary fixed-percentage discount and has specified a minimum quantity of additional units to purchase. A distinguishing feature of the model is that both fixed and linear backorder costs are included, whereas previous works include only the linear backordering cost. A numerical study is performed to provide insight into the behavior of the model.     

Optimal policy for a dynamic,non-stationary,stochastic inventory problem with capacity commitment

This paper studies a single-product, dynamic, non-stationary, stochastic inventory problem with capacity commitment, in which a buyer purchases a fixed capacity from a supplier at the beginning of a planning horizon and the buyer’s total cumulative order quantity over the planning horizon is constrained with the capacity. The objective of the buyer is to choose the capacity at the beginning of the planning horizon and the order quantity in each period to minimize the expected total cost over the planning horizon. We characterize the structure of the minimum sum of the expected ordering, storage and shortage costs in a period and thereafter and the optimal ordering policy for a given capacity. Based on the structure, we identify conditions under which a myopic ordering policy is optimal and derive an equation for the optimal capacity commitment. We then use the optimal capacity and the myopic ordering policy to evaluate the effect of the various parameters on the minimum expected total cost over the planning horizon.     

Exact algorithms for procurement problems under a total quantity discount structure

In this paper, we study the procurement problem faced by a buyer who needs to purchase a variety of goods from suppliers applying a so-called total quantity discount policy. This policy implies that every supplier announces a number of volume intervals and that the volume interval in which the total amount ordered lies determines the discount. Moreover, the discounted prices apply to all goods bought from the supplier, not only to those goods exceeding the volume threshold. We refer to this cost-minimization problem as the total quantity discount (TQD) problem. We give a mathematical formulation for this problem and argue that not only it is NP-hard, but also that there exists no polynomial-time approximation algorithm with a constant ratio (unless P = NP). Apart from the basic form of the TQD problem, we describe four variants. In a first variant, the market share that one or more suppliers can obtain is constrained. Another variant allows the buyer to procure more goods than strictly needed, in order to reach a lower total cost. We also consider a setting where the buyer needs to pay a disposal cost for the extra goods bought. In a third variant, the number of winning suppliers is limited, both in general and per product. Finally, we investigate a multi-period variant, where the buyer not only needs to decide what goods to buy from what supplier, but also when to do this, while considering the inventory costs. We show that the TQD problem and its variants can be solved by solving a series of min-cost flow problems. Finally, we investigate the performance of three exact algorithms (min-cost flow based branch-and-bound, linear programming based branch-and-bound, and branch-and-cut) on randomly generated instances involving 50 suppliers and 100 goods. It turns out that even the large instances of the basic problem are solved to optimality within a limited amount of time. However, we find that different algorithms perform best in terms of computation time for different variants.     

Coordination of dynamic lot-sizing in supply chains

This paper presents a new scheme for the coordination of dynamic, uncapacitated lot-sizing problems in two-party supply chains where parties’ local data are private information and no external or central entity is involved. This coordination scheme includes the following actions: At first, the buyer generates a series of different supply proposals using an extension of her local lot-sizing problem. Then the supplier calculates his cost changes that would result from the implementation of the buyer’s proposals. Based on these information, parties can identify the best proposal generated. The scheme identifies the system-wide optimum in different settings—for instance in a two-stage supply chain where the supplier’s costs for holding a period’s demand in inventory exceed his setup costs.     

Estimating demand by using sales information: inaccuracies encountered

Demand data is integral to a company’s overall information requirement. This is particularly true for manufacturers and retailers with regard to capacity, production, and inventory planning. Notwithstanding the implicit inaccuracies encountered, companies are predisposed to employ sales data as a primary source of information for estimating future demand.In this paper, by adopting a two-product setting, we measure inventory cost inaccuracies that arise from using sales data in estimating demand. By analyzing these costs, we also explore the conditions under which the resulting inaccuracies are either “lessened” or become “acute.” In this context, the determining rule of an induced substitution structure between the two products during stockout occasions is explicitly analyzed.We use a newsboy framework, in a two product environment, wherein one product may be taken as a direct substitute for the other. We provide necessary and sufficient optimality conditions and an extensive computational study to illustrate and support our findings and to provide additional insights on the conditions characterizing optimal stocking policies.