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.     

Analysis of supply chain coordination under fuzzy demand in a two-stage supply chain

This paper considers a two-stage supply chain coordination problem and focuses on the fuzziness aspect of demand uncertainty. We use fuzzy numbers to depict customer demand, and investigate the optimization of the vertically integrated two-stage supply chain under perfect coordination and contrast with the non-coordination case. As in the traditional probabilistic analysis, we prove that the maximum expected supply chain profit in a coordination situation is greater than the total profit in a non-coordination situation.     

A study on lead-time discount coordination for deteriorating products

Goods flowing through supply chains usually deteriorate. Such goods may corrupt, volatilize, and degenerate over time and thus cause the decline of their values or quantity. This study focuses on lead-time coordination for supply chains with deteriorating products which facilitates member cooperation and long-time relationships, thus increasing profit for the entire supply chain. A two-level supply chain with a single supplier and a single retailer is considered, in which the product deteriorates in the same manner for both the supplier and retailer, which is allowed to have shortages. A lead-time discount coordination strategy is used to maximize the profit of the entire supply chain by appropriately determining the optimal order quantity and lead-time. A numerical example is given, and sensitivity analyses are performed to analyze the influence of various parameters on the overall profit. The results can help managers establish long-term cooperative relationships in supply chains.     

Coordination in a two-stage capacitated supply chain with multiple suppliers

The aim of this paper is to coordinate the inventory policies in a decentralized supply chain with stochastic demand by means of contracts. The system considered is a decentralized two-stage supply chain consisting of multiple independent suppliers and a manufacturer with limited production capacities. The suppliers operate on a make-to-stock basis and apply base stock policy to manage their inventories. On the other hand, the manufacturer employs a make-to-order strategy. Under the necessary assumptions, each supplier is modeled as an M/M/1 make-to-stock queue; and the manufacturer is modeled as a GI/M/1 queue after deriving an approximate distribution for the interarrival times of the manufacturer. Once the supply chain is modeled as a queuing system, centralized and decentralized models are developed. Comparison of the optimal solutions to these models reveals that the supply chain needs coordination. Three different transfer payment contracts are examined in this paper. These are the backorder and holding cost subsidy contracts, the transfer payment contract based on Pareto improvement, and the cost sharing contract. Each contract is evaluated according to its coordination ability and whether it is Pareto improving or not. The results indicate that all three contracts can coordinate the supply chain. However, when the Pareto improvement is taken into account, the cost sharing contract seems to be the one that will be preferred by all parties.     

新产品供应链下考虑顾客体验效应的制造商渠道返利策略研究

随着体验经济的到来和新产品市场的竞争, 如何针对顾客体验进行渠道建设和品牌推广就显得尤为重要。本文针对新产品供应链的环境, 考虑顾客的体验效应及零售商对此所做的体验投入, 利用效用理论构建了线上和线下消费者的需求函数, 在此基础上分别探讨了批发价格模式和渠道返利模式制造商占优的供应链的决策行为, 分析了供应链各决策主体均衡解的特征, 并对渠道返利前后供应链节点企业的最优决策进行了比较, 最后用数值例子分析了制造商的返利点、零售商的体验投入水平、顾客的体验效应、旅行成本以及购买意愿等对供应链最优绩效的影响。     

新产品供应链下考虑顾客体验效应的制造商渠道返利策略研究

随着体验经济的到来和新产品市场的竞争, 如何针对顾客体验进行渠道建设和品牌推广就显得尤为重要。本文针对新产品供应链的环境, 考虑顾客的体验效应及零售商对此所做的体验投入, 利用效用理论构建了线上和线下消费者的需求函数, 在此基础上分别探讨了批发价格模式和渠道返利模式制造商占优的供应链的决策行为, 分析了供应链各决策主体均衡解的特征, 并对渠道返利前后供应链节点企业的最优决策进行了比较, 最后用数值例子分析了制造商的返利点、零售商的体验投入水平、顾客的体验效应、旅行成本以及购买意愿等对供应链最优绩效的影响。     

A modified multi-criterion optimization genetic algorithm for order distribution in collaborative supply chain

Supply chain collaboration is prevalent in today’s business model, and has been recognized to be one of the important issues in improving competition strength. Order distribution is to determine which order should be allocated to which supplier, it plays a very important role in a collaborative supply chain, because different order distribution infers different benefit under different criteria. However, there is not much research on the order distribution methodology. This paper adopted a framework of a central coordination system, which is equipped with a multi-criteria genetic optimization feature. In the previous multi-criterion optimization genetic algorithm (MCOGA), the analytic hierarchy process (AHP) is deployed to evaluate the fitness values. In this paper, a modified MCOGA is proposed based on the technique for order preference by similarity to ideal solution (TOPSIS). There are two main parts, namely, searching and evaluation, in genetic algorithms. Compared with the MCOGA, the proposed method takes the advantage of less complexity in the evaluation stage. The numerical example of order distribution is used to illustrate the efficiency of the proposed method.     

Towards integration: a revenue-sharing contract in a supply chain

Email: zhaoqiong.qin{at}erau.edu Received on 31 May 2006. Accepted on 11 December 2006. This paper deals with the problem of a revenue-sharing contractadopted in a supply chain involving one supplier and one retailerwith short life-cycle products. Under this contract, the retailercan obtain the product from the supplier at a discounted pricewhile as a compensation, the retailer must share his revenuewith the supplier at a certain revenue-sharing rate, say r (0 r 1), where r represents the portion of the revenue to bekept by the retailer. We use a two-stage (Stackelberg) gameto model the problem, where one player is the game's leaderand the other the game's follower. Our ultimate objective isto maximize the overall supply chain's total profit, and toshow the effects of salvage revenue and the revenue-sharingrate on transfer cost rate, profit of the supplier and retailerand the overall supply chain's total profit while upholdingthe individual components’ incentives. Our analysis exhibitsthat the case in which salvage revenue is not shared is preferredand the computational results to explore the effects of therevenue-sharing rate lead to many managerial insights regardingthe leader of the game.     

Long-term and penalty contracts in a two-stage supply chain with stochastic demand

Recent applications of game-theoretic analysis to supply chain efficiency have focused on constructs between a buyer (the retailer or manufacturer) and a seller (the supplier) in successive stages of a supply chain. If demand for the final product is stochastic then the supplier has an incentive to keep its capacity relatively low to avoid creating unneeded capacity. The manufacturer, on the other hand, prefers the supplier’s capacity to be high to ensure that the final demand is satisfied. The manufacturer therefore constructs a contract to induce the supplier to increase its production capacity. Most research examines contracting when final demand is realized after the manufacturer places its order to the supplier. However, if final demand is realized before the manufacturer places its order to the supplier, these types of contracts can be ineffective. This paper examines two contracts under the latter timing scenario: long-term contracts in which the business relationship is repeated, and penalty contracts in which the supplier is penalized for too little capacity. Results indicate long-term contracts increase the profit potential of the supply chain. Furthermore, the penalty contracts can ensure that the supplier chooses a capacity level such that the full profit potential is achieved.     

Coordinating decentralized local schedulers in complex supply chain manufacturing

Motivated by scheduling challenges in back-end semiconductor manufacturing, we propose a framework to oversee and integrate local decentralized scheduling algorithms utilized in complex supply chain manufacturing networks. We fill the gap between higher-level production planning and lower-level scheduling by establishing short-term production targets and priority scores for each product at each step in the system. Given a target output schedule, target cycle times for each step, the process and product structure, and initial WIP status, short-term production targets for each product/step are set. These targets can be used to evaluate the system performance and guide decentralized schedulers to control the system so as to achieve desirable outputs in dynamic environments.     

Analysis of a two-stage telecommunication supply chain with technology dependent demand

We analyze a two-stage telecommunication supply chain consisting of one operator and one vendor under a multiple period setting. The operator faces a stochastic market demand which depends on technology investment level. The decision variables for the operator are the initial technology investment level and the capacity of the network for each period. The capacity that the operator installs in one period also remains available in subsequent periods. The operator can increase or decrease the available capacity at each period. For this model, an algorithm to find the centralized optimal solution is proposed. A profit sharing contract where firms share both the revenue and operating costs generated throughout the periods along with initial technology investment is suggested. Also a coordinating quantity discount contract where the discount on the price depends on the total installed capacity is designed. The case where the vendor decides on the technology investment level and the operator decides on the capacity of the network is also analyzed and it is shown that this game has a unique Nash equilibrium.     

Modeling and analysis of a supply–assembly–store chain

We consider a supply–assembly–store chain with produce-to-stock strategy, which comprises a set of component suppliers, a mixed-model assembly line with a constantly moving conveyor linking a set of workstations in series, and a set of product storehouses. Each supplier provides components of a specified family, which are assembled at a corresponding workstation. Units belonging to different models of products are sequentially fed onto the conveyor, and pass through the workstations to generate finished products. Each storehouse stores finished products belonging to a specific model for satisfying customer demands. The suppliers deliver components according to a just-in-time supply policy with stochastic leadtimes. Customer demands for a particular model of products arrive at the corresponding storehouse according to a Poisson stream. The paper conducts a modeling and performance analysis in the design stage of the system in the sense of “long-term-behavior”. A rolling technique is constructed for analyzing stationary probability distributions of the numbers of components. A two-dimensional Markov chain with infinite states is introduced for analyzing stationary probability distributions of inventories of finished products. Based on these distributions, performance measures of the system, such as work-in-process of components, inventory amounts of finished products, as well as service levels for customers, can be easily obtained. Managerial insights are obtained from both analytical and numerical results.     

Managing the order pipeline to reduce supply chain volatility

The bullwhip effect in particular, and supply chain volatility in general, has been the subject of much analytical and empirical investigation by researchers. One goal of this work has been to determine supply chain designs and policies that minimize volatility. Using a system dynamics approach, we use three distinct supply chain volatility metrics to compare the ability of two alternative pipeline inventory management policies to respond to a demand shock. The results indicate that no one policy dominates on all three metrics of supply chain volatility. A simplistic static pipeline policy minimizes the bullwhip effect and lessens the likelihood of on-hand inventory oscillations, while a more sophisticated dynamic pipeline policy may converge more rapidly to the new equilibrium. In addition, simulation results suggest that the dynamic policy provides better customer service through fewer stockouts and backorders.     

The value of early order commitment in a two-level supply chain

One approach to supply chain coordination is early order commitment, whereby a retailer commits to purchase a fixed-order quantity at a fixed delivery time before demand uncertainty is resolved. In this paper, we develop an analytical model to quantify the cost savings of an early order commitment in a two-level supply chain where demand is serially correlated. A decision rule is derived to determine whether early order commitment will benefit the supply chain, and accordingly to determine the optimal timing for early commitment. Our results indicate that the supply chain would experience greater savings from early order commitment when – (a) the inventory item receives less value-added activities at the retailer site; (b) the manufacturing lead time is short; (c) demand correlation over time is positive but weak; or (d) the delivery lead time is long (if a condition exists). We also propose a rebate scheme for the supply chain partners to share the gains of practicing early order commitment.     

On a multi-period supply chain system with supplementary order opportunity

This paper considers a supplementary supply–order system in a multi-period situation. In each period, the buyer first places an initial order based on the demand prediction; he has the opportunity to place a supplementary order with the supplier after the demand of that period is realized. The supplier maintains an inventory, and decides the quantity to be produced and the quantity to be provided for the supplementary order in each time period. We formulate the problem as a multi-period inventory game, and derive the optimal production and order policies for the supplier and buyer, respectively. The existence and uniqueness of Nash equilibrium is proved in the generalized multi-period setting, and the closed-form Nash equilibrium solution is obtained when the parameters are stationary. Numerical study is performed to reveal more managerial insights. We find that the supplementary supply–order mechanism, if designed properly, can effectively improve the multi-period supply chain performance.     

A two-period game of a closed-loop supply chain

We consider a two-period closed-loop supply chain (CLSC) game where a remanufacturer appropriates of the returns’ residual value and decides whether to exclusively manage the end-of-use product collection or to outsource it to either a retailer or a third-service provider (3P). We determine that the manufacturer outsources the product collection only when an outsourcee performs environmentally and operationally better. On the outsourcees side there is always an economic convenience in managing the product returns process exclusively, independently of returns rewards and operational performance. When outsourcing is convenient, a manufacturer always chooses a retailer if the outsourcees show equal performance. Overall, the manufacturer is more sensitive to environmental performance than to operational perfomance. Finally, there exists only a small region inside which outsouring the collection process contributes to the triple bottom line.     

Scheduling in supply chain environment

Successful companies are those that reach at least the two following objectives: reduce their Work-In-Process (WIP) and respond to customer’s requirements in real time. The approach proposed in this paper allows to reach these goals by controlling the WIP and providing information about the completion times of customer’s demands in real time. The approach we develop in this paper has been integrated in a supply chain environment for flow-shops. This paper extends the approach to assembly systems.     

On-line supply chain scheduling problems with preemption

We consider supply chain scheduling problems where customers release jobs to a manufacturer that has to process the jobs and deliver them to the customers. The jobs are released on-line, that is, at any time there is no information on the number, release and processing times of future jobs; the processing time of a job becomes known when the job is released. Preemption is allowed. To reduce the total costs, processed jobs are grouped into batches, which are delivered to customers as single shipments; we assume that the cost of delivering a batch does not depend on the number of jobs in the batch. The objective is to minimize the total cost, which is the sum of the total flow time and the total delivery cost. For the single-customer problem, we present an on-line two-competitive algorithm, and show that no other on-line algorithm can have a better competitive ratio. We also consider an extension of the algorithm for the case of m customers, and show that its competitive ratio is not greater than 2m if the delivery costs to different customers are equal.     

Coordinating order quantity decisions in the supply chain contract under random demand

In this paper, we are concerned with the coordinating quantity decision problem in a supply chain contract. The supply chain contract is composed of one manufacturer and one retailer to meet the random demand of a single product with a short lifecycle. Our analysis show that the retailer expects to obtain higher profit under proper ordering policies, which can also maximize the expected profit of the supply chain. The manufacturer may induce the retailer to order the coordinated quantity by adjusting the unit return price. As a result, the supply chain is expected to achieve the optimal expected profit.     

Double marginalization and coordination in the supply chain with uncertain supply

This paper explores a generalized supply chain model subject to supply uncertainty after the supplier chooses the production input level. Decentralized systems under wholesale price contracts are investigated, with double marginalization effects shown to lead to supply insufficiencies, in the cases of both deterministic and random demands. We then design coordination contracts for each case and find that an accept-all type of contract is required to coordinate the supply chain with random demand, which is a much more complicated situation than that with deterministic demand. Examples are provided to illustrate the application of our findings to specific industrial domains. Moreover, our coordination mechanisms are shown to be applicable to the multi-supplier situation, which fills the research gap on assembly system coordination with random yield and random demand under a voluntary compliance regime.