Marketing-driven channel coordination with revenue-sharing contracts under price promotion to end-customers

This paper explores the equilibrium behavior of a basic supplier-retailer distribution channel with and without revenue-sharing contracts under price promotion to end-customers. Three types of promotional demand patterns characterized by different features of dynamic price sensitivity are considered to rationalize price promotional effects on end-customer demands. Under such a retail price promotion scheme, this work develops a basic model to investigate decentralized channel members’ equilibrium decisions in pricing and logistics operations using a two-stage Stackelberg game approach. Extending from the basic model, this work further derives the equilibrium solutions of the dyadic members under channel coordination with revenue-sharing contracts. Analytical results show that under certain conditions both the supplier and retailer can gain more profits through revenue-sharing contracts by means of appropriate promotional pricing strategies. Moreover, the supplier should provide additional economic incentives to the retailer. Furthermore, a counter-profit revenue-sharing chain effect is found in the illustrative examples. Such a phenomenon infers that the more the retailer requests to share from a unit of sale the more it may lose under the revenue-sharing supply chain coordination scheme.     

Measurement and optimization of responsiveness in supply chain networks with queueing structures

In this paper we consider supply chains with multiple stages of serial or network structure. The supply chains are endogenous in the sense that they involve queues because each order’s lead-time is dependent on the orders already in the system. We define supply chain responsiveness as the probability of fulfilling customer orders within a promised lead-time and study the problems of measuring and optimizing supply chain responsiveness using queueing network models. We first consider a single-server multi-stage serial supply chain and find a closed form expression for the fulfilment time distribution. For the multi-server multi-stage problem, the closed form evaluation of the fulfilment time distribution becomes intractable due to the dependency of the lead-times in different stages. We circumvent this difficulty by proposing a novel FCFS discipline which enables a closed-form analysis. For the multi-server multi-stage Jackson-type supply chain network, to enable analysis, we convert the system into an equivalent single server single stage system with state-dependent rates. For each case, we present detailed numerical examples for both measurement and the optimization of supply chain responsiveness.     

Wholesale-price contract of supply chain with information gathering

This paper investigates a wholesale-price contract of supply chain under the endogenous information structure. This supply chain consists of one supplier and one retailer during the selling season. The retailer does not know his selling cost but can spend resources to acquire information. The supplier offers a contract, which induces the retailer to gather information and generate more production orders with beta costs. We find that there exists an upper bound of the information gathering cost such that the supplier induces the retailer to gather information. The increasing cost of information gathering may decrease the order quantity and wholesale price. Moreover, the cost beta has an impact on the expected profits of the two parties. With the increasing cost of information gathering, the supplier’s expected profit is reduced, while that of the retailer becomes ambiguous in terms of the distribution function and the interval of selling cost information. Finally, a numerical example is presented to explain the main results.     

Pricing policies for substitutable products in a supply chain with Internet and traditional channels

This study considers pricing policies in a supply chain with one manufacturer, who sells a product to an independent retailer and directly to consumers through an Internet channel. In addition to the manufacturer’s product, the retailer sells a substitute product produced by another manufacturer. Given the wholesale prices of the two substitute products, the manufacturer decides the retail price of the Internet channel, and the retailer decides the retail prices of the two substitute products. Both the manufacturer and the retailer choose their own decision variables to maximize their respective profits. This work formulates the price competition, using the settings of Nash and Stackelberg games, and derives the corresponding existence and uniqueness conditions for equilibrium solutions. A sensitivity analysis of an equilibrium solution is then conducted for the model parameters, and the profits are compared for two game settings. The findings show that improving brand loyalty is profitable for both of the manufacturer and retailer, and that an increased service value may alleviate the threat of the Internet channel for the retailer and increase the manufacturer’s profit. The study also derives some conditions under which the manufacturer and the retailer mutually prefer the Stackelberg game. Based on these results, this study proposes an appropriate cooperation strategy for the manufacturer and retailer.     

Contract and product quality in platform selling

More and more e-tailers (platforms) are allowing manufacturers direct access to customers. Two common contracts are offered by platforms to manufacturers: the revenue sharing contract where a platform appropriates a portion of the manufacturer’s revenue, and the fixed fee contract where a platform charges a fixed rent for each sale. Using an analytical model, this paper studies the interrelationship between a platform’s contract choice and a manufacturer’s product quality decision. We find that if product quality is exogenously given, the platform will always adopt the revenue sharing contract. If the manufacturer endogenously decides the quality, however, the platform’s contract choice may be changed. This is because the revenue sharing contract, compared to fixed fee, leads to a lower selling price of the manufacturer, whereas the fixed fee contract can motivate a higher quality than does revenue sharing. As a result, a large (small) market heterogeneity induces the platform to adopt the revenue sharing (fixed fee) contract. We also extend the model to several directions, finding that longer product line, manufacturer competition, lower marginal production cost, and higher platform cost all tend to induce the platform to put forward a fixed fee contract; while if quality decision is less flexible than contract decision, the platform is more ready to embrace revenue sharing. Besides, when there are two platforms competing for the same market, they should differentiate their contract choices so as to mitigate competition.     

时滞变质品供应链的数量折扣协调模型

在由单个批发商与单个零售商组成的两级时滞变质品供应链中,分别建立分散决策和集中决策下供应链系统的单位时间利润函数,通过比较得到集中决策优于分散决策的条件。引入数量折扣契约对时滞变质品供应链进行协调,促使整个供应链系统实现集中决策下的最优状态。设计收益共享合同来合理分配协调后的利润增量,保证批发商和零售商的单位时间利润都比协调前有所增加,从而实现供应链系统的帕累托改善。最后,通过数值算例演示了两种决策模式的单位时间利润情况,并分析了关键参数对供应链系统及各成员企业单位时间利润水平的影响。     

Optimal promotion planning—depth and frequency—for a two-stage supply chain under Markov switching demand

In considering the retailer–supplier supply chain, this paper analyzes how a retailer reasonably decides both the depth and frequency of the price discount promotion including or excluding a supplier’s inventory decision. Assuming that the promotion frequency used by the retailer is probabilistic, we model a promotion-inventory decision under an AR(1) demand with a Markov switching promotion regime. After obtaining the optimal promotion plan, our analysis also considers the behavior of the optimal promotion decision; the retailer’s price format selection, either an Every-Day-Low-Price policy (EDLP) or a Promotion policy (HiLo); and the impact of information sharing of promotion status on the system’s performance. Our results suggest that a retailer tends to overpromote if inventory cost is excluded in its promotion decision, that increasing the market share is a preferable action for both the retailer and the supplier, that total margin and price-elasticity play an important role in selecting the price format, and that the profitability for a supplier of sharing promotion information depends on the transition probabilities of the Markov switching regime.     

Capacity augmentation of a supply chain for a short lifecycle product: A system dynamics framework

For an innovative product characterized by short product lifecycle and high demand uncertainty, investment in capacity buildup has to be done cautiously. Otherwise either the product’s market diffusion is impeded or the manufacturer is left with unutilized capacity. Using the right information for making capacity augmentation decisions is critical in facing this challenge. In this paper, we propose a method for identifying critical information flows using the system dynamics model of a two-echelon supply chain. The fundamental premise of system dynamics methodology is that (system) structure determines (its) behavior. Using loop dominance analysis method we study the feedback loop structure of the supply chain system. The outcome is a set of dominant loops that determine the dynamics of capacity growth. It is revealed that the delivery delay information has little effect while the loop that connects retail sales with production order affects the dynamics significantly. Modifying this loop yields appropriate capacity augmentation decisions resulting in higher performance. What-if analyses bring out effects of modifying other structural elements. In conclusion, we claim that the information feedback based methodology is general enough to be useful in designing decision support systems for capacity augmentation. The limitations of the model are also discussed and possible extensions identified.     

A stochastic model for risk management in global supply chain networks

With the increasing emphasis on supply chain vulnerabilities, effective mathematical tools for analyzing and understanding appropriate supply chain risk management are now attracting much attention. This paper presents a stochastic model of the multi-stage global supply chain network problem, incorporating a set of related risks, namely, supply, demand, exchange, and disruption. We provide a new solution methodology using the Moreau–Yosida regularization, and design an algorithm for treating the multi-stage global supply chain network problem with profit maximization and risk minimization objectives.     

Application of fuzzy optimization to a supply chain network design: A case study of an edible vegetable oils manufacturer

This study applies fuzzy sets to integrate the supply chain network of an edible vegetable oils manufacturer. The proposed fuzzy multi-objective linear programming model attempts to simultaneously minimize the total transportation costs. The first part of the total transportation costs is between suppliers and silos; and rest one is between manufacturer and warehouses. The approach incorporates all operating realities and actual flow patterns at production/distribution network with reference to demands of warehouses, capacities of tin and pet packaging lines. The model has been formulated as a multi objective linear programming model where data are modeled by triangular fuzzy numbers. Finally, the developed fuzzy model is applied for the case study, compiled the results and discussed.