Transshipment incentive contracts in a multi-level supply chain

Transshipments within a supply chain can be difficult to implement as the costs and benefits are often incurred by different parties. This difficulty becomes even more problematic when the costs and benefits are not completely known by all parties. The primary purpose of this paper is to introduce the role of asymmetric information into the design of supply chain transshipment contracts. Using a representative supply chain from within the soft drink industry as an example, a multi-level contracting framework is developed that aligns incentives to encourage transshipments and improve performance in the absence of all parties having full information. Analysis of the proposed framework suggests that, even if a transshipment is likely to be unprofitable to the transshipping dyad, it may still be best for the entire supply chain. Moreover, overall supply chain inventories with transshipments do not necessarily increase relative to the no-transshipment case.     

Contracting with asymmetric demand information in supply chains

We solve a buyback contract design problem for a supplier who is working with a retailer who possesses private information about the demand distribution. We model the retailer’s private information as a space of either discrete or continuous demand states so that only the retailer knows its demand state and the demand for the product is stochastically increasing in the state. We focus on contracts that are viable in practice, where the buyback price being strictly less than the wholesale price, which is itself strictly less than the retail price. We derive the optimal (for the supplier) buyback contract that allows for arbitrary allocation of profits to the retailer (subject to the retailer’s reservation profit requirements) and show that in the limit this contract leads to the first-best solution with the supplier keeping the entire channel’s profit (after the retailer’s reservation profit).     

Pricing in a supply chain for auction bidding under information asymmetry

We examine a supply chain in which a manufacturer participates in a sealed-bid lowest price procurement auction through a distributor. This form of supply chain is common when a manufacturer is active in an overseas market without establishing a local subsidiary. To gain a strategic advantage in the division of profit, the manufacturer and distributor may intentionally conceal information about the underlying cost distribution of the competition. In this environment of information asymmetry, we determine the equilibrium mark-up, the ex-ante expected mark-up and expected profit of the manufacturer and the equilibrium bid of the distributor. In unilateral communication, we demonstrate the informed agent’s advantage resulting to higher mark-up. Under information sharing, we show that profit is equally shared among the supply chain partners and we explicitly derive the mark-up when the underlying cost distribution is uniform in [0, 1]. The model and findings are illustrated by a numerical example.     

The coordinating contracts for a fuzzy supply chain with effort and price dependent demand

This paper investigates the coordination of a two-echelon supply chain with fuzzy demand that is dependent on both retail price and sales effort. In contrast with the centralized and decentralized decision models, two coordinating models based on symmetric information and asymmetric information about retailer’s scale parameter are developed by game theory, and the corresponding analytical solutions are obtained. Theoretical analysis and numerical examples yield the maximal supply chain profits in two coordination situations are equal to that in the centralized situation and greater than that in the decentralized situation. Furthermore, under asymmetric information contract, the maximal expected profit obtained by the low-scale-level retailer is higher than that under symmetric information contract.     

A robust optimization approach to closed-loop supply chain network design under uncertainty

The concern about significant changes in the business environment (such as customer demands and transportation costs) has spurred an interest in designing scalable and robust supply chains. This paper proposes a robust optimization model for handling the inherent uncertainty of input data in a closed-loop supply chain network design problem. First, a deterministic mixed-integer linear programming model is developed for designing a closed-loop supply chain network. Then, the robust counterpart of the proposed mixed-integer linear programming model is presented by using the recent extensions in robust optimization theory. Finally, to assess the robustness of the solutions obtained by the novel robust optimization model, they are compared to those generated by the deterministic mixed-integer linear programming model in a number of realizations under different test problems.     

Dual-channel closed-loop supply chain with government consumption-subsidy

The government has been acting as an important role in the formation and operation of closed-loop supply chain. This paper focuses on how consumption-subsidy influences dual-channel closed-loop supply chain. After introducing government consumption-subsidy program and dual-channel closed-loop supply chain, the paper analyzes the channel members’ decisions before and after the government-funded program performance, respectively. Finally, influence of consumption-subsidy has been considered from the consumers, the scale of closed-loop supply chain and the enterprises perspectives, which provides an important basis for our propositions. The key propositions of the paper are listed as follows: All the consumers that purchase the new products are beneficiaries of the government consumption-subsidy in varying degrees; the consumption-subsidy is conducive to the expansion of closed-loop supply chain; both the manufacturer and the retailer are beneficiaries of the consumption-subsidy, while the e-tailer benefits or not is uncertain.     

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.     

Pareto analysis of supply chain contracts under satisficing objectives

Supply chain coordination has become critical to firms as increased pressure is placed on them to improve performance. We evaluate the performance of Push, Pull, and Advance-purchase discount (APD) contracts in a manufacturer-retailer supply chain where one or both firms have a satisficing objective of maximizing the probability of achieving a target profit. We identify the resulting operational modes of the supply chain and potential conflicts over the preferred contracts under the Push, Pull, and APD contracts. When both firms are satisficing, conflict over the preferred contract arises when the manufacturer has an ambitious profit target or the retailer has a low profit target. We show that the Push contract can result in a large decrease in the expected profit of a risk-neutral manufacturer when the retailer maximizes the probability of achieving her maximum expected profit. We find that a modified buy-back and profit guarantee contracts can provide significant Pareto improvement over Push or APD contracts when the manufacturer is risk-neutral and the retailer is satisficing, while revenue-sharing contracts cannot. In contrast, revenue sharing and modified buy-back contracts are Pareto dominant under certain conditions when the manufacturer is satisficing and the retailer is risk-neutral.     

Compensation plan for competing salespersons under asymmetric information

We investigate the optimal compensation scheme involving one firm and two competing salespersons deployed in different territories under asymmetric information. The problem is analyzed using a two-stage game. In the first stage, the firm announces the compensation plans. The two salespersons, who are closer to customers, have superior market information and then simultaneously but independently decide which plans to sign. The firm decides the production quantity and the salespersons independently make effort decisions. In the second stage, sales volumes are realized and the associate payments are made.     

Preferences for contractual forms in supply chains

The supply chain contracting literature has focused on incentive contracts designed to align supply chain members’ individual interests. A key finding of this literature is that members’ preferences for contractual forms are often at odds: the upstream supplier prefers relatively complex contracts that can coordinate the supply chain; however, the downstream retailer prefers a wholesale price-only contract because it leaves more surplus (than does a coordinating contract), which the retailer can capture. This paper addresses the following question: Under what circumstances do suppliers and retailers prefer the same contractual form? We study supply chain members’ preferences for contractual forms under three different competitive settings in which multiple supply chains compete to sell substitutable products in the same market. Our analysis suggests that both upstream and downstream sides of the supply chain may prefer the same “quantity discount” contract, which would eliminate the conflicts of interest that otherwise typify contracting situations. More interesting still is that both sides may also prefer the wholesale price-only contract; this finding provides a theoretical explanation for why that inefficient (but simple) contract is widely adopted in supply chain transactions.     

Sustaining long-term supply chain partnerships using price-only contracts

In this paper, we study how an informal, long-term relationship between a manufacturer and a retailer performs in turbulent market environments characterized by uncertain demand. We show that the long-term partnership based on repeated interaction is sustainable under price-only contracts when the supply chain partners are sufficiently patient. That is, the channel can be coordinated over a long time horizon when the factor whereby the members discount the future value of this trusting relationship is sufficiently high. Second, above the minimum discount factor, a range of wholesale prices exists that can sustain the long-term partnership, and there are different possible profit divisions between the two players. Third, when the market is turbulent, i.e., either the expected demand or the demand variance changes from period to period according to a probabilistic law, it is typically less possible to sustain the long-term partnership in a booming market or in a market with low demand variability. Finally, obtaining more information about future market fluctuation may not help the supply chain to sustain the long-term partnership, due to partners’ strategic considerations. With the availability of the market signal, total supply chain profits increase, but the retailer may even be worse-off.     

Scalable methodology for supply chain inventory coordination with private information

This paper considers the problems of coordinating serial and assembly inventory systems with private information where end-item demands are known over a finite horizon. In a private information environment, the objective function and cost parameters of each facility are regarded as private information that no other facilities in the system have access to. The solution approach decomposes the problem into separable subproblems such that the private information is partitioned as required. Global optimality is sought with an iterative procedure in which the subproblems negotiate the level of material flows between facilities. At the core of the solution procedure is a supplier–buyer link model that can be used as a building block to form other supply chain configurations. Experimental results show that the proposed methodology provides promising results when compared to competing methodologies that disregard information privacy.     

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.     

Reverse channel decisions for a fuzzy closed-loop supply chain

This article reports the results of a study that explores the decisions of reverse channel choice in a fuzzy closed-loop supply chain. Specifically, a manufacturer produces new products by using original components or by remanufacturing used products and wholesales the new products to the retailer who then sells them to the consumers. The used products are collected by the manufacturer or the retailer or a third party. The primary goal of this paper is to investigate the implications of three different used-product collection modes on the decisions of the manufacturer, the retailer, and the third party, and on their own profits in the expected value model. By using game theory and fuzzy theory, the firms optimal strategies are obtained.     

A distributed coordination mechanism for supply networks with asymmetric information

The paper analyses the problem of coordination in supply networks of multiple retailers and a single supplier, where partners have asymmetric, private information of demand and costs. After stating generic requirements like distributedness, truthfulness, efficiency and budget balance, we use the apparatus of mechanism design to devise a coordination mechanism that guarantees the above properties in the network. The resulting protocol is a novel realisation of the widely used Vendor Managed Inventory (VMI) where the responsibility of planning is at the supplier. We prove that together with the required generic properties a fair sharing of risks and benefits cannot be guaranteed. We illustrate the general mechanism with a detailed discussion of a specialised version, assuming that inventory planning is done according to the newsvendor model, and explore the operation of this protocol through computational experiments.     

‘Too Little’ or ‘Too Late’: The timing of supply chain demand collaboration

This study examines the supply chain demand collaboration between a manufacturer and a retailer. We study how the timing of collaboration facilitates production decision of the manufacturer when the information exchanged in the collaboration is asymmetric. We investigate two collaboration mechanisms: ‘Too Little’ and ‘Too Late’, depending on the timing of information sharing between the manufacturer and the retailer. Our research results indicate that early collaboration as in the ‘Too Little’ mechanism leads to a stable production schedule, which decreases the need of production adjustment when production cost information becomes available; whereas a late collaboration as in the ‘Too Late’ mechanism enhances the flexibility of production adjustment when demand information warrants it. In addition, the asymmetric demand information confounds production decisions all the time; the manufacturer has to provide proper incentives to ensure truthful information sharing in collaboration. Information asymmetry might also reduce the difference in production decision between the ‘Too Little’ and ‘Too Late’ collaboration mechanisms. Numerical analysis is further conducted to demonstrate the performance implications of the collaboration mechanisms on the supply chain.     

The use of advance demand information in a project-based supply chain

In a project environment, a manufacturer is confronted with two types of demand: regular demand from many small orders and very irregular, lumpy demand from infrequent, large orders. Manufacturers who build to stock must carry large safety stocks to meet the lumpy demand. As part of the project engineering process, however, project engineers and implementers (e.g. installers) typically have developed information about material requirements well in advance of placement of orders. We analyze the inventory reduction that could be achieved if the installer were to communicate advance demand information (ADI) to the manufacturer. We look at it in particular when the bid is placed. We focus on the following characteristics of available ADI in project environments: First, ADI information is uncertain, because decisions on installer and manufacturer selection have not yet been finalized. Second, information is detailed, available at the item level. We show that ADI is particularly valuable when potential demand for large projects is irregular and when proposals for potential projects have a high probability of leading to orders.     

Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques

Recently, there is a growing concern about the environmental and social footprint of business operations. While most of the papers in the field of supply chain network design focus on economic performance, recently, some studies have considered environmental dimensions.     

The value of information in a capacitated closed loop supply chain

We explore the value of information in the context of a firm that faces uncertainty with respect to demand, product returns, recovery yield, and capacity utilization. Capacity is finite and shared between new production and recovery operations. The operational decisions of interest are the quantity of new product to produce, the quantity of returns to recover, and the quantity of returns to dispose. Product recovery is uncertain in that each returned unit can be successfully recovered with a known probability, and otherwise it is discarded at a cost. Demand in a period is satisfied with new production, recovered returns, or a mix of both types.     

A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return

A closed-loop supply chain (CLSC) network consists of both forward and reverse supply chains. In this paper, a CLSC network is investigated which includes multiple plants, collection centres, demand markets, and products. To this aim, a mixed-integer linear programming model is proposed that minimizes the total cost. Besides, two test problems are examined. The model is extended to consider environmental factors by weighed sums and ε-constraint methods. In addition, we investigate the impact of demand and return uncertainties on the network configuration by stochastic programming (scenario-based). Computational results show that the model can handle demand and return uncertainties, simultaneously.