Stuart X. Zhu

Pricing and Lead Time Decisions in Decentralized Supply Chains

This paper studies a decentralized supply chain consisting of a supplier and a retailer facing price-and lead-time-sensitive demands. A Stackelberg game is constructed to analyze the price and lead time decisions by the supplier as the leader and the retailer as the follower. The equilibrium strategies of the two players are obtained. Using the performance of the corresponding centralized system as a benchmark, we show that decentralized decisions in general are inefficient and lead to inferior performance due to the double marginalization effect. However, further analysis shows that the decision inefficiency is strongly influenced by market and operational factors, and if the operational factors are dominating, it may not be significant. This shows that before pursuing a coordination strategy with retailers, a supplier should first improve his or her own internal operations.

Competition for cores in remanufacturing

We study competition between an original equipment manufacturer (OEM) and an independently operating remanufacturer (IO). Different from the existing literature, the OEM and IO compete not only for selling their products but also for collecting returned products (cores) through their acquisition prices. We consider a two-period model with manufacturing by the OEM in the first period, and manufacturing as well as remanufacturing in the second period. We find the optimal policies for both players by establishing a Nash equilibrium in the second period, and then determine the optimal manufacturing decision for the OEM in the first period. This leads to a number of managerial insights. One interesting result is that the acquisition price of the OEM only depends on its own cost structure, and not on the acquisition price of the IO. Further insights are obtained from a numerical investigation. We find that when the cost benefits of remanufacturing diminishes and the IO has more chance to collect the available cores, the OEM manufactures less in the first period as the market in the second period gets larger to protect its market share. Finally, we consider the case where consumers have lower willingness to pay for the remanufactured products and find that in that case remanufacturing becomes less profitable overall.

The risk-averse newsvendor problem with random capacity

We study the effect of capacity uncertainty on the inventory decisions of a risk-averse newsvendor. We consider two well-known risk criteria, namely Value-at-Risk (VaR) included as a constraint and Conditional Value-at-Risk (CVaR). For the risk-neutral newsvendor, we find that the optimal order quantity is not affected by the capacity uncertainty. However, this result does not hold for the risk-averse newsvendor problem. Specifically, we find that capacity uncertainty decreases the order quantity under the CVaR criterion. Under the VaR constraint, capacity uncertainty leads to an order decrease for low confidence levels, but to an order increase for high confidence levels. This implies that the risk criterion should be carefully selected as it has an important effect on inventory decisions. This is shown for the newsvendor problem, but is also likely to hold for other inventory control problems that future research can address.

Optimal core acquisition and pricing strategies for hybrid manufacturing and remanufacturing systems

In this study, we combine two aspects of remanufacturing, namely product acquisition management and marketing (pricing) of the remanufactured products. We consider an original equipment manufacturer (OEM) who decides on the acquisition prices offered for returns from different quality types and on selling prices of new and remanufactured products, in a single period setting. We develop a procedure for determining the optimal prices and corresponding profit of the OEM, and conduct a sensitivity analysis to understand the effect of different model parameters on the optimal strategies and profit. An important managerial insight is that the optimal solution is not to have the same profit per remanufactured item for all return types, but to if the minimum cost for acquisition and remanufacturing of some core type is lower.

Joint pricing and inventory replenishment decisions with returns and expediting

We study a single-item periodic-review model for the joint pricing and inventory replenishment problem with returns and expediting. Demand in consecutive periods are independent random variables and their distributions are price sensitive. At the end of each period, after the demand is realized, a buyer can return excess stocks to a supplier. Or, if there are stockouts, the buyer can place an expediting order at the supplier to reduce the amount of shortage. Unfilled demands are fully backlogged. We characterize the optimal dynamic policy that determines the pricing, inventory replenishment, and adjustment decisions in each period so that the total expected discounted profit is maximized. For a very general stochastic demand function, we can show that the optimal replenishment policy is a modified base-stock policy, the optimal pricing policy is a modified base-stock-list-price policy, and the optimal policy for inventory adjustment follows a dual-threshold policy. We further study the operational effect of returns and expediting. Analytical and numerical results demonstrate that returns and expediting lead to a significant profit increase in a number of situations, including limited supply capacity, sufficient flexibility of the expediting order, high demand uncertainty, and a price-sensitive market.

Optimal policies for the berth allocation problem under stochastic nature

Key purpose of container terminals is to serve container vessels. Container vessels may be of different types such as large deep-sea vessels or feeders and barges. Container terminal operators have to deploy intelligent strategies for the allocation of their limited resources to the calling vessels of those different types. The presence of uncertainty in the real processing of the operational schedules and arrival of vessels adds to the complexity of the already multifaceted problem. An inefficient decision in the berth allocation phase affects all the other applications connected to this and may increase the service period and costs. In this study, we propose a framework based on stochastic dynamic programing approach to model the berth allocation problem and characterize optimal polices under stochastic arrival and handling times for different types of calling vessels. We find that the optimal control policy is of threshold type depending on the number of vessels in a certain berth group. The derived policies can be used at container terminals for the optimal use of their berthing facilities.

Analysis of gray markets in differentiated duopoly

In recent years, gray markets have become a significant phenomenon in the business practice. This paper investigates the gray markets issues in differentiated duopoly case by considering quantity competition among firms. We develop a game-theoretic model and provide equilibrium results for three scenarios, i.e. the benchmark scenario ‘no gray market’, the scenario ‘parallel imports act as a buffer against a follower’s product’ and the scenario ‘gray markets stimulate the competition’. By the analysis of the equilibrium results, some important managerial insights are obtained. Finally, by comparison of the equilibrium results among different scenarios, we study the impact of gray markets on manufacturers’ optimal strategies and profits in differentiated duopoly.

Optimal Remanufacturing and Pricing Strategies Under Name-Your-Own-Price Auctions and Stochastic Demand

In this paper, we study recycling, remanufacturing, and pricing strategies of a manufacturer in a closed-loop supply chain. Different from traditional list-price transaction, a name-your-own-price auction is introduced into the recycling process where consumers offer a bid for their own used items and the manufacturer decides whether to accept the bid. We first analyze the consumers’ behavior and find that their bids increase with the dealing cost. Next, we build a newsvendor framework to investigate the manufacturer’s optimal manufacturing with pricing strategies and find that the stocking factor influences the recycling quantity and manufacturing policy. Moreover, we find that a larger salvage value motivates the manufacturer to set a higher stocking factor and thus recycle more as well as manufacture new products. We further investigate the effect of the demand uncertain level and the dealing cost on the system.

A simultaneous facility location and vehicle routing problem arising in health care logistics in the Netherlands

Abstract This paper introduces a simultaneous facility location and vehicle routing problem that arises in health care logistics in the Netherlands. In this problem, the delivery of medication from a local pharmacy can occur via lockers, from where patients that are within the coverage distance of a locker can collect their medication, or by home delivery. The aim of the problem is to determine which lockers from a set of potential locker locations to open and to generate routes that visit the opened lockers and routes that visit the patients that are not covered by the opened lockers, while minimizing the routing costs and the opening costs of the lockers. We formally define this problem and solve it by applying a branch-and-bound algorithm to this mathematical formulation. Moreover, we propose a fast hybrid heuristic to solve the problem. Extensive computational results are given on a randomly generated instance set and an instance set inspired by practice from Alliance Healthcare Netherlands, an industrial partner. Our results indicate that our heuristic is able to consistently outperform a commercial solver applied to the mathematical formulation, and that its solutions are extremely robust. We provide important business insights on several parameters of the problem.

Integrated Passenger and Freight Train Planning on Shared-Use Corridors

Our study involves the decision-making problems that railway infrastructure managers face in a rail network with dedicated tracks and shared-use corridors. We will analyze the consolidation strategy for shared-use corridors, where the track serves passenger and freight trains. In the stochastic demand case, we will provide an analytical model for the railway infrastructure manager to compute the expected long-term profit using a consolidation system. We will pinpoint the different characteristics of passenger and freight trains, and analytically derive the optimum track allocation and consolidation time, together with the optimum price, in all such cases, using two different model structures, i.e., the additive and the multiplicative forms. We will extend our model further to consider the due-date requirements and volume incentives for railway operators. Our experiments will use realistic parameter values, based on the Dutch railway system.