A Stochastic Inventory Model With Fast‐Ship Commitments

We present a multiperiod model of a retail supply chain, consisting of a single supplier and a single retailer, in which regular replenishment occurs periodically but players have the option to support fast delivery when customers experience a stockout during a replenishment period. Because expedited shipments increase the supplier's transportation cost, and possibly production/inventory costs, the supplier typically charges a markup over and above the prevailing wholesale price for fast‐shipped items. When fast shipping is not supported, items are backordered if customers are willing to wait until the start of the next replenishment period. We characterize the retailers and the supplier's optimal stocking and production policies and then utilize our analytical framework to study how the two players respond to changes in supply chain parameters. We identify a sufficient condition such that the centralized supply chain is better off with the fast‐ship option. We find a range of markups for fast‐ship orders such that the fast‐ship option is preferred by both the supplier and the retailer in a decentralized chain. However, a markup that is a win–win for both players may not exist even when offering fast‐ship option is better for the centralized chain. Our analysis also shows that depending on how the markup is determined, greater customer participation in fast‐ship orders does not necessarily imply more profits for the two players. For some predetermined markups, the retailer's profit with the fast‐ship option is higher when more customers are willing to wait. However, the retailer may not be able to benefit from the fast‐ship option because the supplier may choose not to support the fast‐ship option when fast‐ship participation increases due to the fact that the fast‐ship participation rate adversely affects the initial order size.     

Joint Mail‐In Rebate Decisions in Supply Chains Under Demand Uncertainty

We study the joint decisions of offering mail‐in rebates (MIRs) in a single‐manufacturer–single‐retailer supply chain using a game theoretic framework. Either party can offer an MIR to the end consumer if it is in his best interest. The consumer demand is stochastic and depends on the product price and the amount of MIRs. When the retail price is exogenous, we show the existence of a unique Nash equilibrium under both additive and multiplicative demand functions and characterize it completely. We show that any of the following four scenarios can be the equilibrium: both parties offer MIR, only one party offers MIR, none offers MIR. When the retail price is a decision variable for the retailer and the rebate redemption rate increases with the amount of MIR, we once again prove the existence of a unique Nash equilibrium where both the retailer and the manufacturer offer MIRs. Using a numerical study, we show that the average post‐purchase price of the product is higher not only than the perceived pre‐purchase price but also than the newsvendor optimal price without an MIR. This implies that an MIR makes a product look cheaper while the consumers actually pay more on average.     

The Retail Space‐Exchange Problem with Pricing and Space Allocation Decisions

We consider retail space‐exchange problems where two retailers exchange shelf space to increase accessibility to more of their consumers in more locations without opening new stores. Using the Hotelling model, we find two retailers’ optimal prices, given their host and guest space in two stores under the space‐exchange strategy. Next, using the optimal space‐dependent prices, we analyze a non‐cooperative game, where each retailer makes a space allocation decision for the retailer's own store. We show that the two retailers will implement such a strategy in the game, if and only if their stores are large enough to serve more than one‐half of their consumers. Nash equilibrium for the game exists, and its value depends on consumers’ utilities and trip costs as well as the total available space in each retailer's store. Moreover, as a result of the space‐exchange strategy, each retailer's prices in two stores are both higher than the retailer's price before the space exchange, but they may or may not be identical.     

Competitive and Collaborative Quality and Warranty Management in Supply Chains

Product quality and product warranty coverage are two important and closely related operational decisions. A longer warranty protection period can boost sales, but it may also result in dramatically increased warranty cost, if product quality is poor. To investigate how these two decisions interact with each other and influence supply chain performance, we develop a single‐period model with a supplier that provides a product to an original equipment manufacturer, which in turn sells it to customers. Customer demand is random and affected by the length of the product warranty period. Warranty costs are incurred by both the supplier and the manufacturer. We analyze two different scenarios based on which party sets the warranty period: manufacturer warranty and supplier warranty. Product quality is controlled by the supplier, and the manufacturer determines the ordering quantity. We analyze these decentralized systems and provide the structural properties of the equilibrium strategies. We also compare the results of centralized and decentralized systems and identify the conditions under which one system provides a longer warranty and better product quality than the other. Our numerical study further shows that, in decentralized settings, when the warranty period is determined by the firm sharing the larger proportion of total warranty costs, the supply chain can achieve greater system‐wide profit. Both parties can therefore benefit from properly delegating the warranty decision and sharing the resulting additional profit. We further design a supplier‐development and buy‐back contract for coordinating decentralized supply chains. Several extensions are also discussed.     

Distributed Decision‐Making in Supply Chains and Private E‐Marketplaces

This paper develops a distributed decision‐making framework for the players in a supply chain or a private e‐marketplace to collaboratively arrive at a global Pareto‐optimal solution. In this model, no player has complete knowledge about all the costs and constraints of the other players. The decision‐making framework employs an iterative procedure, based on the Integer L‐shaped method, in which a master problem is solved to propose global solutions, and each player uses his local problems to construct feasibility and optimality cuts on the master problem. The master problem is modeled as a mixed‐integer program, and the players' local problems are formulated as linear programs. Collaborative planning scenarios in private e‐marketplaces and in supply chains were formulated and solved for test data. The results show that this distributed model is able to achieve near‐optimal solutions considerably faster than the traditional centralized approach.     

Complexity and Self‐Sustainment in Disaster Response Supply Chains

Governmental organizations play a major role in disaster relief operations. Supply chains set up to respond to disasters differ dramatically in many dimensions that affect the cost of relief efforts. One factor that has been described recently is self‐sustainment, which occurs when supplies consumed by intermediate stages of a supply chain must be provided via the chain itself because they are not locally available. This article applies the concept of self‐sustainment to response supply chains. A mathematical model of a self‐sustaining response supply chain is developed. Analysis of this model yields insights about the relationships and interactions among self‐sustainment, speed of disaster onset, dispersion of impact, and the cost of the relief efforts.     

Competition and Coordination in Two‐Tier Public Service Systems under Government Fiscal Policy

As a result of government budgetary limits and rapid market growth, many public service systems—such as health care—are characterized by extensive customer wait times that have become a serious problem. This problem might be solved by allowing private firms to enter these markets, which would provide customers with a choice between a free (governmental) public service provider (SP) and a fee‐charging (or “toll”) private SP. In such a two‐tier service system, the two SPs are differentiated by service quality and cost efficiency. This study focuses on the competition and coordination issues for two‐tier service systems with customers who are sensitive to both service quality and delay. The free system attempts to maximize its expected total customer utility with limited capacity, whereas the toll system attempts to maximize its profit. Neither goal is aligned with the social welfare goal of the public service. To achieve the social welfare goal, the government plays a crucial role in coordinating the two‐tier service system via the budget, the tradeoff of social members' goals, and tax‐subsidy policies. Using a mixed duopoly game, we establish Nash equilibrium strategies and identify the conditions for the existence of the two‐tier service system. We employ several interesting and counter‐intuitive managerial insights generated by the model to show that the public service can be delivered more efficiently via customer choice and SP competition. In addition, we show that a relatively low tax‐subsidy rate can almost perfectly coordinate the two SPs to achieve most of the maximum possible benefit of the two‐tier service system.     

Model Selection and Estimation with Quantal‐Response Data in Benchmark Risk Assessment

This article describes several approaches for estimating the benchmark dose (BMD) in a risk assessment study with quantal dose‐response data and when there are competing model classes for the dose‐response function. Strategies involving a two‐step approach, a model‐averaging approach, a focused‐inference approach, and a nonparametric approach based on a PAVA‐based estimator of the dose‐response function are described and compared. Attention is raised to the perils involved in data “double‐dipping” and the need to adjust for the model‐selection stage in the estimation procedure. Simulation results are presented comparing the performance of five model selectors and eight BMD estimators. An illustration using a real quantal‐response data set from a carcinogenecity study is provided.     

Local Resources and Procurement Practices in Humanitarian Supply Chains: An Empirical Examination of Large‐Scale House Reconstruction Projects

Different procurement decisions taken by relief organizations can result in considerably different implications in regards to transport, storage, and distribution of humanitarian aid and ultimately can influence the performance of the humanitarian supply chain and the delivery of the humanitarian aid. In this article, we look into what resources are needed and how these resources evolve in the delivery of humanitarian aid. Drawing on the resource‐based view of the firm, we develop a framework to categorize the impact of local resources on the configuration of humanitarian supply chains. In contrast to other papers, the importance of localizing the configuration of the humanitarian supply chain is not only conceptually recognized, but empirical investigations are also provided. In terms of methodology, this article is based on the analysis of secondary data from two housing reconstruction projects. Findings indicate that the use of local resources in humanitarian aid has positive effects on programs’ overall supply chain performance and these effects are not only related to the macroeconomic perspective, but benefits expand to improvements related to the use of knowledge. At the same time, it was found that local sourcing often comes with a number of problems. For example, in one of the cases, significant problems existed, which were related to the scarcity of local supplies. Both housing reconstruction projects have indicated the continuous need for changes throughout the programs as a dynamic supply chain configuration is important for the long‐term sustainability of reconstruction aid.