This study considers a stochastic inventory management problem where a capital-constrained firm can obtain additional working capital through inventory-based financing (IBF) by pledging its inventory to obtain loans from a lender. We show that the firm's optimal inventory policy in each period may order new inventory up to a state-dependent order-up-to level subject to the firm's capital and IBF loan constraints, or salvage existing inventory down to a state-dependent salvage-down-to level. We further partially characterize the structures of the two state-dependent levels in each period. Through analytical and numerical studies, we offer a number of new insights regarding the optimal inventory management for a capital-constrained firm with access to inventory-based financing. In particular, we find that when the firm anticipates a shortage of capital with which to meet high demands in a future period, it may strategically over-stock its inventory in earlier periods in order to secure the necessary capital. Through extensive numerical studies, our study also demonstrates how some of the key parameters may affect the optimal inventory policy and the value of IBF.

Trade credit is an important form of short-term financing for capital-constrained small firms. In this paper, we build a supply chain model consisting of one supplier and two competing retailers to investigate the impacts of trade credit on both vertical and horizontal supply chain interactions. The supplier is a large-scale manufacturer with a strong financial status that can offer trade credit to the two downstream retailers who may be financially constrained. The two retailers are engaged in Cournot competition with uncertain market demands. The demand risks may expose a financially distressed retailer to bankruptcy risk, which may be transmitted vertically through trade credit to the upstream supplier. Horizontally, the trade credit and the ensuing bankruptcy risk of one retailer will also affect the other retailer’s competition behavior and profit. We find that trade credit has two opposite effects on downstream retailers’ selling quantity decisions: it may either aggravate or soften two retailers’ competition. Interestingly, when two retailers have unbalanced financial statuses, the supplier may bail-out the financially distressed retailer, and the predation between two retailers exhibits a bidirectional pattern. Moreover, we show that a retailer always benefits from a better financial status. Improvement of the competitor’s financial status, however, may be either beneficial or harmful to the retailer, depending on the demand uncertainty and competition intensity. The supplier’s preference for the retailers’ financial statuses may also be influenced by the demand uncertainty and competition intensity.

Motivated by emerging practice in the cut flower industry, we consider a periodic-review inventory system for a perishable product with a lifetime of two periods. There are two separate customer demands for the new product with two-period remaining lifetime and the old product with one-period remaining lifetime, and a fixed proportion of the unsatisfied demand for one product will purchase the other product as a substitute. One distinctive feature of our system is that a random portion of the sold new product is returned and can be remanufactured and remarketed as the old product for sale. The objective is to maximize the expected total discounted profit over a finite planning horizon. We show that the optimal remanufacturing policy is a modified base–stock policy, and that the optimal manufacturing quantity of the new product decreases in the inventory level of the old product after remanufacturing. Furthermore, when the inventory level of the old product is large, the optimal manufacturing quantity asymptotically approaches a constant, which is lower and upper bounded by two newsvendor fractile solutions. We also conduct a numerical study to derive insights into the effects of remanufacturing and demand substitution. In particular, we show that remanufacturing can be a powerful way of mitigating negative environmental impacts in the cut flower industry. Finally, we discuss two model extensions that allow a joint production capacity and a multi-period lifetime.

Observing prevalent concerns about the influence of carbon emissions on climate change, we address the problem of remanufacturing with trade-ins under carbon regulations. We analyze the optimal pricing and production decisions of the manufacturer under the carbon tax policy and the cap and trade program. The results show that the introduction of carbon regulations can promote sales of remanufactured products while reducing the demands of new products. However, the implementation of carbon regulations has negative impacts on the manufacturer's profits. Nevertheless, the manufacturer's profits can be improved through deliberately designed government subsidy schemes. We also demonstrate that the government has the incentive to propose such subsidy schemes because the total emissions can be reduced under well-designed regulations, but not at the cost of the manufacturer's profits.

Three kinds of decision models for closed-loop supply chain (CLSC) with trade-ins are developed in this paper, including the centralized collection (Model C), the retailer collection (Model R), and the manufacturer collection (Model M). By analyzing these models, we argue that there are three types of optimal collection strategies, namely, no collection, partial collection, and full collection. We provide conditions under which one of these three collection strategies is optimal for different supply chain models. By comparing the impact of trade-ins on these different supply chain models, we find that only when the direct net value of a used product derived from the trade-ins for the whole CLSC system including the consumers is high enough can trade-in strategy be adopted to stimulate consumer demand and improve the manufacturer׳s and retailer׳s profit. Based on the life-cycle assessment method, we find that when the marginal effect of the product on environment in the continue-to-use phase is more significant than in other phases, trade-ins can promote the environmental performance of the CLSC system. Further, by comparing the optimal solutions for the different models, we find that one collection model may dominate the others in terms of the economic performance of the involved parties. Specifically, Model M dominates Model R in terms of the profits of the manufacturer and the profits of the whole supply chain; Model R dominates Model M in terms of retailer׳s profit; and Model R dominates all other models in terms of environmental performance.

We consider a manufacturer facing single period inventory planning problem with uncertain demand and multiple options of expediting. The demand comes at a certain time in the future. The manufacturer may order the product in advance with a relatively low cost. She can order additional amount by expediting after the demand is realized. There are a number of expediting options, each of which corresponds to a certain delivery lead time and a unit procurement price. The unit procurement price is decreasing over delivery lead time. The selling price is also decreasing over time. In this paper, we assume that the manufacturer must deliver all products to the customer in a single shipment. The problem can be formulated as a profit maximization problem. We develop structural properties and show how the optimal solution can be identified efficiently. In addition, we compare our model with the classical newsvendor model and obtain a number of managerial insights. Highlights ► We consider a newsvendor problem with multiple options of expediting. ► We develop a number of structural properties that help to solve the problem efficiently. ► We examine how the demand variation affects the optimal decisions and profits.

Recently, crossdocking techniques have been successfully applied in responsive supply chain management. However, most researches focused on physical layout of a crossdock, or scheduling operations within a crossdock. In this paper, we study a multi-crossdock transshipment service problem with both soft and hard time windows. The flows from suppliers to customers via the crossdocks are constrained by fixed transportation schedules. Cargos can be delayed and consolidated in crossdocks, and both suppliers and customers have specific hard time windows. In addition to hard time windows, customers also have less-restrictive time windows, called soft time windows. The problem to minimize the total cost of the multi-crossdock distribution network, including transportation cost, inventory handling cost and penalty cost, can be proved to be NP-hard in the strong sense and hence efficient heuristics are desired. We propose two types of meta-heuristic algorithms, called Adaptive Tabu Search and Adaptive Genetic Algorithm, respectively, to solve the problem efficiently. We conduct extensive experiments and the results show that both of them outperform CPLEX solver and provide fairly good solutions within realistic timescales. We also perform sensitivity analysis and obtain a number of managerial insights.

In this article, we consider the performance evaluation of a multicomponent, multiproduct assemble-to-order (ATO) system. Each component is managed independently using a base-stock policy at a supply facility with limited production capacity and an infinite buffer. The arrivals of demands follow a multivariate Poisson process and unfilled demands are backlogged. Because exact analysis of the proposed system is not feasible, we propose two approximation methods which provide upper and lower bounds for various performance measures such as fill rate, average waiting time, and average number of backorders of the proposed system. Our computational experiments demonstrate the effectiveness of the two approximation methods under various system settings. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011

We consider a component acquisition problem for a contract manufacturer who faces a one-time stochastic demand for a single product consisting of a number of components. Components can be ordered early at normal prices before the demand is revealed, or they can be replenished later at higher prices due to expediting. In addition, the customer pays a price for the final product that is nonincreasing in the delivery lead time to discourage late delivery. We propose a cost-minimization model and develop an efficient polynomial time algorithm to solve the problem.

This paper considers an inventory and production-planning problem for a contract manufacturer who anticipates an order of a single product, but with uncertain quantity. To meet the challenges of long component procurement lead times and limited assembly capacity, which may render production time insufficient to assemble total order quantity, the manufacturer may need to procure components or even assemble some quantities of the final product before receiving the confirmation of the actual order quantity. We present profit-maximization models that make optimal inventory and production decisions in the above assemble-to-order environment. We also consider the option of outsourcing, so that the manufacturer can outsource part of his production to an external facility that also has limited capacity. We establish structural properties of optimal solutions and develop efficient solution procedures for the proposed problems. We also provide sensitivity analysis of the optimal decisions, and some managerial insights.