6,524 research outputs found

    Buy Now and Price Later: Supply Contracts with Time-Consistent Mean-Variance Financial Hedging

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    We consider a two-stage supply chain comprising one risk-neutral manufacturer (he) and one risk-averse retailer (she), where the manufacturer procures consumption commodities in spot market as major inputs for production and sells the final products to the retailer. The retailer then sells the final products to the market at a stochastic clearance price. We investigate a flexible price contract that allows the manufacturer to determine the product wholesale price, and the retailer to determine the order quantity, based on the future spot price of consumption commodities. Compared with the simple wholesale price contract, a win-win situation can be achieved under the flexible price contract when the manufacturer's postponed processing cost is lower than a threshold. However, under this flexible price contract the retailer may suffer from the commodity price volatility, even if she does not procure the commodities directly. We further investigate how the risk-averse retailer conducts mean-variance financial hedging by purchasing consumption commodity futures contracts. We formulate the problem using a dynamic programming model and derive a closed-form time-consistent financial hedging policy. Through numerical experiments, we show that the commodity price risk from the manufacturer to the retailer is effectively mitigated with the hedging, and the benefits of the flexible price contract are maintained

    Supply chain contracting coordination for fresh products with fresh-keeping effort

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    Purpose – Fresh product loss rates in supply chain operations are particularly high due to the nature of perishable products. This paper aims to maximize profit through the contract between retailer and supplier. The optimized prices for the retailer and the supplier, taking the fresh-keeping effort into consideration, are derived. Design/methodology/approach – To address this issue, we consider a two-echelon supply chain consisting of a retailer and a supplier (i.e., wholesaler) for two scenarios: centralized and decentralized decision-making. We start from investigating the optimal decision in the centralized supply chain and then comparing the results with those of the decentralized decision. Meanwhile, a fresh-keeping cost-sharing contract and a fresh-keeping cost- and revenue-sharing contract are designed. Numerical examples are provided, and managerial insights are discussed at end. Findings – The results show that (a) the centralized decision is more profitable than the decentralized decision; (b) a fresh product supply chain can only be coordinated through a fresh-keeping cost- and revenue-sharing contract; (c) the optimal retail price, wholesale price and fresh-keeping effort can all be achieved; (d) the profit of a fresh product supply chain is positively related to consumers’ sensitivity to freshness and negatively correlated with their sensitivity to price. Originality/value – Few studies have considered fresh-keeping effort as a decision variable in the modelling of supply chain. In this paper, a mathematical model for the fresh-keeping effort and for price decisions in a supply chain is developed. In particular, fresh-keeping cost sharing contract and revenue-sharing contract are examined simultaneously in the study of the supply chain coordination problem

    Essays in inventory decisions under uncertainty

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    Uncertainty is a norm in business decisions. In this research, we focus on the inventory decisions for companies with uncertain customer demands. We first investigate forward buying strategies for single stage inventory decisions. The situation is common in commodity industry where prices often fluctuate significantly from one purchasing opportunity to the next and demands are random. We propose a combined heuristic to determine the optimal number of future periods a firm should purchase at each ordering opportunity in order to maximize total expected profit when there is uncertainty in future demand and future buying price. Second, we study the complexities of bundling of products in an Assemble-To-Order (ATO) environment. We outline a salvage manipulator mechanism that coordinates the decentralized supply chain. Third, we extend our salvage manipulator mechanism to a two stage supply chain with a long cumulative lead time. With significant lead times, the assumption that the suppliers all see the same demand distribution as the retailer cannot be used.Ph.D.Committee Chair: Yih-Long Chang; Committee Member: Paul Griffin; Committee Member: Ravi Subramanian; Committee Member: Soumen Ghosh; Committee Member: Srinagesh Gavirnen

    Decision behavior in supply chains with random production yields

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    Dealing with supply risks is one of the challenges of decision makers in supply chains as producing and sourcing become more and more complex. Theoretical research on different types of supply uncertainty as well as their management is well covered. Behavioral aspects in this context, however, have not received much attention so far. In this paper, we present an experimental study which aims at investigating how subjects make decisions of ordering and producing in the presence of random production yields at a supplier, i.e. production output is a random fraction of production input. Subjects were confronted with the situation of either the buyer or the supplier in a simple two-tier supply chain with deterministic demand and had to make the respective quantity decisions. Results show that buyers have a good understanding of the situation and are likely to follow a probabilistic choice rule. In addition to that, hedging against supply risks drives their behavior of over-ordering. Suppliers on the other hand start off with moderate production decisions but improve over time which indicates learning effects. Furthermore, the study shows that additional sharing of information on yield rates is no cure for inefficient behavior of the buyer

    The Value of Supply Chain Finance

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    Optimal Decisions of a Supply Chain with Two Risk-Averse and Competing Retailers under Random Demand

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    This paper investigates the optimal decisions in a decentralized supply chain consisting of one manufacturer and two competing retailers who face price-sensitive and stochastic demand. The retailers are risk averse with conditional value at risk (CVaR) as their risk measure, and the manufacturer is a risk-neutral agent. We construct manufacturer-Stackelberg games with retailers, who engage in horizontal price competition. For the multiplicative demand model and expected demand as an exponential function of both prices, we show that there exists the optimal pricing-ordering joint decision uniquely. We then explore the influence of the price sensitivity, risk aversion, and retail competition on optimal decisions and channel efficiency. The results show that retail competition contributes to manufacturer and improves channel efficiency of the decentralized supply chain. When the retailers are more risk averse, the channel efficiency becomes much lower. However, the level of retailers’ risk aversion has no significant impact on the manufacturer’s optimal wholesale price and retailer’s optimal selling price

    Addressing the sample size problem in behavioural operational research: simulating the newsvendor problem

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    Laboratory-based experimental studies with human participants are beneficial for testing hypotheses in behavioural operational research. However, such experiments are not without their problems. One specific problem is obtaining a sufficient sample size, not only in terms of the number of participants but also the time they are willing to devote to an experiment. In this paper, we explore how agent-based simulation (ABS) can be used to address the sample size problem and demonstrate the approach in the newsvendor setting. The decision-making strategies of a small sample of individual decision-makers are determined through laboratory experiments. The interactions of these suppliers and retailers are then simulated using an ABS to generate a large sample set of decisions. With only a small number of participants, we demonstrate that it is possible to produce similar results to previous experimental studies that involved much larger sample sizes. We conclude that ABS provides the potential to extend the scope of experimental research in behavioural operational research
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