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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

We consider a commodity procurement problem where a firm satisfies a future customer demand with uncertainty risk via spot trading and forward sourcing. Although the firm can make demand forecast update and hence, remove demand uncertainty when the selling season arrives, it is still susceptible to a high emergency logistics cost at that time spot. Therefore, in this paper, the tradeoff between the mismatching cost of supply and uncertain demand (highest at the beginning of the planning horizon) and the high at-once delivery cost (highest at the ending of the planning horizon) is investigated. We develop a two-stage model and derive the optimal procurement policy for the firm. We also characterize the optimal parameters by assuming demand follows a bivariate normal distribution. Finally, extensive Monte-Carlo simulation is conducted and we quantify the value of forward contracts and the value of information update, using the crude oil data.