| This dissertation focuses on exploring how companies design and adjust purchasing, inventory, and selling strategies when facing stochastic purchasing prices.;First we develop a supply contract that considers environments with changing prices, we then investigate characterization properties of the price processes, and determine expressions of the contract's expected low price and its second moment for a given horizon, then we identify an expected optimum time before the contract expires at which the lowest price occurs. Simulation experiments verify our analysis, and they illustrate how the optimum purchase time decreases as the change rate of the cost increases.;Next, we analyze purchasing strategies for retailers regarding the best timing and amount of purchases when operating under combined timing and quantity flexibility contracts in an environment of uncertain prices. To decrease the computational complexity and make the procedure adaptable to the case of multiple suppliers, we develop, analyze, and compare a Time Strategy and a Target Strategy and then combine these methods into an approximate algorithm to facilitate the purchasing decision in a more efficient way. We then extend the solution procedure to the multiple suppliers case.;Last we study the problem of planning the procurement and sales for a newsvendor for whom the price of the raw material fluctuates along time and the demand of the output product is random and price-sensitive. After we provide a backward deduction method to solve this problem, we provide an efficient solution algorithm adapted for multiple-supplier cases and long-term-length scenarios, and a corresponding lower bound for the expected profit. We further analyze how to choose between a forward contract and spot market purchasing. Then we extend the above analysis to the profit and risk analysis in multiple-supplier cases and multiple-period newsvendor cases. Through numerical analysis we demonstrate how the potential supplier base and the parameters influence profit and risk, and the purchasing decisions. |
