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We study a model with a single supplier and a single buyer who interact multiple times before the buyer sells her product in the end-consumer market. We show that when the supplier uses a wholesale price contract, even under perfect foresight, the supplier, the buyer, and the end consumers benefit from multiple trading opportunities versus a one-shot procurement agreement. [ABSTRACT FROM AUTHOR]

In an environment where a buyer procures capacity from a capacitated supplier through a wholesale price contract, the impact of timing of the decisions and of additional demand information on the supplier's pricing and the buyer's procurement decisions are investigated. As the selling season approaches, the buyer and the supplier have better information about the demand process. It is questioned as to what degree waiting until the demand uncertainty is resolved—given that such an option is feasible—is the best alternative for the supply chain partners. The main model is a two-period dynamic pricing/procurement game where the supplier sets wholesale prices dynamically; he sets the second period price after seeing the demand state as well as the buyer's first period procurement quantity. Two single-period models based on the information available to the players prior to their decisions are also studied. For each model, the subgame perfect Nash equilibrium is found in a closed form and the players' behaviors are analyzed to determine the impact of the additional information and trading periods on their welfare. The supplier's optimal capacity decision is also considered. Several additional insights are obtained through numerical experiments. [ABSTRACT FROM AUTHOR]

We present an efficient solution method -- Direct Derivative Estimation (DDE) -- for computing optimal order-up-to levels for a discrete time non-stationary inventory control model. We generalize a number of non-stationary inventory control models (which underlie larger models of supply chains) that include forecast updates. seasonality, information sharing, and exchange-rate fluctuations. This procedure is different from the existing ones in that it computes, in a recursive manner, the derivative of the cost function and not the cost function itself. It can also handle a much wider variety of fluctuations in the problem parameters. In our computational testing it was found to be considerably faster than Dynamic Programming and Infinitesimal Perturbation Analysis. [ABSTRACT FROM AUTHOR]