Incorporating Buyer Behavior to Drive Supply Chain Operations

Exogenous demand assumptions provide accurate results at the retail level. As we go in the supply chain, the orders of the buyers get more complicated. The orders are influenced by both the decisions of the supplier and the costs of the buyer’s operations. Therefore, it is critical for a supplier to understand the ordering behavior of a buyer in order to manage her operations. We consider a two-stage supply chain where the buyer faces a stationary and stochastic demand from his customers. The buyer places an order to maximize his profits. We provide a theoretical and empirical framework to analyze the buyer behavior. We study two practical problems: design of quantity discounts and handling reported forecasts. Our goal is to improve the supplier’s operations through a better understanding of the buyer’s ordering behavior. In the first part, we study an all-unit quantity discount problem under stochastic demand for a single-item in a single supplier, single buyer setting. First, we analyze the buyer’s problem. For a single period, we derive the buyer’s optimal policy, which we call a three-index policy. We investigate the structure of the optimal policy for the infinite horizon problem and show that higher index policies with complex order structures may turn out to be optimal. We characterize the conditions under which such order structures are observed and identify two strategies, wait-and-see and buy-and-hold, that complicate the optimal policy. With a numerical analysis, we show that for the infinite horizon problem the performance of the best three-index policy is within 4.5% of the optimal, with an average deviation of no more than 1%. Next, we look into the supplier’s problem. We suggest dis-