| Abstract: | ![]()
In a service environment a service provider needs to determine the amount and kinds of capacity to meet customers’ needs over many periods. To make good decisions, she needs to know the probability distribution of her customers’ demand in each period. We study a situation in which customers’ demand for a given service is random in each period, but inelastic, or modeled well by this assumption, and cannot be delayed to the next period. This article presents a mechanism that allows a service provider to learn the distribution of a customer's demand by offering him a set of contracts through which he can partially prepay for future service for a reduced cost for units of service based on anticipated needs. We describe the form of a set of contracts that will cause the customer to reveal his demand distribution as he minimizes his expected costs. To justify the effort of organizing and offering contracts, we present an application that demonstrates the cost savings to the service provider with better capacity planning using the truthfully elicited distribution. |
