Designing and Managing Online Service Quality and Product Mix Under Uncertain Demand and Fixed Short-term Capacity

In this paper we explore the problem of maximizing revenue for an Internet service firm that operates in a market of unique short-lived products that have uncertain demand. We look at the short-term problem where the firm has a capacity constraint and has to choose an appropriate product mix such that customers' desired quality-of-service requirements are fulfilled. For example, converging digital technologies of broadcasting and telephony on the Internet require a certain level of service quality for acceptable performance. Internet content providers offering webcasts of special events are examples of such firms in business-to-consumer markets. Companies that deploy commercial video-on-demand servers in high-bandwidth digital cable markets are examples of such firms in businessto-business markets. We model such firms as fixed capacity servers that make pricing and product mix decisions to maximize revenue while satisfying service quality constraints. Our model integrates auction theory, to facilitate dynamic price-discovery, with the knapsack problem. This results in a non-standard knapsack formulation. We analyze the economic incentives of customers and present solution techniques ranging from pseudo-polynomial optimal computations to a class of heuristics that perform well in computational experiments. We provide both, the theoretical worst-case bounds and the computational performance of our heuristics.