Incentive-Compatible Revenue Management in Queueing Systems: Optimal Strategic Delay and other Delaying Tactics

How should a capacity-constrained firm design an incentive-compatible price-scheduling mechanism to maximize revenues from a heterogeneous pool of time-sensitive customers with private information on their willingness to pay, time-sensitivity and processing requirement? We consider this question in the context of a queueing system that serves two customer types. We provide the following insights. First, the familiar cμ priority rule, known to minimize the system-wide expected delay cost and to be incentive-compatible under social optimization, need not be optimal in this setting. This specific fact suggests a more general guideline: in designing incentive-compatible and revenue-maximizing scheduling policies, delay cost-minimization, which plays a prominent role in controlling and pricing queueing systems, should not be the dominant criterion ex ante. Second, we identify optimal scheduling policies with novel features. One such policy prioritizes the more time-sensitive customers but voluntarily delays the completed orders of low-priority customers. This insertion of strategic delay deters time-sensitive customers from purchasing the low-priority class. In other situations, it is optimal to appropriately randomize priority assignments, in one extreme case serving customers in the reverse cμ order, which maximizes the system delay cost among all work conserving policies. Compared to the cμ rule, these optimal policies increase, decrease or reverse the delay differentiation between customer types. We show how the optimal level of delay differentiation systematically emerges from a trade-off between operational constraints and customer incentives. Third, our stepwise solution approach can be adapted for designing revenue-maximizing and incentive-compatible mechanisms in systems with different customer attributes or operational properties.