Incentive-Compatible Revenue Management in Queueing Systems: Optimal Strategic Delay

Abstract

H ow should a firm design a price/lead-time menu and scheduling policy to maximize revenues from heterogeneous time-sensitive customers with private information about their preferences? We consider this question for a queueing system with two customer types and provide the following results. First, we develop a novel problem formulation and solution method that combines the achievable region approach with mechanism design. This approach extends to menu design problems for other systems. Second, the work conserving c priority rule, known to be delay cost minimizing, incentive-compatible, and socially optimal, need not be revenue maximizing. A strategic delay policy may be optimal: It prioritizes impatient customers, but artificially inflates the lead times of patient customers. This suggests a broader guideline: Revenue-maximizing firms that lack customer-level demand information should also consider customer incentives, not only operational constraints, in their scheduling policies. Third, we identify general necessary and sufficient conditions for optimal strategic delay: a price, a lead-time, and a segment-size condition. We translate these into demand and capacity parameter conditions for cases with homogeneous and heterogeneous valuations for each type. In some cases strategic delay is optimal if capacity is relatively abundant, in others if it is relatively scarce.

“We Will Be Right with You”: Managing Customer Expectations with Vague Promises and Cheap Talk

“…The follow-up literature extends Naor (1969) along multiple dimensions. One such stream studies models where the firm offers different grades of services (see Mendelson and Whang (1990) and the recent paper by Afeche (2004)). Another stream focuses on competition in the presence of congestion-sensitive customers (see Cachon and Harker (2002) and the recent paper by Allon and Federgruen (2007)).…”

Optimal pricing and scheduling control of product shipping

“…Classical papers in this field typically treat [2,3] Yes WTP&WTW Linear Two cμ [4] No WTP&WTW Linear Two Uniform [5] Yes WTP&WTW Linear Continuous cμ [6] No WTW&WTP S-shape Multiple Dynamic [10] Yes WTW Linear Two Priority [15] No WTW S-shape Two Dynamic [27] Yes WTW Linear Two FIFS [33] Yes WTP&WTW Linear Multiple Allocation [35] Yes WTP&WTW Linear Multiple cμ [31] Yes WTP&WTW Linear Multiple cμ [20] Yes WTP&WTW Linear Multiple cμ Ours Yes WTP&WTW Linear Multiple cμ [42] No WTP&WTW General Multiple Gcμ [43] No WTP&WTW incr, Convex Two Gĉμ [44] Yes WTP&WTW Linear Two FIFS this problem in a centralized manner (i.e., a central social planner is able to control all the behaviors of sellers, customers, etc. ; see, e.g., [41]).…”

“…• In Table 5, there are 105 cases where type (1,2) customers are accepted and in all these cases these customers are prioritized over type (1,1) customers. 4.…”

Using Strategic Idleness to Improve Customer Service Experience in Service Networks

“…In closing this section we note that (i) the idea of intentionally idling a capacitated resource has also been considered by Afèche (2013). In the revenue management context, he showed how such delays can allow a seller to differentiate between customer types and thus improve the overall profit.…”