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Coverage, Coarseness, and Classification: Determinants of Social Efficiency in Priority Queues

Author

Listed:
  • Itai Gurvich

    (Cornell School of Operations Research and Information Engineering and Cornell Tech, New York, New York 10044)

  • Martin A. Lariviere

    (Kellogg School of Management, Northwestern University, Evanston Illinois 60208)

  • Can Ozkan

    (Gap Inc., San Francisco, California 94105)

Abstract

Customers often resent priority queues even though priorities are often necessary to maximize either social welfare or revenue. Consequently, it is useful to consider the level of social inefficiency introduced when the design of a priority scheme is turned over to a revenue-maximizing firm. In this paper we study how the priority scheme chosen by a revenue-maximizing firm differs from the one a social planner would use. We study a single-server queue with customers who draw their valuations from a continuous distribution and have a per-period waiting cost that is proportional to their realized valuations. The decision maker must post a menu offering a finite number of waiting time-price pairs. There are then three dimensions on which a revenue maximizer and social planner can differ: coverage (i.e., how many customers in total to serve), coarseness (i.e., how many classes of service to offer), and classification (i.e., how to map customers to priority levels). We show that differences between the decision-makers’ priority policies are all about classification. Both are content to offer very coarse schemes with just two priority levels, and they will have negligible differences in coverage. However, differences in classification are persistent. Further, a revenue maximizer may—relative to the social planner—have too few or too many high-priority customers. Whether the revenue maximizer overstuffs or understuffs the high-priority class depends on a measure of consumer surplus that is captured by the mean residual life function of the valuation distribution.

Suggested Citation

  • Itai Gurvich & Martin A. Lariviere & Can Ozkan, 2019. "Coverage, Coarseness, and Classification: Determinants of Social Efficiency in Priority Queues," Management Science, INFORMS, vol. 65(3), pages 1061-1075, March.
  • Handle: RePEc:inm:ormnsc:v:65:y:2019:i:3:p:1061-1075
    DOI: 10.1287/mnsc.2017.2987
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    References listed on IDEAS

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    Cited by:

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    2. Zhongbin Wang & Shiliang Cui & Lei Fang, 2023. "Distance-Based Service Priority: An Innovative Mechanism to Increase System Throughput and Social Welfare," Manufacturing & Service Operations Management, INFORMS, vol. 25(1), pages 353-369, January.
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    8. Lun Yu & Seyed Iravani & Ohad Perry, 2022. "A Fluid-Diffusion-Hybrid Limiting Approximation for Priority Systems with Fast and Slow Customers," Operations Research, INFORMS, vol. 70(4), pages 2579-2596, July.
    9. Chamberlain, Jonathan & Simhon, Eran & Starobinski, David, 2021. "Preemptible queues with advance reservations: Strategic behavior and revenue management," European Journal of Operational Research, Elsevier, vol. 293(2), pages 561-578.
    10. Luyi Yang & Zhongbin Wang & Shiliang Cui, 2021. "A Model of Queue Scalping," Management Science, INFORMS, vol. 67(11), pages 6803-6821, November.
    11. Yiwei Chen & Cong Shi, 2019. "Joint Pricing and Inventory Management with Strategic Customers," Operations Research, INFORMS, vol. 67(6), pages 1610-1627, November.
    12. Kim, Jaehong & Li, Mengling & Xu, Menghan, 2025. "Priority search with outside options," Theoretical Economics, Econometric Society, vol. 20(3), July.
    13. Siddharth Prakash Singh & Owen Q. Wu, 2025. "Incorporating Income Disparity and Utility Heterogeneity in Resource Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 27(3), pages 757-769, May.
    14. Jian Liu & Yong‐Pin Zhou & Jian Chen, 2023. "Customer segmentation and ex ante fairness: A queueing perspective," Production and Operations Management, Production and Operations Management Society, vol. 32(10), pages 3246-3265, October.
    15. Luyi Yang, 2021. "Invite Your Friend and You’ll Move Up in Line: Optimal Design of Referral Priority Programs," Manufacturing & Service Operations Management, INFORMS, vol. 23(5), pages 1139-1156, September.
    16. Zhao, Chen & Wang, Zhongbin, 2023. "The impact of line-sitting on a two-server queueing system," European Journal of Operational Research, Elsevier, vol. 308(2), pages 782-800.
    17. Liu, Jian & Chen, Jian & Bo, Rui & Meng, Fanlin & Xu, Yong & Li, Peng, 2023. "Increases or discounts: Price strategies based on customers’ patience times," European Journal of Operational Research, Elsevier, vol. 305(2), pages 722-737.
    18. Ming Hu & Ruslan Momot & Jianfu Wang, 2022. "Privacy Management in Service Systems," Manufacturing & Service Operations Management, INFORMS, vol. 24(5), pages 2761-2779, September.
    19. Zhouzi Li & Mor Harchol-Balter & Alan Scheller-Wolf, 2026. "When does partial priority improve revenue?," Queueing Systems: Theory and Applications, Springer, vol. 110(1), pages 1-35, March.
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    21. Wang, Tianyu & Wu, Desheng & Yang, Jiaxian, 2026. "Efficiency with consent: Permutable queueing in on-demand services," Omega, Elsevier, vol. 138(C).

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