IDEAS home Printed from https://ideas.repec.org/a/spr/queues/v99y2021i3d10.1007_s11134-021-09720-z.html
   My bibliography  Save this article

Equilibrium analysis of observable express service with customer choice

Author

Listed:
  • Jiaqi Zhou

    (University of Maryland)

  • Ilya O. Ryzhov

    (University of Maryland)

Abstract

We study a stylized queueing model motivated by paid express lanes on highways. There are two parallel, observable first-come, first-served queues with finitely many servers: one queue has a faster service rate, but charges a fee to join, and the other is free but slow. Upon arrival, customers see the state of each queue and choose between them by comparing the respective disutility of time spent waiting, subject to random shocks. This framework encompasses both the multinomial logit and exponomial customer choice models. Using a fluid limit approximation, we give a detailed characterization of the equilibrium in this system. We show that social welfare is optimized when the express queue is exactly at (but not over) full capacity; however, in some cases, revenue is maximized by artificially creating congestion in the free queue. The latter behavior is caused by changes in the price elasticity of demand as the service capacity of the free queue fills up.

Suggested Citation

  • Jiaqi Zhou & Ilya O. Ryzhov, 2021. "Equilibrium analysis of observable express service with customer choice," Queueing Systems: Theory and Applications, Springer, vol. 99(3), pages 243-281, December.
    • Handle: RePEc:spr:queues:v:99:y:2021:i:3:d:10.1007_s11134-021-09720-z
    DOI: 10.1007/s11134-021-09720-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11134-021-09720-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11134-021-09720-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ping Cao & Yaolei Wang & Jingui Xie, 2019. "Priority Service Pricing with Heterogeneous Customers: Impact of Delay Cost Distribution," Production and Operations Management, Production and Operations Management Society, vol. 28(11), pages 2854-2876, November.
    2. Angelos Aveklouris & Maria Vlasiou & Bert Zwart, 2019. "Bounds and limit theorems for a layered queueing model in electric vehicle charging," Queueing Systems: Theory and Applications, Springer, vol. 93(1), pages 83-137, October.
    3. Rouba Ibrahim, 2018. "Managing Queueing Systems Where Capacity is Random and Customers are Impatient," Production and Operations Management, Production and Operations Management Society, vol. 27(2), pages 234-250, February.
    4. Naor, P, 1969. "The Regulation of Queue Size by Levying Tolls," Econometrica, Econometric Society, vol. 37(1), pages 15-24, January.
    5. Srinagesh Gavirneni & Vidyadhar G. Kulkarni, 2016. "Self-Selecting Priority Queues with Burr Distributed Waiting Costs," Production and Operations Management, Production and Operations Management Society, vol. 25(6), pages 979-992, June.
    6. Pengfei Guo & Zhe George Zhang, 2013. "Strategic Queueing Behavior and Its Impact on System Performance in Service Systems with the Congestion-Based Staffing Policy," Manufacturing & Service Operations Management, INFORMS, vol. 15(1), pages 118-131, September.
    7. Jinting Wang & Shiliang Cui & Zhongbin Wang, 2019. "Equilibrium Strategies in M/M/1 Priority Queues with Balking," Production and Operations Management, Production and Operations Management Society, vol. 28(1), pages 43-62, January.
    8. Philipp Afèche & Opher Baron & Joseph Milner & Ricky Roet-Green, 2019. "Pricing and Prioritizing Time-Sensitive Customers with Heterogeneous Demand Rates," Operations Research, INFORMS, vol. 67(4), pages 1184-1208, July.
    9. Refael Hassin & Ricky Roet-Green, 2017. "The Impact of Inspection Cost on Equilibrium, Revenue, and Social Welfare in a Single-Server Queue," Operations Research, INFORMS, vol. 65(3), pages 804-820, June.
    10. Mor Armony & Constantinos Maglaras, 2004. "On Customer Contact Centers with a Call-Back Option: Customer Decisions, Routing Rules, and System Design," Operations Research, INFORMS, vol. 52(2), pages 271-292, April.
    11. Philipp Afèche & J. Michael Pavlin, 2016. "Optimal Price/Lead-Time Menus for Queues with Customer Choice: Segmentation, Pooling, and Strategic Delay," Management Science, INFORMS, vol. 62(8), pages 2412-2436, August.
    12. Jamol Pender & Richard Rand & Elizabeth Wesson, 2020. "A Stochastic Analysis of Queues with Customer Choice and Delayed Information," Mathematics of Operations Research, INFORMS, vol. 45(3), pages 1104-1126, August.
    13. Luyi Yang & Laurens G. Debo & Varun Gupta, 2019. "Search Among Queues Under Quality Differentiation," Management Science, INFORMS, vol. 65(8), pages 3605-3623, August.
    14. Constantinos Maglaras, 2006. "Revenue Management for a Multiclass Single-Server Queue via a Fluid Model Analysis," Operations Research, INFORMS, vol. 54(5), pages 914-932, October.
    15. Aydın Alptekinoğlu & John H. Semple, 2016. "The Exponomial Choice Model: A New Alternative for Assortment and Price Optimization," Operations Research, INFORMS, vol. 64(1), pages 79-93, February.
    16. Omar Besbes & Costis Maglaras, 2009. "Revenue Optimization for a Make-to-Order Queue in an Uncertain Market Environment," Operations Research, INFORMS, vol. 57(6), pages 1438-1450, December.
    17. Shiliang Cui & Zhongbin Wang & Luyi Yang, 2020. "The Economics of Line-Sitting," Management Science, INFORMS, vol. 66(1), pages 227-242, January.
    18. Kurtz, Thomas G., 1978. "Strong approximation theorems for density dependent Markov chains," Stochastic Processes and their Applications, Elsevier, vol. 6(3), pages 223-240, February.
    19. Terry A. Taylor, 2018. "On-Demand Service Platforms," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 704-720, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Opher Baron & Xiaole Chen & Yang Li, 2023. "Omnichannel Services: The False Premise and Operational Remedies," Management Science, INFORMS, vol. 69(2), pages 865-884, February.
    4. Pei, Zhi & Dai, Xu & Yuan, Yilun & Du, Rui & Liu, Changchun, 2021. "Managing price and fleet size for courier service with shared drones," Omega, Elsevier, vol. 104(C).
    5. Zhongbin Wang & Yunan Liu & Lei Fang, 2022. "Pay to activate service in vacation queues," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2609-2627, June.
    6. Mustafa Akan & Barı ş Ata & Tava Olsen, 2012. "Congestion-Based Lead-Time Quotation for Heterogenous Customers with Convex-Concave Delay Costs: Optimality of a Cost-Balancing Policy Based on Convex Hull Functions," Operations Research, INFORMS, vol. 60(6), pages 1505-1519, December.
    7. Hossein Abouee‐Mehrizi & Ata Ghareaghaji Zare & Renata A. Konrad, 2022. "Pricing in Service Systems with Rational Balking and Abandonment of Time‐Sensitive Customers," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 495-510, February.
    8. Benjamin Legros, 2021. "Agents’ Self‐Routing for Blended Operations to Balance Inbound and Outbound Services," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3599-3614, October.
    9. Hanukov, Gabi & Avinadav, Tal & Chernonog, Tatyana & Yechiali, Uri, 2020. "A service system with perishable products where customers are either fastidious or strategic," International Journal of Production Economics, Elsevier, vol. 228(C).
    10. Zhongbin Wang & Luyi Yang & Shiliang Cui & Jinting Wang, 2021. "In-queue priority purchase: a dynamic game approach," Queueing Systems: Theory and Applications, Springer, vol. 97(3), pages 343-381, April.
    11. 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.
    12. De Munck, Thomas & Chevalier, Philippe & Tancrez, Jean-Sébastien, 2023. "Managing priorities on on-demand service platforms with waiting time differentiation," International Journal of Production Economics, Elsevier, vol. 266(C).
    13. Manlu Chen & Ming Hu & Jianfu Wang, 2022. "Food Delivery Service and Restaurant: Friend or Foe?," Management Science, INFORMS, vol. 68(9), pages 6539-6551, September.
    14. Zhang, Zhe George & Yin, Xiaoling, 2021. "Information and pricing effects in two-tier public service systems," International Journal of Production Economics, Elsevier, vol. 231(C).
    15. İşlier, Zeynep Gökçe & Güllü, Refik, 2024. "On strategic customers with correlated utility attributes: Effects and information benefits," European Journal of Operational Research, Elsevier, vol. 313(1), pages 258-269.
    16. Luyi Yang & Shiliang Cui & Zhongbin Wang, 2022. "Design of Covid‐19 testing queues," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2204-2221, May.
    17. Shiliang Cui & Xuanming Su & Senthil Veeraraghavan, 2019. "A Model of Rational Retrials in Queues," Operations Research, INFORMS, vol. 67(6), pages 1699-1718, November.
    18. Vibhanshu Abhishek & Mustafa Dogan & Alexandre Jacquillat, 2021. "Strategic Timing and Dynamic Pricing for Online Resource Allocation," Management Science, INFORMS, vol. 67(8), pages 4880-4907, August.
    19. Terry A. Taylor, 2018. "On-Demand Service Platforms," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 704-720, October.
    20. Chai, Xudong & Jiang, Tao & Chang, Baoxian & Liu, Liwei, 2021. "On a multiple priorities matching system with heterogeneous delay sensitive individuals," Applied Mathematics and Computation, Elsevier, vol. 395(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:queues:v:99:y:2021:i:3:d:10.1007_s11134-021-09720-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.