IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v50y2016i1p288-305.html
   My bibliography  Save this article

Hidden-City Ticketing: The Cause and Impact

Author

Listed:
  • Zizhuo Wang

    (Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455)

  • Yinyu Ye

    (Department of Management Science and Engineering, Stanford University, Stanford, California 94305)

Abstract

Hidden-city ticketing is an interesting airline ticket-pricing phenomenon. It occurs when an itinerary connecting at an intermediate city is less expensive than a ticket from the origin to the intermediate city. In such a case, passengers traveling to the intermediate city have an incentive to pretend to be traveling to the final destination, deplane at the connection point, and forgo the unused portion of the ticket. Hidden-city opportunities are not uncommon nowadays.In this paper, we establish a mathematical model to shed some light on the cause of hidden-city opportunities and the impact of (the passengers’) hidden-city ticketing practice on both the airlines’ revenues and consumer welfare. To perform our study, we adapt a network revenue management model. We illustrate that the hidden-city opportunity may arise when there is a large difference in the price elasticity of demand on related itineraries, providing a plausible explanation for this phenomenon. To show the impact of the hidden-city ticketing practice on the airlines’ revenues, we first argue that when passengers take advantage of such opportunities, the airlines should react, and the optimal reaction would be to eliminate any hidden-city opportunities. However, even if the airline optimally reacts, the revenue gained is still less than the optimal revenue it could have earned if passengers did not take advantage of hidden-city opportunities. Moreover, under our model, the revenue decrease could be as much as half of the optimal revenue when passengers do not use hidden-city tickets, but it cannot be more if the airline’s network has a hub-and-spoke structure. We also show that when passengers take advantage of hidden-city opportunities, the prices of certain itineraries will rise, which is a disadvantage to the passengers in the long run.

Suggested Citation

  • Zizhuo Wang & Yinyu Ye, 2016. "Hidden-City Ticketing: The Cause and Impact," Transportation Science, INFORMS, vol. 50(1), pages 288-305, February.
  • Handle: RePEc:inm:ortrsc:v:50:y:2016:i:1:p:288-305
    DOI: 10.1287/trsc.2015.0587
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.2015.0587
    Download Restriction: no

    File URL: https://libkey.io/10.1287/trsc.2015.0587?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
    ---><---

    References listed on IDEAS

    as
    1. William L. Cooper, 2002. "Asymptotic Behavior of an Allocation Policy for Revenue Management," Operations Research, INFORMS, vol. 50(4), pages 720-727, August.
    2. Daniel Adelman, 2007. "Dynamic Bid Prices in Revenue Management," Operations Research, INFORMS, vol. 55(4), pages 647-661, August.
    3. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    4. Severin Borenstein & Nancy L. Rose, 2014. "How Airline Markets Work…or Do They? Regulatory Reform in the Airline Industry," NBER Chapters, in: Economic Regulation and Its Reform: What Have We Learned?, pages 63-135, National Bureau of Economic Research, Inc.
    5. Nancy L. Rose, 2014. "Economic Regulation and Its Reform: What Have We Learned?," NBER Books, National Bureau of Economic Research, Inc, number rose05-1, March.
    6. Guillermo Gallego & Garrett van Ryzin, 1997. "A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management," Operations Research, INFORMS, vol. 45(1), pages 24-41, February.
    7. Evans, William N & Kessides, Ioannis N, 1993. "Localized Market Power in the U.S. Airline Industry," The Review of Economics and Statistics, MIT Press, vol. 75(1), pages 66-75, February.
    8. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    9. Qian Liu & Garrett van Ryzin, 2008. "On the Choice-Based Linear Programming Model for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 288-310, October.
    10. Dan Zhang & Daniel Adelman, 2009. "An Approximate Dynamic Programming Approach to Network Revenue Management with Customer Choice," Transportation Science, INFORMS, vol. 43(3), pages 381-394, August.
    11. Dan Zhang, 2011. "An Improved Dynamic Programming Decomposition Approach for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 35-52, April.
    12. William James Adams & Janet L. Yellen, 1976. "Commodity Bundling and the Burden of Monopoly," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 90(3), pages 475-498.
    13. R. Venkatesh & Wagner Kamakura, 2003. "Optimal Bundling and Pricing under a Monopoly: Contrasting Complements and Substitutes from Independently Valued Products," The Journal of Business, University of Chicago Press, vol. 76(2), pages 211-232, April.
    14. Yannis Bakos & Erik Brynjolfsson, 2000. "Bundling and Competition on the Internet," Marketing Science, INFORMS, vol. 19(1), pages 63-82, May.
    15. Brueckner, Jan K & Spiller, Pablo T, 1994. "Economies of Traffic Density in the Deregulated Airline Industry," Journal of Law and Economics, University of Chicago Press, vol. 37(2), pages 379-415, October.
    16. Severin Borenstein, 1991. "The Dominant-Firm Advantage in Multiproduct Industries: Evidence from the U. S. Airlines," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1237-1266.
    17. R. Preston McAfee & John McMillan & Michael D. Whinston, 1989. "Multiproduct Monopoly, Commodity Bundling, and Correlation of Values," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 104(2), pages 371-383.
    18. Severin Borenstein, 1989. "Hubs and High Fares: Dominance and Market Power in the U.S. Airline Industry," RAND Journal of Economics, The RAND Corporation, vol. 20(3), pages 344-365, Autumn.
    19. Kalyan Talluri & Garrett van Ryzin, 1999. "A Randomized Linear Programming Method for Computing Network Bid Prices," Transportation Science, INFORMS, vol. 33(2), pages 207-216, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gaggero, Alberto A. & Luttmann, Alexander, 2023. "The determinants of hidden-city ticketing: Competition, hub-and-spoke networks, and advance-purchase requirements," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    2. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2023. "Price discrimination through hidden city options? A data-driven study on the extent and evolution of skiplaggability in the global aviation system," Journal of Air Transport Management, Elsevier, vol. 108(C).

    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. Dan Zhang & Larry Weatherford, 2017. "Dynamic Pricing for Network Revenue Management: A New Approach and Application in the Hotel Industry," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 18-35, February.
    2. Yuhang Ma & Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "An Approximation Algorithm for Network Revenue Management Under Nonstationary Arrivals," Operations Research, INFORMS, vol. 68(3), pages 834-855, May.
    3. Dan Zhang & Zhaosong Lu, 2013. "Assessing the Value of Dynamic Pricing in Network Revenue Management," INFORMS Journal on Computing, INFORMS, vol. 25(1), pages 102-115, February.
    4. Thomas W. M. Vossen & Dan Zhang, 2015. "Reductions of Approximate Linear Programs for Network Revenue Management," Operations Research, INFORMS, vol. 63(6), pages 1352-1371, December.
    5. Chan Seng Pun & Diego Klabjan & Fikri Karaesmen & Sergey Shebalov, 2016. "Itinerary-based nesting control with upsell," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(2), pages 107-137, April.
    6. Jing-Sheng Song & Zhengliang Xue, 2021. "Demand Shaping Through Bundling and Product Configuration: A Dynamic Multiproduct Inventory-Pricing Model," Operations Research, INFORMS, vol. 69(2), pages 525-544, March.
    7. Dan Zhang, 2011. "An Improved Dynamic Programming Decomposition Approach for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 35-52, April.
    8. Wuyang Yuan & Lei Nie & Xin Wu & Huiling Fu, 2018. "A dynamic bid price approach for the seat inventory control problem in railway networks with consideration of passenger transfer," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-23, August.
    9. Nicolas Houy & François Le Grand, 2015. "The Monte Carlo first-come-first-served heuristic for network revenue management," Working Papers halshs-01155698, HAL.
    10. Mika Sumida & Huseyin Topaloglu, 2019. "An Approximation Algorithm for Capacity Allocation Over a Single Flight Leg with Fare-Locking," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 83-99, February.
    11. Meissner, Joern & Strauss, Arne, 2012. "Improved bid prices for choice-based network revenue management," European Journal of Operational Research, Elsevier, vol. 217(2), pages 417-427.
    12. Sebastian Koch & Jochen Gönsch & Claudius Steinhardt, 2017. "Dynamic Programming Decomposition for Choice-Based Revenue Management with Flexible Products," Transportation Science, INFORMS, vol. 51(4), pages 1046-1062, November.
    13. Silke J. Forbes & Renáta Kosová, 2023. "Does Competition Benefit Complements? Evidence from Airlines and Hotels," Management Science, INFORMS, vol. 69(8), pages 4733-4752, August.
    14. Strauss, Arne K. & Klein, Robert & Steinhardt, Claudius, 2018. "A review of choice-based revenue management: Theory and methods," European Journal of Operational Research, Elsevier, vol. 271(2), pages 375-387.
    15. William L. Cooper & Tito Homem-de-Mello, 2007. "Some Decomposition Methods for Revenue Management," Transportation Science, INFORMS, vol. 41(3), pages 332-353, August.
    16. Sumit Kunnumkal & Huseyin Topaloglu, 2010. "Computing Time-Dependent Bid Prices in Network Revenue Management Problems," Transportation Science, INFORMS, vol. 44(1), pages 38-62, February.
    17. Nicolas Houy & François Le Grand, 2015. "Financing and advising with (over)confident entrepreneurs : an experimental investigation," Working Papers 1514, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    18. Meissner, Joern & Strauss, Arne, 2012. "Network revenue management with inventory-sensitive bid prices and customer choice," European Journal of Operational Research, Elsevier, vol. 216(2), pages 459-468.
    19. Alexander Erdelyi & Huseyin Topaloglu, 2010. "A Dynamic Programming Decomposition Method for Making Overbooking Decisions Over an Airline Network," INFORMS Journal on Computing, INFORMS, vol. 22(3), pages 443-456, August.
    20. Gayle, Philip G. & Wu, Chi-Yin, 2013. "A re-examination of incumbents’ response to the threat of entry: Evidence from the airline industry," Economics of Transportation, Elsevier, vol. 2(4), pages 119-130.

    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:inm:ortrsc:v:50:y:2016:i:1:p:288-305. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.