IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v18y2019i6d10.1057_s41272-019-00205-6.html
   My bibliography  Save this article

A cabin capacity allocation model for revenue management in the cruise industry

Author

Listed:
  • Daniel Sturm

    (Hamburg University of Technology)

  • Kathrin Fischer

    (Hamburg University of Technology)

Abstract

The cruise industry is a profitable field for the application of revenue management methods. Existing model formulations for booking limit determination usually assume that the different elements of booking requests are independent. In this work, it is shown that this approach can lead to non-feasible capacity allocations, which consequently are neither optimal nor applicable in practical planning situations. Therefore, a new improved integer linear model formulation is developed here which by explicitly assigning booking requests to cabins derives a feasible and revenue-maximizing capacity allocation. The model and its results are illustrated with a real-world sized case study.

Suggested Citation

  • Daniel Sturm & Kathrin Fischer, 2019. "A cabin capacity allocation model for revenue management in the cruise industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(6), pages 441-450, December.
  • Handle: RePEc:pal:jorapm:v:18:y:2019:i:6:d:10.1057_s41272-019-00205-6
    DOI: 10.1057/s41272-019-00205-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-019-00205-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1057/s41272-019-00205-6?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. Josep Mª Espinet Rius, 2018. "Global and local pricing strategies in the cruise industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(5), pages 329-340, October.
    2. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    3. Maddah, Bacel & Moussawi-Haidar, Lama & El-Taha, Muhammad & Rida, Hussein, 2010. "Dynamic cruise ship revenue management," European Journal of Operational Research, Elsevier, vol. 207(1), pages 445-455, November.
    4. Ladany, Shaul P. & Arbel, Avner, 1991. "Optimal cruise-liner passenger cabin pricing policy," European Journal of Operational Research, Elsevier, vol. 55(2), pages 136-147, November.
    5. Richard Metters & Carrie Queenan & Mark Ferguson & Laura Harrison & Jon Higbie & Stan Ward & Bruce Barfield & Tammy Farley & H. Ahmet Kuyumcu & Amar Duggasani, 2008. "The “Killer Application” of Revenue Management: Harrah's Cherokee Casino & Hotel," Interfaces, INFORMS, vol. 38(3), pages 161-175, June.
    6. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
    7. Donghui Ma & Jin Sun, 2012. "Revenue Management System for the Cruise Industry: A Simulation Study," Springer Books, in: Alexis Papathanassis & Michael H. Breitner & Cornelia Schoen & Nadine Guhr (ed.), Cruise Management, chapter 11, pages 223-232, Springer.
    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. Mahmoud Dehghan Nayeri & Amir-Nader Haghbin & Abdolkarim Mohammadi-Balani & Karim Bayat, 2020. "A multi-objective mean–variance mathematical programming approach to combined phase-out and clearance pricing strategy for seasonal products: case study of a Jeans retailer," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(3), pages 210-217, June.

    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. Oleg Shcherbina & Elena Shembeleva, 2014. "Modeling recreational systems using optimization techniques and information technologies," Annals of Operations Research, Springer, vol. 221(1), pages 309-329, October.
    2. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    3. 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.
    4. Ma, Jie & Tse, Ying Kei & Wang, Xiaojun & Zhang, Minhao, 2019. "Examining customer perception and behaviour through social media research – An empirical study of the United Airlines overbooking crisis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 192-205.
    5. Hu, Qiying & Wei, Yihua & Xia, Yusen, 2010. "Revenue management for a supply chain with two streams of customers," European Journal of Operational Research, Elsevier, vol. 200(2), pages 582-598, January.
    6. Irene Ng & Nick K.T. Yip, 2009. "Mechanism design in an integrated approach towards revenue management: the case of Empress Cruise Lines," The Service Industries Journal, Taylor & Francis Journals, vol. 31(3), pages 469-482, February.
    7. Josep Mª Espinet Rius, 2018. "Global and local pricing strategies in the cruise industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(5), pages 329-340, October.
    8. Valerio Lacagnina & Davide Provenzano, 2016. "An integrated fuzzy-stochastic model for revenue management," Tourism Economics, , vol. 22(4), pages 779-792, 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. Huang, Kuancheng & Lin, Chia-Yi, 2014. "A simulation analysis for the re-solving issue of the network revenue management problem," Journal of Air Transport Management, Elsevier, vol. 38(C), pages 36-42.
    11. Owusu Boahen & Emmanuel Kweku Quansah & Owusu Kwame Sarpong, 2013. "Assessing the Benefits of Yield Management in the Hospitality Industry in Kumasi Metropolis of Ghana," International Journal of Business and Social Research, LAR Center Press, vol. 3(9), pages 17-25, September.
    12. Zhe Yuan & Haoxuan Xu & Yeming (Yale) Gong & Chengbin Chu & Jinlong Zhang, 2017. "Designing public storage warehouses with high demand for revenue maximisation," International Journal of Production Research, Taylor & Francis Journals, vol. 55(13), pages 3686-3700, July.
    13. Hans Buhl & Robert Klein & Johannes Kolb & Andrea Landherr, 2011. "CR 2 M—an approach for capacity control considering long-term effects on the value of a customer for the company," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 22(2), pages 187-204, December.
    14. Lin, Kyle Y., 2006. "Dynamic pricing with real-time demand learning," European Journal of Operational Research, Elsevier, vol. 174(1), pages 522-538, October.
    15. Shuyu Zhou & Yeming (Yale) Gong & René de Koster, 2016. "Designing self-storage warehouses with customer choice," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3080-3104, May.
    16. Lin, Kyle Y. & Sibdari, Soheil Y., 2009. "Dynamic price competition with discrete customer choices," European Journal of Operational Research, Elsevier, vol. 197(3), pages 969-980, September.
    17. Owusu Boahen & Emmanuel Kweku Quansah & Owusu Kwame Sarpong, 2013. "Assessing the Benefits of Yield Management in the Hospitality Industry in Kumasi Metropolis of Ghana," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 3(9), pages 17-25, July.
    18. Milad HajMirzaei & Koorush Ziarati & Alireza Nikseresht, 2022. "A customer type discovery algorithm in hotel revenue management systems," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 200-211, April.
    19. 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.
    20. 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.

    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:pal:jorapm:v:18:y:2019:i:6:d:10.1057_s41272-019-00205-6. 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.palgrave.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.