Journal of Revenue and Pricing Management

, Volume 18, Issue 6, pp 441–450 | Cite as

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

  • Daniel SturmEmail author
  • Kathrin Fischer
Research Article


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.


Revenue management Capacity allocation Cruise industry Simulation 



  1. Ayvaz-Cavdaroglu, N., D.K. Gauri, and S. Webster. 2019. Empirical evidence of revenue management in the cruise line industry. Journal of Travel Research 58 (1): 104–120.CrossRefGoogle Scholar
  2. Aziz, H.A., N. El Gayar, M. Saleh, and H. El Shishiny. 2008. A randomized model for group reservations in a hotel’s revenue management system. In Proceedings of the 6th International Conference on Informatics and Systems (IFOS 2008). Cairo.Google Scholar
  3. Biehn, N. 2006. A cruise ship is not a floating hotel. Journal of Revenue and Pricing Management 5 (2): 135–142.CrossRefGoogle Scholar
  4. Chiang, W.-C., J.C.H. Chen, and X. Xu. 2007. An overview of research on revenue management: Current issues and future research. International Journal of Revenue Management 1 (1): 97–128.CrossRefGoogle Scholar
  5. Cruise Market Watch. 2019a. Growth of the ocean cruise line industry. Accessed 6 Aug 2019.
  6. Cruise Market Watch. 2019b. 2018 worldwide cruise line market share. Accessed 6 Aug 2019.
  7. Espinet Rius, J.M. 2018. Global and local pricing strategies in the cruise industry. Journal of Revenue and Pricing Management 17 (5): 329–340.CrossRefGoogle Scholar
  8. Frank, M., M. Friedemann, and A. Schröder. 2008. Principles for simulations in revenue management. Journal of Revenue and Pricing Management 7 (1): 7–16.CrossRefGoogle Scholar
  9. Goldman, P., R. Freling, K. Pak, and N. Piersma. 2002. Models and techniques for hotel revenue management using a rolling horizon. Journal of Revenue and Pricing Management 1 (3): 207–219.CrossRefGoogle Scholar
  10. Harewood, S.I. 2006. Managing a hotel’s perishable inventory using bid prices. International Journal of Operations & Production Management 26 (10): 1108–1122.CrossRefGoogle Scholar
  11. Ji, L., and J. Mazzarella. 2007. Application of modified nested and dynamic class allocation models for cruise line revenue management. Journal of Revenue and Pricing Management 6 (1): 19–32.CrossRefGoogle Scholar
  12. Kimes, S.E. 1989. Yield management: A tool for capacity-constrained service firms. Journal of Operations Management 8 (4): 348–363.CrossRefGoogle Scholar
  13. Ladany, S.P., and A. Arbel. 1991. Optimal cruise-liner passenger cabin pricing policy. European Journal of Operational Research 55 (2): 136–147.CrossRefGoogle Scholar
  14. Li, B. 2010. Modelling for cruise two-dimensional online revenue management system. International Journal of Digital Content Technology and Its Applications 4 (6): 72–78.CrossRefGoogle Scholar
  15. Li, B. 2014. A cruise line dynamic overbooking model with multiple cabin types from the view of real options. Cornell Hospitality Quarterly 55 (2): 197–209.CrossRefGoogle Scholar
  16. Li, Y., Q. Miao, and B.X. Wang. 2014. Modeling a cruise line revenue management problem. Journal of Revenue and Pricing Management 13 (3): 247–260.CrossRefGoogle Scholar
  17. Lieberman, W.H., and T. Dieck. 2002. Expanding the revenue management frontier: Optimal air planning in the cruise industry. Journal of Revenue and Pricing Management 1 (1): 7–18.CrossRefGoogle Scholar
  18. Ma, D., and J. Sun. 2012. Revenue management system for the cruise industry: A simulation study. In Cruise management: Information and decision support systems, ed. A. Papathanassis, M.H. Breitner, C. Schoen, and N. Guhr, 223–232. Wiesbaden: Gabler.CrossRefGoogle Scholar
  19. Maddah, B., L. Moussawi-Haidar, M. El-Taha, and H. Rida. 2010. Dynamic cruise ship revenue management. European Journal of Operational Research 207 (1): 445–455.CrossRefGoogle Scholar
  20. McGill, J., and G.J. van Ryzin. 1999. Revenue management: Research overview and prospects. Transportation Science 33 (2): 233–256.CrossRefGoogle Scholar
  21. Metters, R., C. Queenan, M. Ferguson, L. Harrison, J. Higbie, S. Ward, B. Barfield, T. Farley, H.A. Kuyumcu, and A. Duggasani. 2008. The “killer application” of revenue management: Harrah’s Cherokee Casino & Hotel. Interfaces 38 (3): 161–175.CrossRefGoogle Scholar
  22. Sturm, D. and K. Fischer. 2016. Cruise line revenue management: Overview and research opportunities. In Operations research proceedings 2016: Selected papers of the annual international conference of the German Operations Research society (GOR), ed. Fink, A., A. Fügenschuh and M.J. Geiger, 441–447, August 30–September 2, Helmut Schmidt University Hamburg, Germany, 2016. Cham: Springer.Google Scholar
  23. Sun, X., D.K. Gauri, and S. Webster. 2011. Forecasting for cruise line revenue management. Journal of Revenue and Pricing Management 10 (4): 306–324.CrossRefGoogle Scholar
  24. Talluri, K.T., and G.J. van Ryzin. 2004. The theory and practice of revenue management. New York: Springer.CrossRefGoogle Scholar
  25. Toh, R.S., M.J. Rivers, and T.W. Ling. 2005. Room occupancies: Cruise lines out-do the hotels. International Journal of Hospitality Management 24 (1): 121–135.CrossRefGoogle Scholar
  26. Vahdat, M.A., S. Golestany, M.H. Abouei, and M. Honarvar. 2014. A stochastic approach to hotel revenue management considering individual and group customers. In Proceedings of the 2014 international conference on industrial engineering and operations management. Bali.Google Scholar
  27. Vinod, B. 2004. Unlocking the value of revenue management in the hotel industry. Journal of Revenue and Pricing Management 3 (2): 178–190.CrossRefGoogle Scholar
  28. Zurheide, S., and K. Fischer. 2015. Revenue management methods for the liner shipping industry. Flexible Services and Manufacturing Journal 27 (2): 200–223.CrossRefGoogle Scholar

Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  1. 1.Institute for Operations Research and Information SystemsHamburg University of TechnologyHamburgGermany

Personalised recommendations