Dynamic pricing of airline offers

Practice Article
  • 10 Downloads

Abstract

Airlines have started to focus on expanding their product offerings beyond flights to include ancillary products (e.g., baggage, advance seat reservations, meals, flexibility options), as well as third-party content (e.g., parking and insurance). Today, however, offer creation is rudimentary, managed in separate processes, organizations, and IT systems. We believe the current approach is inadequate and that the key to profitability is to manage offers consistently in an integrated Offer Management System (OMS). However, realizing this vision, will require significant advancements in the science of pricing and in distribution. The entire scope of an OMS cannot be covered in a single paper. Hence, to provide depth, we will focus on what we believe is one of the most critical components of the OMS—Dynamic Pricing of airline offers. Finally, we discuss various industry initiatives that will enable deployment of Dynamic Pricing of the flight product alone or the broader scope of OMS.

Keywords

Revenue Management System Offer Management System Dynamic Pricing Ancillary Price Optimization Machine Learning Distribution NDC 

Notes

Acknowledgements

We thank Jason Coverston, at Navitaire, for sharing his insights on Navitaire’s Ancillary Price Optimization (APO). We also thank Stephane Lecourtois for sharing his knowledge on merchandising.

References

  1. Adams, W.J., and J.L. Yellen. 1976. Commodity Bundling and the Burden of Monopoly. Quarterly Journal of Economics 90 (3): 475–498.CrossRefGoogle Scholar
  2. Aggarwal, C.C. 2016. An Introduction to Recommender Systems. New York: Springer.CrossRefGoogle Scholar
  3. Belobaba, P.P. 1989. Application of a Probabilistic Decision Model to Airline Seat Inventory Control. Operations Research 37: 183–197.CrossRefGoogle Scholar
  4. Bockelie, A. 2017. Revenue Management with Ancillary Services: A New Optimization Approach. Presented at AGIFORS Reservation and Distribution Study Group, Frankfurt, Germany.Google Scholar
  5. Coverston, J. 2016. Ancillary Pricing Optimization (APO), Navitaire Customer Conference, Las Vegas.Google Scholar
  6. Hoyles, Y. 2015. IATA Simplifying the Business. New Distribution Capability (NDC). Facilitating Air Retailing. http://www.iata.org/whatwedo/airline-distribution/ndc/Documents/ndc-strategy-paper.pdf. Accessed 15 Oct 2017.
  7. Fiig, T. 2007. ODYSSEY: SAS’ O&D Forecasting System. Presented at AGIFORS Reservation and Yield Management Study Group, Jeju Island, Korea.Google Scholar
  8. Fiig, T., K. Isler, C. Hopperstad, and P. Belobaba. 2010. Optimization of Mixed Fare Structures: Theory and Applications. Journal of Revenue and Pricing Management 9 (1/2): 152–170.CrossRefGoogle Scholar
  9. Fiig, T., K. Isler, C. Hopperstad, and S. Olsen. 2011. Forecasting and Optimization of Fare Families. Journal of Revenue and Pricing Management 11 (3): 322–342.CrossRefGoogle Scholar
  10. Fiig, T., B. Smith, G. Goyons, and R. Adelving. 2015. Dynamic Pricing—the Next Revolution in RM? Journal of Revenue and Pricing Management 15 (5): 360–379.CrossRefGoogle Scholar
  11. Fiig, T., R. Härdling, S. Pölt, and C. Hopperstad. 2014. Demand Forecasting and Measuring Forecast Accuracy in General Fare Structures. Management 13 (6): 413–439.Google Scholar
  12. Garrow, L. 2010. Discrete Choice Modeling and Air Travel Demand: Theory and Applications. Farnham: Ashgate Publishing.Google Scholar
  13. Gorin, T. 2012. Forecasting Passenger Demand at the “Right” Level. Optimal Dimension Definitions and Clusters for Forecasting Demand. Presented at AGIFORS Reservation and Distribution Study Group, Barcelona, Spain.Google Scholar
  14. IATA. 2013. Profitability and the Air Transport Value Chain. IATA Economics Briefing No. 10, IATA.Google Scholar
  15. IATA. 2016. New Distribution Capability (NDC) Implementation Guide 3.2. http://www.iata.org/whatwedo/airline-distribution/ndc/Documents/ndc-implementation-guide.pdf. Accessed 3 Mar 2018.
  16. Jannach, D., M. Zanker, A. Felfernig, et al. 2010. Recommender Systems: An Introduction (Chapter 10). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  17. Kahneman, D., and F.A. Tversky. 1979. Prospect Theory: An Analysis of Decision Under risk. Econometrica 47 (2): 263–292.CrossRefGoogle Scholar
  18. Lautenbacher, C.J., and S.J. Stidham. 1999. The Underlying Markov Decision Process in the Single-Leg Airline Yield Management Problem. Transportation Science 33: 136–146.CrossRefGoogle Scholar
  19. Lee, T.C., and M. Hirsch. 1993. A Model for Dynamic Airline Seat Inventory Control with Multiple Seat Bookings. Transportation Science 27: 252–265.CrossRefGoogle Scholar
  20. Linden, B., J. Smith, and J. York. 2003. Amazon.com Recommendations: Item-to-Item Collaborative Filtering. IEEE Internet Computing 7 (1): 76–80.CrossRefGoogle Scholar
  21. Littlewood, K. 1972. Forecasting and Control of Passenger Bookings. 12th AGIFORS Annual Symposium Proceedings, Nathanya, Israel, pp. 95–117.Google Scholar
  22. Popp, C. 2016. RM Meets Distribution. Presented at AGIFORS Reservation and Distribution Study Group, San Francisco, CAGoogle Scholar
  23. Radcliffe, N.J. 2007. Using Control Groups to Target on Predicted Lift: Building and Assessing Uplift Model. Direct Marketing Analytics Journal 1: 14–21.Google Scholar
  24. Ratliff, R. 2017. Industry-standard Specifications for Air Dynamic Pricing Engines: Progress Update. Presented at AGIFORS Revenue Management Study Group Meeting, San Francisco, USA.Google Scholar
  25. Rauch, J. Pölt, S., Isler, K. 2015. Disentangling Capacity Control from Price Optimization. Presented at AGIFORS Reservation and Distribution Study Group, Shanghai, ChinaGoogle Scholar
  26. Rauch, J., K. Isler, and S. Poelt. 2017. Disentangling Capacity Control from Price Optimization. Journal of Revenue and Pricing Management.  https://doi.org/10.1057/s41272-017-0118-9.
  27. Reinartz, W. 2002. Customizing Prices in Online Markets. Symphonya Emerging Issues in Management 1: 55–65.Google Scholar
  28. Sahin, O. Hagen, J., Jadanza, R., and Fiig T. forthcoming. Dynamically Pricing Ticket Options: An Artificial Intelligence Approach.Google Scholar
  29. Smith, B.C., and C.W. Penn. 1988. Analysis of Alternative Origin-Destination Control Strategies. AGIFORS Symposium Proceedings 28: 123–144.Google Scholar
  30. Smith, B., R. Darrow, J. Elieson, D. Guenther, V. Rao, and F. Zouaoui. 2007. Travelocity Becomes a Travel Retailer. Interfaces 37 (1): 68–81.CrossRefGoogle Scholar
  31. Weber, K. 2001. From O&D Bid Price Control to Package Bid Price Control. Presented at AGIFORS Reservation and Yield Management Study Group, Bangkok, Thailand.Google Scholar
  32. Williamson, E.L. 1992. Airline Network Seat Inventory Control: Methodologies and Revenue Impacts. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA.Google Scholar
  33. Wilson, B. and Touraine, S. (2016). NDC—ONE Order initiatives: Industry opportunities for simplification and value creation. Presented at AGIFORS Reservation and Distribution Study Group, Frankfurt, Germany.Google Scholar

Copyright information

© Macmillan Publishers Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Amadeus Airline ITKastrupDenmark
  2. 2.Amadeus Airline IT, Amadeus S.A.S.Sophia Antipolis CedexFrance

Personalised recommendations