Dynamic pricing – The next revolution in RM?


Existing revenue management systems (RMS) base their recommendations on historic observations and do not explicitly consider competition. This means that RMS recommendations often are not appropriate for real-time competitive situations. Dynamic pricing (DP) is an extension of RMS that dynamically calculates the optimal price, taking into account the airline’s strategy, customer-specific information and real-time alternative offerings. By optimizing the contribution within the shopping session, DP has a more current and detailed view of demand and can improve RMS performance. We investigated the performance of DP using two simulators, Altéa Benchmarking Engine and Passenger Origin Destination Simulator and demonstrate that DP can deliver substantial revenue benefits with no modification to existing revenue management (RM) processes. However, the deployment of DP into the airline distribution process will be a challenge, because it affects all shopping and downstream processes, such as ticketing, servicing, revenue accounting, RM and interline settlement, that rely on information from existing fare aggregators. Nevertheless, the potential benefits of DP are so compelling that we believe the effort to bring this technology into practice is warranted.

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    RMS averaged view: ; . Insert into : . .

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    The PODS simulator was originally developed at the Boeing Company in the mid-1990s by Craig Hopperstad. It is currently owned by PODS Research LLC. Its research efforts have been directed, and its results validated, over the last 20 years by the airline members of the MIT/PODS Consortium.


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The authors would like to thank Valerie Viale, senior manager product marketing at Amadeus and who is responsible for the DP product, for her constructive feedback. In addition the authors are also indebted to our anonymous referees for their time and exceptional valuable comments.

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Correspondence to Thomas Fiig.

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1is director, chief scientist at Amadeus, where he is responsible for revenue management strategy and scientific methodologies. He holds a PhD in Theoretical Physics and Mathematics and a BA in Finance from the University of Copenhagen, Denmark. He has published several articles, recently focused on methodologies for origin-and-destination forecasting and optimization of simplified fare structures. He serves on the editorial board of the Journal of Revenue and Pricing Management.

2is a product definition analyst in the revenue management area at Amadeus. Currently, she is constructing the dynamic pricing product. She earned her master’s degree in Operations Research from INPG Institut National Polytechnique and her engineering degree from ENSIMAG in Grenoble, France.

3is a software development engineer at Amadeus, and a main contributor to the development of the Altéa Benchmarking Engine (ABE) simulation tool. Currently, he works in revenue management and operations research. He holds an engineering degree in Mathematics and Computer Science from ENSIMAG in Grenoble, France.

4is a freelance engineer specializing in pricing, revenue management and air transportation scheduling. While at American Airlines and Sabre, he developed many of the revenue management techniques used throughout the airline industry and pioneered the application of revenue management techniques in other industries. He holds patents in reservation system design, scheduling, pricing, operations and online retailing. He is an AGIFORS past president and Fellow. He led a team that received the Edelman Award and INFORMS Revenue Management Section Prize for their work on revenue management at American Airlines.

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Fiig, T., Goyons, O., Adelving, R. et al. Dynamic pricing – The next revolution in RM?. J Revenue Pricing Manag 15, 360–379 (2016). https://doi.org/10.1057/rpm.2016.28

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  • dynamic pricing (DP)
  • distribution
  • revenue management system (RMS)
  • global distribution systems (GDS)
  • Passenger Origin Destination Simulator (PODS)
  • Altéa Benchmarking Engine (ABE)