Author:
Ahlberg Ernst,Mirkina Irina,Olsson Alfred,Söyland Christian,Carlsson Lars
Abstract
AbstractThe success of revenue management models depends to a large extent on the quality of historical data used to forecast future bookings. Several theoretical models and best practices of handing historical data have been developed over the years, that all rely on assumptions about underlying distribution and seasonality in the historical data. In this paper, we describe a novel method that compares the fingerprints of the departure to optimise and selects historical departures without making assumptions on data distribution or seasonality. By evaluating the method at the departure level and using the Nemenyi rank test, we show the method’s application in the ferry transportation business and discuss its advantages.
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Economics and Econometrics,Finance,Business and International Management
Reference13 articles.
1. Belobaba, P.P. 2016. Optimization models in RM systems: Optimality versus revenue gains. Journal of Revenue and Pricing Management 15 (3): 229–235. https://doi.org/10.1057/rpm.2016.13.
2. Belobaba, P. P., and C. Hopperstad. 2004. Algorithms for revenue management in unrestricted fare markets. In: Meeting of the INFORMS Section on Revenue Management, Massachusetts Institute of Technology, Cambridge, MA.
3. Hossein, T., and L. Weatherford. 2017. Application of an alternative expected marginal seat revenue method (EMSRC) in unrestricted fare environments. Journal of Air Transport Management 62: 65–77. https://doi.org/10.1016/j.jairtraman.2017.02.006.
4. Larry, Weatherford. 2016. The history of forecasting models in revenue management. Journal of Revenue and Pricing Management 15 (3): 212–221.
5. L’Heureux, E. 1986. A new twist in forecasting short-term passenger pickup. In AGIFORS Proceedings.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Retail pricing models;Journal of Revenue and Pricing Management;2023-07-25