Revenue Management System for the Cruise Industry: A Simulation Study
Donghui Ma and
Jin Sun
Chapter 11 in Cruise Management, 2012, pp 223-232 from Springer
Abstract:
Abstract The fast growing cruise line industry anticipates huge uncertainties in its business environment. The cruise companies face uncertainty from four main sources: demand, competition, distribution channel, as well as the economic and political environment. The uncertainty brings risks as well as opportunities for the cruise industry, and a key issue is to understand the nature of the uncertainty and optimize profit by using appropriate management techniques. Depending on the prediction of expected customer preferences, different revenue management strategies should be implemented (Ji & Mazzarella, 2006). In this study, we developed simulation framework to compare 3 different revenue management methods with the simulated data. The first method is the First Come First Service (FCFS); the second method was the Dynamic Class Allocation (DCA). The last method, the Modified DCA, was derived by updating the underlying distributions of demand by current booking data with Bayesian approach. The aim is to find a universal powerful method which depends less on the revenue manager’s subject prediction of the demand by combining his belief and the real time booking data. The simulation result shows that when the demand estimated from historical data was not representing the future, by using the modified method, we can significantly improve revenue by updating demand information.
Keywords: revenue management; nested class allocation; dynamic class allocation; cabin fares; cruise lines; Bayesian updating (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations: View citations in EconPapers (1)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-8349-7159-3_11
Ordering information: This item can be ordered from
http://www.springer.com/9783834971593
DOI: 10.1007/978-3-8349-7159-3_11
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().