Revenue Management System for the Cruise Industry: A Simulation Study

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.