Modelling and simulation of impact of revenue management on Japan's domestic market

Revenue management has been shown to be an effective tool for increasing revenues in a variety of domestic and international airline markets. Owing to the significant volume of group passengers and differences in characteristics between the Japanese and other markets outside Japan, however, it has been difficult for Japanese airlines to determine whether revenue management methods will bring them similar revenue increases if applied to their domestic operations. An investigation of the impact of revenue management on airlines in Japan's domestic market is presented in this paper, taking into account the important role of group bookings in this environment. This paper first introduces the unique characteristics of the Japanese domestic market and describes the business and revenue management processes typically used by Japanese airlines. In preparation for the modelling of group bookings, parameters to describe the behaviour of group bookings are estimated, using data collected from Japanese airlines. Based on the parameters of the group booking data analysed, a model of the group passenger booking process is then developed and the model's framework is used for simulation. The Passenger Origin–Destination Simulator (PODS), originally designed to simulate revenue management for individual passenger bookings, is modified to incorporate the group booking process and used for the investigation. Leg–based seat inventory control, specifically fare class yield management (FCYM) with the expected marginal seat revenue (EMSRb) algorithm, is applied as the revenue management method, and it is shown to result in increased revenue for the implementing airline(s) in a representative Japanese domestic market, with group bookings incorporated. The result of simulations of scenarios reflecting the recent integration of two large Japanese domestic carriers and direct competition with a third existing carrier suggest that the revenue gains from using FCYM are as high as 5 per cent when one competitor implements systematic RM forecasting and optimisation. The simulated revenue gains are substantially less under scenarios in which both competitors implement FCYM, at about 1 per cent for each carrier.