Abstract
To remedy the lack of mathematical programming and the Expected Marginal Seat Revenue (EMSR) model for multi-leg seat inventory control, this paper proposes a method based on passenger choice. Except for data about which seats passengers decide to opt for, there is no need to obtain distributions of passengers' demands or other “a priori” information. The proposed method can discover the real factors that affect passengers' choices, and then estimate the probabilities of seat choices and the revenue according to the weights of the factors. Simulated experiments and comparison with the shadow price method and the virtual “bucket” method confirm the feasibility and effectiveness of the proposed method in seat inventory control for multi-leg flights.
Highlights
In recent years, the aviation and passenger transport industry has developed swiftly with rapid economic growth
The traditional Expected Marginal Seat Revenue (EMSR) model, and the seat inventory control model based on mathematical programming for the multi-leg seat allocation problem, assume that the needs of passengers follow independent normal distributions
After American deregulation in the 1970s, the emergence of fare levels lead to the seat inventory control problem becoming a focal issue
Summary
The aviation and passenger transport industry has developed swiftly with rapid economic growth. The traditional Expected Marginal Seat Revenue (EMSR) model, and the seat inventory control model based on mathematical programming for the multi-leg seat allocation problem, assume that the needs of passengers follow independent normal distributions. Hersh and Ladany presented a model considering the time distribution of reservations and cancellations, as well as the effects of waiting lists, standbys and overbookings; the model constructed a Bayesian reassessment of the probabilities sequential decision procedure. Such a model accords more importance to factors such as standbys and overbookings[2]. In 2006, Wang took the logit model as a foundation and analysed cabin choice behaviour for a specific service and a particular type of passenger[5]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Engineering Business Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
