Revenue Management Model Based on Capacity Sharing and Overbooking in the Airline

Abstract

Aviation industry often faced uncertainty demand and high level of cancellation. Revenue management in the airline is related to demand management policies to classify and estimate the various requests of pricing and capacity control. This study will develop airline revenue management model integrates luggage passengers with air cargo based on the control of air cargo space. The airline must pay attention to customer behavior due to high cancellation and no-show. In this case we deal with the aspect of the overbooking in which one of the ways to reduce the cost of spoilage due to cancellation or no show. Moreover, in this proposed model, we discuss the expected revenue function to maximize the expected revenue from the policies of accept or reject the booking requests between passengers and air cargo by the same airline. This study aims to develop expected revenue in the dynamic programming model in order to maximize the revenue expectations of the policy of accepting and rejecting booking request between passengers with air cargo in the same airline.

No-Show Passenger Prediction for Flights

“…Overbooking is a policy of selling tickets above the seating capacity. This policy has a risk and might potentially cost the airline if the number of customers who show up for departure exceeds seat capacity because the airline must give specified compensation for overbooking penalties [32]. In these situations, the airline usually looks for volunteers to take a later trip in exchange for payment, like a voucher for a future flight.…”

“…2) Revenue Management: Revenue management is an important part of the airline sector that entails adopting demand management strategies to forecast price and capacity control for various demands effectively. Airlines operate on a business model similar to that of perishable goods, which means that if seats or cargo space remain unsold before a flight, the opportunity to generate revenue is lost [32]. With high fixed costs, revenue management is utilized to predict demand uncertainty issues since excess inventory cannot be stored or carried over to the next period due to the limited capacity of seats and cargo space.…”