Airline Retailing « Categories

Corporate globalisation has led to a significant increase in business travel in recent years, and large corporations use travel management agencies to provide a hassle-free experience for their employees. Using historical airline corporate booking data, this study examines the travel patterns of corporate clients. In the research, one year of corporate travel booking data is evaluated, and prediction algorithms are utilised to recommend itineraries to business travellers for a specific origin-destination pair with numerous combinations. A boosting method is used to anticipate booking and non-booking events based on a prediction probability threshold value. The results indicate that the origin-destination (OD) pair and the airline of travel are the most important aspects of corporate booking selection. The choice probability is further used for recommending a few combinations for a selected OD pair which is a practical application of this analysis. To download the online version of this whitepaper, click here. Please note that you would require a subscription to access this whitepaper. ————————————————————————————————————— This whitepaper was created in partnership with the Indian Institute of Technology, Madras; and was authored by Prabhupad Bharadwaj (IIT-M), Sunitha Chandrasekaran (Sabre), and Sanjeeb Patel (Sabre). The paper is published is published in the International Journal of Revenue Management (IJRM), Vol. 13, No. 4, 2023 by Inderscience Publishers – a global academic publisher based in Geneva, Switzerland.

Airline Retailing

Corporate Booking Recommendation Using a Machine Learning Approach