A heuristic for incorporating ancillaries into air choice models with personalization (part 2: integrated multinomial logit and hedonic regression models)-Reference-Cited by-同舟云学术

A heuristic for incorporating ancillaries into air choice models with personalization (part 2: integrated multinomial logit and hedonic regression models)

Published:2022-12-07 Issue:2 Volume:22 Page:140-151
ISSN:1476-6930
Container-title:Journal of Revenue and Pricing Management
language:en
Short-container-title:J Revenue Pricing Manag

Author:

Sznajder Michal,Ratliff Richard,Kaya Cuneyd

Publisher

Springer Science and Business Media LLC

Subject

Strategy and Management,Economics and Econometrics,Finance,Business and International Management

Link

https://link.springer.com/content/pdf/10.1057/s41272-022-00400-y.pdf

Reference16 articles.

1. Acuna-Agost, R., E. Thomas, and A. Lheritier. 2021. Price elasticity estimation for deep learning-based choice models: An application to air itinerary choices. Journal of Revenue and Pricing Management 20 (3): 213–226. https://doi.org/10.1057/s41272-021-00308-z.

2. Babic, R.S., M. Ozmec-Ban, and J. Bajic. 2019. A review of recent trends in airline ancillary revenues. Economy and Market Communication Review 9 (1): 136–155.

3. Freeman, K., and K. Turney. 2015. The race is on: Delivering a differentiated customer experience in the age of airline retailing. Sabre Ascend Magazine, vol. 2.

4. Garrow, L.A. 2010. Discrete choice modelling and air travel demand: Theory and applications. Farnham: Ashgate Publishing.

5. Goodman, A.C. 1983. Willingness to pay for car efficiency: A hedonic price approach. Journal of Transport Economics and Policy 17 (3): 247–266.

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