Choice Based Revenue Management for Parallel Flights

41 Pages Posted: 8 Mar 2014 Last revised: 23 May 2015

See all articles by J. Dai

J. Dai

Operations Research & Information Engineering

Weijun Ding

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

Anton Kleywegt

Georgia Institute of Technology - School of Industrial and Systems Engineering

Xinchang Wang

Washington State University

Yi Zhang

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

Date Written: March 5, 2014

Abstract

This paper describes a revenue management problem of a major airline that operates in a very competitive market involving two major hubs and having more than 30 parallel daily flights. We consider choice based stochastic assortment optimization problems to maximize the expected revenue for the airline. The inputs include models of booking arrival rates, competitor assortment selection probabilities, customers' booking choices among the airline's own flights as well as competitors' flights, booking-to-ticketing conversion probabilities, and go-show and no-show probabilities. We build a variety of booking choice models to incorporate unobserved heterogeneous customer preferences for different departure times. The way departure time preferences are modeled dramatically affects price sensitivity estimates, and therefore the modeling of heterogeneous departure time preferences matters. We also show that customer choice behavior exhibits discontinuities, with much greater demand for the cheapest alternative than for the second cheapest alternative even when the price difference is small, and much greater demand for fully refundable tickets than almost fully refundable tickets. We formulate a deterministic (fluid) optimization problem corresponding to each of the booking choice models, and we show that in some cases these problems can be solved efficiently even when the discontinuities cause violation of the independence from irrelevant alternatives property. The resulting solutions are used to determine assortment selection policies for the stochastic problem. Simulation studies show that several of these policies generate significantly more revenue than the airline's existing policy, and that the improved performance of these policies is robust with respect to misspecification errors as well as with respect to errors in parameter estimates.

Keywords: Pricing and Revenue Management, Transportation, Consumer Behavior

JEL Classification: R41, C51, C61

Suggested Citation

Dai, J. and Ding, Weijun and Kleywegt, Anton and Wang, Xinchang and Zhang, Yi, Choice Based Revenue Management for Parallel Flights (March 5, 2014). Available at SSRN: https://ssrn.com/abstract=2404193 or http://dx.doi.org/10.2139/ssrn.2404193

J. Dai

Operations Research & Information Engineering ( email )

226 Rhodes Hall
136 Hoy Road
Ithaca, NY 14853
United States

Weijun Ding

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

Anton Kleywegt

Georgia Institute of Technology - School of Industrial and Systems Engineering ( email )

Atlanta, GA 30332
United States

Xinchang Wang (Contact Author)

Washington State University ( email )

Dept of Fin and Mgt Science
PO BOX 644746
Pullman, WA 99164-4746
United States

Yi Zhang

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

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