Reference : Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application t...
Scientific journals : Article
Business & economic sciences : Quantitative methods in economics & management
http://hdl.handle.net/2268/192501
Accounting for Price Endogeneity in Airline Itinerary Choice Models: An Application to Continental U.S. Markets
English
Lurkin, Virginie [Université de Liège > HEC-Ecole de gestion de l'ULg : UER > UER Opérations : Informatique de gestion >]
Garrow, Laurie mailto [Georgia Institute of Technology > School of Civil and Environmental Engineering > > >]
Higgins, Matthew mailto [Georgia Institute of Technology > Ernest Scheller Jr. College of Business > > >]
Newman, Jeffrey mailto [Georgia Institute of Technology > School of Civil and Environmental Engineering > > >]
Schyns, Michael mailto [Université de Liège > HEC-Ecole de gestion de l'ULg : UER > UER Opérations : Informatique de gestion >]
Jun-2017
Transportation Research. Part A : Policy & Practice
Pergamon Press
100
228–246
Yes (verified by ORBi)
International
0965-8564
[en] air travel behavior ; itinerary choice ; time of day preference ; price elasticity ; price endogeneity
[en] Network planning models, which forecast the profitability of airline schedules, support many critical decisions, including equipment purchase decisions. Network planning models include an itinerary choice model which is used to allocate air total demand in a city pair to different itineraries. Multinomial logit (MNL) models are commonly used in practice and capture how individuals make trade-offs among different itinerary attributes; however, none that we are aware of account for price endogeneity. This study formulates an itinerary choice model that is consistent with those used by industry and corrects for price endogeneity using a control function that uses several types of instrumental variables. We estimate our models using database of more than 3 million tickets provided by the Airlines Reporting Corporation. Results based on Continental U.S. markets for May 2013 departures show that models that fail to account for price endogeneity overestimate customers’ value of time and result in biased price estimates and incorrect pricing recommendations. The size and comprehensiveness of our database allows us to estimate highly refined departure time of day preference curves that account for distance, direction of travel, the number of time zones traversed, departure day of week and itinerary type (outbound, inbound or one-way). These time of day preference curves can be used by airlines, researchers, and government organizations in the evaluation of different policies such as congestion pricing.
QuantOM, Georgia Institute of Technology
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS
Researchers ; Professionals
http://hdl.handle.net/2268/192501
10.1016/j.tra.2017.04.007

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