Modeling Demographic and Unobserved Heterogeneity in Air Passengers’ Sensitivity to Service Attributes in Itinerary Choice

Abstract

Modeling passengers’ flight choice behavior is valuable to understanding the increasingly competitive airline market and predicting air travel demand. Standard and mixed-multinomial logit models of itinerary choice for business travel are estimated on the basis of a stated preference survey conducted in 2001. The results suggest that observed demographic- and trip-related differences are incorrectly manifested as unobserved heterogeneity in a random-coefficient mixed logit model that ignores the demographic- and trip-related characteristics of travelers. Among demographics, gender and income level have the most noticeable effects on sensitivity to service attributes in itinerary choice behavior, but membership in a frequent flyer program, employment status, travel frequency, and group travel also emerge as important determinants. However, residual heterogeneity is significant because of unobserved factors, even after accommodating sensitivity variations due to demographic- and trip-related factors. Consequently, substitution rates for each service attribute show substantial variations in the willingness to pay among observationally identical business passengers.

Do carriers internalize congestion costs? Empirical evidence on the internalization question

“…5 Congestion related delays have also been shown to influence travel decisions. For example, Warburg et al (2006) show that on-time performance is one of several important itinerary choice factors for airline passengers. In the roadway literature, Small (1982) shows that urban commuters change their schedule to avoid congested highways.…”

Analyzing key socio-economic and socio-demographic drivers of domestic passengers’ airline choice behavior in Turkey using multinomial and mixed logit models

“…Educational level and marital status were demonstrated as influencing factors by some earlier work (Oyewole 2001;Tyrell et al 2001;Ong and Tan 2010). Not surprisingly, past studies (Tyrell et al 2001;Warburg et al 2006;Yang, Lu and Hsu 2014) found that income level and occupational status were significantly associated with passengers' airline, airport, or destination choices as a socio-economic or socio-demographic indicator.…”

“…The low-care business model purposes to Several other socio-economic, socio-demographic, alternative-specific, or destination attributes have been found to have an impact on passengers' airline or airport choice. Some prior studies (Oyewole 2001;Warburg, Bhat and Adler 2006) found that passengers' gender might have a significant impact on passengers' stated airline or airport preference. Further, other past research (Tyrell, Countryman, Hong and Cai 2001;Tsaur and Wu 2005) highlighted the significant association between several age groups and passengers' choice.…”

Predicting Aggregate Air Itinerary Shares Using Discrete Choice Modeling

“…Only a few studies present approaches for itinerary market share estimation across multiple dimensions using discrete choice modeling. From those, early models used a multinomial logit (MNL) approach 8,9,10,11 ; while more recent models also apply nested logit (NL) models 12,13 , mixed multinomial logit (MMNL) models 14 and other alternatives approaches 15,16 . The mentioned aggregate passenger-allocation studies can be classified with respect the type of data they are based on: revealed preference data (RP) or booking data; stated preferences (SP) data or survey data; and a combination of both.…”