Modeling competition among airline itineraries
Laurie A. Garrow,
Matthew Higgins (),
Jeffrey P. Newman and
Transportation Research Part A: Policy and Practice, 2018, vol. 113, issue C, 157-172
Discrete choice models are commonly used to forecast the probability an airline passenger chooses a specific itinerary. In a prior study, we estimated an itinerary choice model based on a multinomial logit specification that corrected for price endogeneity. In this paper, we extend the analysis to include inter-itinerary competition along three dimensions: nonstop versus connecting level of service, carrier, and time of day using nested logit (NL) and ordered generalized extreme value (OGEV) models. To the best of our knowledge, these are the first NL and OGEV itinerary choice models to correct for price endogeneity. Despite the many structural changes that have occurred in the airline industry, our results are strikingly similar to models estimated more than a decade ago. These results are important because it suggests that customer preferences, on average, have been stable over time and are similar across distribution channels. The stability in inter-itinerary competition patterns provides an important practical implication for airlines, namely it reduces the need to frequently update the parameter estimates for these models.
Keywords: Air travel behavior; Itinerary choice; Nested logit; Ordered generalized extreme value models (search for similar items in EconPapers)
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