Risk Aversion to Short Connections in Airline Itinerary Choice

Abstract

Network airlines traditionally attempt to minimize passenger connecting times at hub airports, assuming that passengers prefer minimum scheduled elapsed times for their trips. However, minimizing connecting times creates schedule peaks at hub airports. These peaks are extremely cost-intensive in terms of additional personnel, resources, runway capacity, and schedule recovery. Consequently, passenger connecting times should be minimized only if the anticipated revenue gain of minimizing passenger connecting times is larger than the increase in operating cost (i.e., if this policy increases overall operating profit). The extent to which a change in elapsed time affects passenger itinerary choice–-and thus an airline's market share–-is analyzed. An existing airline itinerary choice survey is extended to test the assumption that passenger demand is affected by the length of connecting times. Previous studies have not explicitly focused on the connecting time at hubs in their models. The hypothesis is that passengers might incur lower utilities from shorter connecting time versus longer connecting times based on the potential discomfort of a hasty connection and the misconnection risk associated with short connecting times. A stated preference experiment is performed, and socioeconomic data are collected to estimate a choice model. Multinomial logit model results support this hypothesis and refute the traditional network airline assumption.

Interactive stated choice surveys: a study of air travel behaviour

“…Proussaloglou and Koppelman (1995) examined the choice of airline for recent trips using mail-in RP data. Theis et al (2006) examined the impact of connection time at hubs. In recent years, a majority of studies have used the SP methodology.…”

Quantified Traveler: Travel Feedback Meets the Cloud to Change Behavior

“…including only attitude or other psychological constructs) using path analysis or discrete choice models (e.g. [24,25,26,27,28,29]), most of these studies have relied on either stated preferences surveys or on revealed behavior measured at one point in time, and feedback mechanisms and social comparison processes are not generally represented in these models. Beyond the contributions related to the overall QT system and experiment, a modeling contribution of this work is to model behavior change in a revealed travel experimental context, i.e., by using an app on a smartphone to log travel continuously for 3 weeks, and using the logs for a feedback treatment mechanism.…”

Modeling Passenger Travel and Delays in the National Air Transportation System

“…Theis, Adler, Clarke, & Ben-Akiva (2006) demonstrate that passengers travelling on one-stop itineraries are sensitive to connection times, specifically exhibiting a disutility associated with both short and long connection times. The referenced study by Coldren & Koppelman (2005) suggests that passengers prefer travelling on larger aircraft.…”