Train commuters’ scheduling preferences: Evidence from a large-scale peak avoidance experiment
Stefanie Peer (),
Jasper Knockaert and
Erik Verhoef ()
Transportation Research Part B: Methodological, 2016, vol. 83, issue C, 314-333
We study the trip scheduling preferences of train commuters in a real-life setting. The underlying data have been collected during large-scale peak avoidance experiment conducted in the Netherlands, in which participants could earn monetary rewards for traveling outside peak hours. The experiment included ca. 1000 participants and lasted for multiple months. Holders of an annual train pass were invited to join the experiment, and a customized smartphone app was used to measure the travel behavior of the participants. We find that compared to the pre-measurement, the relative share of peak trips decreased by 22% during the reward period, and by 10% during the post-measurement. By combining multiple complementary data sources, we are able to specify and estimate (MNL and panel latent class) departure time choice models. These yield plausible estimates for the monetary values that participants attach to reducing travel time, schedule delays, the number of transfers, crowdedness, and unreliability.
Keywords: Scheduling decisions; Revealed preference data; Train commuters; Smartphone app; GPS data; Valuations of trip attributes (search for similar items in EconPapers)
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Working Paper: Train Commuters' Scheduling Preferences: Evidence from a Large-Scale Peak Avoidance Experiment (2015)
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