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Train commuters’ scheduling preferences: Evidence from a large-scale peak avoidance experiment

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  • Peer, Stefanie
  • Knockaert, Jasper
  • Verhoef, Erik T.

Abstract

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.

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  • Peer, Stefanie & Knockaert, Jasper & Verhoef, Erik T., 2016. "Train commuters’ scheduling preferences: Evidence from a large-scale peak avoidance experiment," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 314-333.
    • Handle: RePEc:eee:transb:v:83:y:2016:i:c:p:314-333
    DOI: 10.1016/j.trb.2015.11.017
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    7. Yen, Barbara T.H. & Mulley, Corinne & Meza, Gerardo, 2023. "Exploring the attitudes and perceptions influencing user participation in gamification schemes for TDM," Research in Transportation Economics, Elsevier, vol. 99(C).
    8. Jinwon Kim & Jucheol Moon, 2022. "Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data," Working Papers 2201, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
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    10. Jasper Knockaert & Stefanie Peer & Erik Verhoef, 2016. "Identification of self-selection biases in field experiments using stated preference experiments," Natural Field Experiments 00568, The Field Experiments Website.
    11. Anupriya, & Graham, Daniel J. & Hörcher, Daniel & Anderson, Richard J. & Bansal, Prateek, 2020. "Quantifying the ex-post causal impact of differential pricing on commuter trip scheduling in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 16-34.
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    13. Raphaël Homayoun Boroumand & Stéphane Goutte & Thomas Péran & Thomas Porcher, 2019. "Worker mobility and the purchase of low CO2 emission vehicles in France: a datamining approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 16(2), pages 171-205, December.
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    18. Liang, Jinpeng & Zang, Guangzhi & Liu, Haitao & Zheng, Jianfeng & Gao, Ziyou, 2023. "Reducing passenger waiting time in oversaturated metro lines with passenger flow control policy," Omega, Elsevier, vol. 117(C).

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    More about this item

    Keywords

    Scheduling decisions; Revealed preference data; Train commuters; Smartphone app; GPS data; Valuations of trip attributes;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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