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Crowding in public transport: Who cares and why?

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  • Haywood, Luke
  • Koning, Martin
  • Monchambert, Guillaume

Abstract

Crowding on public transport (PT) is a major issue for commuters around the world. Nevertheless, economists have rarely investigated the causes of crowding discomfort. Furthermore, most evidence on the costs of PT crowding is based on trade-offs between crowding, travel time and money. First, this paper assesses discomfort with PT crowding at various density levels across heterogeneous individuals using a different methodology. Based on a survey of 1000 Paris PT users, the negative relationship of in-vehicle density on reported satisfaction is similar to previous studies investigating PT crowding costs and stable across most individual characteristics. We also find a sensitive increase in crowding costs over users’ income. Second, we investigate the causes of this discomfort effect. We identify three key drivers: (a) dissatisfaction with standing and not being seated; (b) less opportunities to make use of the time during the journey; (c) the physical closeness of other travelers per se.

Suggested Citation

  • Haywood, Luke & Koning, Martin & Monchambert, Guillaume, 2017. "Crowding in public transport: Who cares and why?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 215-227.
  • Handle: RePEc:eee:transa:v:100:y:2017:i:c:p:215-227 DOI: 10.1016/j.tra.2017.04.022
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    Cited by:

    1. Hörcher, Daniel & Graham, Daniel J. & Anderson, Richard J., 2017. "Crowding cost estimation with large scale smart card and vehicle location data," Transportation Research Part B: Methodological, Elsevier, pages 105-125.
    2. repec:eee:transa:v:103:y:2017:i:c:p:311-326 is not listed on IDEAS

    More about this item

    Keywords

    Public transport; Crowding; Stated satisfaction; Travel cost; Survey data;

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • 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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