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Public transport user's perception and decision assessment using tactic-based guidelines

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  • Nesheli, Mahmood Mahmoodi
  • Ceder, Avishai (Avi)
  • Estines, Simon

Abstract

An important step in the development of an integrated system is for policy-makers and public transport (PT) operators to remove the uncertainty of PT service performance in real-time. Implementing proper control actions, such as tactics, leads to reducing passenger waiting time and preventing missed transfers. These two undesirable features are major contributors to PT’s negative image. However, there has been no specific investigation of the effect of implementing tactics on passengers’ perceptions and decisions (demand side). This paper presents the results of a qualitative and quantitative study of PT users to obtain a deeper understanding of travelers’ attitudes toward transport uncertainty and to explore perceptions of real-time operational tactics on PT service quality. The study is undertaken in two-parts: (a) assessment of the effects of delay on PT users’ perception and decision to change route or mode; (b) evaluation of users’ decision based on various real-time operational tactics. To investigate users’ perception and decisions related to various operational tactics, a user-preference survey was conducted at a major terminal in Auckland, New Zealand, and Lyon, France. The survey data was modeled following a Multinomial Logistic Regression and a decision-tree-based method. The statistical analysis emphasized that, in various situations (e.g., waiting at a stop for more than 10min), more than 60% of the travelers will change their decision and adapt travel behaviors based on a decision-support tool. The findings provide policy makers with an understanding of the behavioral aspect of real-time operational tactics.

Suggested Citation

  • Nesheli, Mahmood Mahmoodi & Ceder, Avishai (Avi) & Estines, Simon, 2016. "Public transport user's perception and decision assessment using tactic-based guidelines," Transport Policy, Elsevier, vol. 49(C), pages 125-136.
    • Handle: RePEc:eee:trapol:v:49:y:2016:i:c:p:125-136
    DOI: 10.1016/j.tranpol.2016.04.007
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    References listed on IDEAS

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    1. Grotenhuis, Jan-Willem & Wiegmans, Bart W. & Rietveld, Piet, 2007. "The desired quality of integrated multimodal travel information in public transport: Customer needs for time and effort savings," Transport Policy, Elsevier, vol. 14(1), pages 27-38, January.
    2. Beirão, Gabriela & Sarsfield Cabral, J.A., 2007. "Understanding attitudes towards public transport and private car: A qualitative study," Transport Policy, Elsevier, vol. 14(6), pages 478-489, November.
    3. Eboli, Laura & Mazzulla, Gabriella, 2012. "Performance indicators for an objective measure of public transport service quality," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 51, pages 1-4.
    4. Ceder, Avishai & Chowdhury, Subeh & Taghipouran, Nima & Olsen, Jared, 2013. "Modelling public-transport users’ behaviour at connection point," Transport Policy, Elsevier, vol. 27(C), pages 112-122.
    5. G. V. Kass, 1980. "An Exploratory Technique for Investigating Large Quantities of Categorical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 119-127, June.
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    4. Jara-Diaz, Sergio & Monzon, Andres & Cascajo, Rocio & Garcia-Martinez, Andres, 2022. "An international time equivalency of the pure transfer penalty in urban transit trips: Closing the gap," Transport Policy, Elsevier, vol. 125(C), pages 48-55.

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