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A model to assess public transport demand stability

Author

Listed:
  • Bass, Pablo
  • Donoso, Pedro
  • Munizaga, Marcela

Abstract

Transport authorities, especially those in developing countries where rising income stimulate increased car ownership rates, are often concerned with maintaining or increasing levels of public transport use. Therefore, the ability to identify clients at risk of abandoning the system can be valuable for remedial measures, allowing for more focused quality improvements. We present and apply a model that determines the probability of migrating from public to private transport at both aggregated and disaggregated levels. In application, the model predicted migration with 60% accuracy in the first preference recovery measure. The proposed model can improve the understanding of the behavior of public transport users, the analysis of demand stability and the factors influencing migration. This, in turn, can help to focus policy and management measures and increase the efficiency of public investment.

Suggested Citation

  • Bass, Pablo & Donoso, Pedro & Munizaga, Marcela, 2011. "A model to assess public transport demand stability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 755-764, October.
  • Handle: RePEc:eee:transa:v:45:y:2011:i:8:p:755-764
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    References listed on IDEAS

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    1. María Yáñez & Patricio Mansilla & Juan de Ortúzar, 2010. "The Santiago Panel: measuring the effects of implementing Transantiago," Transportation, Springer, vol. 37(1), pages 125-149, January.
    2. Hensher, David A. & Stopher, Peter & Bullock, Philip, 2003. "Service quality--developing a service quality index in the provision of commercial bus contracts," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(6), pages 499-517, July.
    3. Gaundry, Marc J. I. & Dagenais, Marcel G., 1979. "The dogit model," Transportation Research Part B: Methodological, Elsevier, vol. 13(2), pages 105-111, June.
    4. H C W L Williams, 1977. "On the Formation of Travel Demand Models and Economic Evaluation Measures of User Benefit," Environment and Planning A, , vol. 9(3), pages 285-344, March.
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    Cited by:

    1. Gschwender, Antonio & Munizaga, Marcela & Simonetti, Carolina, 2016. "Using smart card and GPS data for policy and planning: The case of Transantiago," Research in Transportation Economics, Elsevier, vol. 59(C), pages 242-249.
    2. Bastani, Parisa & Heywood, John B. & Hope, Chris, 2012. "The effect of uncertainty on US transport-related GHG emissions and fuel consumption out to 2050," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 517-548.

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