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How network structure can boost and shape the demand for bus transit

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  • Badia, Hugo
  • Argote-Cabanero, Juan
  • Daganzo, Carlos F.

Abstract

Conventional wisdom states that transit riders are averse to transfers and that consequently bus networks should be designed to limit their number. Probably as a result of this belief, many real bus systems try to connect as many origins and destinations as possible without transfers, so they are usually composed of long, circuitous routes with redundant overlapping sections – and the resulting bus map is hard to understand. If coverage is extensive, many routes are needed. Economics then prevents an agency from populating all routes with sufficient buses to provide attractively frequent service. This low frequency and the complicated circuitous map discourage transfers, perpetuating the belief that people are averse to transferring. Not surprisingly, the percentage of bus trips that includes a transfer has been reported to be: 1.5% for Boston, 3% for New York, 13% for London, and 16% for Melbourne.

Suggested Citation

  • Badia, Hugo & Argote-Cabanero, Juan & Daganzo, Carlos F., 2017. "How network structure can boost and shape the demand for bus transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 83-94.
    • Handle: RePEc:eee:transa:v:103:y:2017:i:c:p:83-94
    DOI: 10.1016/j.tra.2017.05.030
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    References listed on IDEAS

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    1. Estrada, M. & Roca-Riu, M. & Badia, H. & Robusté, F. & Daganzo, C.F., 2011. "Design and implementation of efficient transit networks: Procedure, case study and validity test," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 935-950, November.
    2. Daganzo, Carlos F., 2010. "Structure of competitive transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 434-446, May.
    3. Jeffrey Brown & Gregory Thompson, 2008. "Examining the influence of multidestination service orientation on transit service productivity: a multivariate analysis," Transportation, Springer, vol. 35(2), pages 237-252, March.
    4. Badia, Hugo & Estrada, Miquel & Robusté, Francesc, 2016. "Bus network structure and mobility pattern: A monocentric analytical approach on a grid street layout," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 37-56.
    5. Carlos F. Daganzo, 1987. "The Break-Bulk Role of Terminals in Many-to-Many Logistic Networks," Operations Research, INFORMS, vol. 35(4), pages 543-555, August.
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    Cited by:

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    2. Ansarilari, Zahra & Bodur, Merve & Shalaby, Amer, 2024. "A novel model for transfer synchronization in transit networks and a Lagrangian-based heuristic solution method," European Journal of Operational Research, Elsevier, vol. 317(1), pages 76-91.
    3. Yao, Di & Xu, Liqun & Li, Jinpei, 2020. "Does technical efficiency play a mediating role between bus facility scale and ridership attraction? Evidence from bus practices in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 77-96.
    4. Hugo Badia, 2020. "Comparison of Bus Network Structures in Face of Urban Dispersion for a Ring-Radial City," Networks and Spatial Economics, Springer, vol. 20(1), pages 233-271, March.
    5. Dakic, Igor & Leclercq, Ludovic & Menendez, Monica, 2021. "On the optimization of the bus network design: An analytical approach based on the three-dimensional macroscopic fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 393-417.
    6. Chinnawat Hoonsiri & Vasin Kiattikomol & Siriluk Chiarakorn, 2020. "Energy Saving and CO 2 Reduction Potential from Partial Bus Routes Reduction Model in Bangkok Urban Fringe," Energies, MDPI, vol. 13(22), pages 1-18, November.
    7. Manser, Patrick & Becker, Henrik & Hörl, Sebastian & Axhausen, Kay W., 2020. "Designing a large-scale public transport network using agent-based microsimulation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 1-15.
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