IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v88y2020ics0966692320302283.html
   My bibliography  Save this article

Profiling tourists' use of public transport through smart travel card data

Author

Listed:
  • Gutiérrez, Aaron
  • Domènech, Antoni
  • Zaragozí, Benito
  • Miravet, Daniel

Abstract

Data collected through smart travel cards in public transport networks have become a valuable source of information for transport geography studies. During the last two decades, a growing body of literature has used this sort of data source to study the behaviour of public transport users in cities and regions around the world. However, its use has been scarce in contexts where public transport demand is highly influenced by the activities of the tourist sector. Therefore, it remains to be seen whether these data can be leveraged to optimize the supply of public transport. In this article, data drawn from the Camp de Tarragona automated fare collection system extracted during 2018 are used to study tourists' use of public transport in Costa Daurada (Catalonia, Spain). This is a popular coastal destination with a high concentration of visitors during the summer period. The analysis focuses on the use of the T-10, a multipersonal transport fare with no time limitations on its use which makes it appealing for tourists. Model-based clustering has been applied to identify different clusters of passengers according to their activity and spatial profiles. Differences between profiles are significant and, as a result, this study allowed the validation of a method that could be replicated in other contexts, as it provides highly useful information for public transport policy and mobility management.

Suggested Citation

  • Gutiérrez, Aaron & Domènech, Antoni & Zaragozí, Benito & Miravet, Daniel, 2020. "Profiling tourists' use of public transport through smart travel card data," Journal of Transport Geography, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:jotrge:v:88:y:2020:i:c:s0966692320302283
    DOI: 10.1016/j.jtrangeo.2020.102820
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692320302283
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2020.102820?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Albalate, Daniel & Bel, Germà, 2010. "Tourism and urban public transport: Holding demand pressure under supply constraints," Tourism Management, Elsevier, vol. 31(3), pages 425-433.
    2. Bagchi, M. & White, P.R., 2005. "The potential of public transport smart card data," Transport Policy, Elsevier, vol. 12(5), pages 464-474, September.
    3. Aaron Gutiérrez & Daniel Miravet, 2016. "The Determinants of Tourist Use of Public Transport at the Destination," Sustainability, MDPI, vol. 8(9), pages 1-16, September.
    4. Ed Manley & Chen Zhong & Michael Batty, 2018. "Spatiotemporal variation in travel regularity through transit user profiling," Transportation, Springer, vol. 45(3), pages 703-732, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sun, Li & Zhao, Juanjuan & Zhang, Jun & Zhang, Fan & Ye, Kejiang & Xu, Chengzhong, 2024. "Activity-based individual travel regularity exploring with entropy-space K-means clustering using smart card data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    2. Kar, Manaswinee & Sadhukhan, Shubhajit & Parida, Manoranjan, 2022. "Assessing commuters’ perceptions towards improvement of intermediate public transport as access modes to metro stations," Transport Policy, Elsevier, vol. 129(C), pages 140-155.
    3. Benito Zaragozí & Sergio Trilles & Aaron Gutiérrez & Daniel Miravet, 2021. "Development of a Common Framework for Analysing Public Transport Smart Card Data," Energies, MDPI, vol. 14(19), pages 1-22, September.
    4. Türk, Umut & Östh, John & Kourtit, Karima & Nijkamp, Peter, 2021. "The path of least resistance explaining tourist mobility patterns in destination areas using Airbnb data," Journal of Transport Geography, Elsevier, vol. 94(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Benito Zaragozí & Sergio Trilles & Aaron Gutiérrez & Daniel Miravet, 2021. "Development of a Common Framework for Analysing Public Transport Smart Card Data," Energies, MDPI, vol. 14(19), pages 1-22, September.
    2. Barros, Victor & Cruz, Carlos Oliveira & Júdice, Tomás & Sarmento, Joaquim Miranda, 2021. "Is taxation being effectively used to promote public transport in Europe?," Transport Policy, Elsevier, vol. 114(C), pages 215-224.
    3. Oscar Egu & Patrick Bonnel, 2020. "Investigating day-to-day variability of transit usage on a multimonth scale with smart card data. A case study in Lyon," Post-Print halshs-03148937, HAL.
    4. Liao, Cong & Scheuer, Bronte, 2022. "Evaluating the performance of transit-oriented development in Beijing metro station areas: Integrating morphology and demand into the node-place model," Journal of Transport Geography, Elsevier, vol. 100(C).
    5. Kevin Credit & Zander Arnao, 2023. "A method to derive small area estimates of linked commuting trips by mode from open source LODES and ACS data," Environment and Planning B, , vol. 50(3), pages 709-722, March.
    6. Erik Karger & Marvin Jagals & Frederik Ahlemann, 2021. "Blockchain for Smart Mobility—Literature Review and Future Research Agenda," Sustainability, MDPI, vol. 13(23), pages 1-32, November.
    7. Zamparini, L. & Domènech, A. & Miravet, D. & Gutiérrez, A., 2022. "Green mobility at home, green mobility at tourism destinations: A cross-country study of transport modal choices of educated young adults," Journal of Transport Geography, Elsevier, vol. 103(C).
    8. Apanasevic, Tatjana & Rudmark, Daniel, 2021. "Crowdsourcing and Public Transportation: Barriers and Opportunities," 23rd ITS Biennial Conference, Online Conference / Gothenburg 2021. Digital societies and industrial transformations: Policies, markets, and technologies in a post-Covid world 238005, International Telecommunications Society (ITS).
    9. Daniel Albalate del sol, 2015. "Evaluating HSR availability on Tourism: Evidence from Spanish Provinces and Cities," ERSA conference papers ersa15p288, European Regional Science Association.
    10. Fernández, Xosé Luis & Coto-Millán, Pablo & Díaz-Medina, Benito, 2018. "The impact of tourism on airport efficiency: The Spanish case," Utilities Policy, Elsevier, vol. 55(C), pages 52-58.
    11. Bantis, Thanos & Haworth, James, 2020. "Assessing transport related social exclusion using a capabilities approach to accessibility framework: A dynamic Bayesian network approach," Journal of Transport Geography, Elsevier, vol. 84(C).
    12. Nakamura, Hiroki & Abe, Naoya, 2016. "Tourist decisions in renting various personal travel modes: A case study in Kitakyushu City, Japan," Tourism Management, Elsevier, vol. 55(C), pages 85-93.
    13. Maurici Ruiz-Pérez & Joana Maria Seguí-Pons, 2020. "Transport Mode Choice for Residents in a Tourist Destination: The Long Road to Sustainability (the Case of Mallorca, Spain)," Sustainability, MDPI, vol. 12(22), pages 1-31, November.
    14. Cao, Zheng & Li, Gang & Song, Haiyan, 2017. "Modelling the interdependence of tourism demand: The global vector autoregressive approach," Annals of Tourism Research, Elsevier, vol. 67(C), pages 1-13.
    15. Qingru Zou & Xiangming Yao & Peng Zhao & Heng Wei & Hui Ren, 2018. "Detecting home location and trip purposes for cardholders by mining smart card transaction data in Beijing subway," Transportation, Springer, vol. 45(3), pages 919-944, May.
    16. De Zhao & Wei Wang & Amber Woodburn & Megan S. Ryerson, 2017. "Isolating high-priority metro and feeder bus transfers using smart card data," Transportation, Springer, vol. 44(6), pages 1535-1554, November.
    17. Bursa, Bartosz & Mailer, Markus & Axhausen, Kay W., 2022. "Travel behavior on vacation: transport mode choice of tourists at destinations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 234-261.
    18. Paul Nailly & Etienne Côme & Latifa Oukhellou & Allou Samé & Jacques Ferriere & Yasmine Merad-Boudia, 2024. "Multivariate count time series segmentation with “sums and shares” and Poisson lognormal mixture models: a comparative study using pedestrian flows within a multimodal transport hub," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(2), pages 455-491, June.
    19. Ezza, Alberto & Marinò, Ludovico & Giovanelli, Lucia, 2019. "Assessing the impact of tourism on hospitals’ performance in a coastal destination," MPRA Paper 93999, University Library of Munich, Germany.
    20. Hamed Faroqi & Mahmoud Mesbah & Jiwon Kim & Ali Khodaii, 2022. "Targeted Advertising in the Public Transit Network Using Smart Card Data," Networks and Spatial Economics, Springer, vol. 22(1), pages 97-124, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jotrge:v:88:y:2020:i:c:s0966692320302283. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.