IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i19p14213-d1247911.html
   My bibliography  Save this article

Applying Data Analytics to Analyze Activity Sequences for an Assessment of Fragmentation in Daily Travel Patterns: A Case Study of the Metropolitan Region of Barcelona

Author

Listed:
  • Lídia Montero

    (Department of Statistics and Operations Reserach, Universitat Politècnica de Catalunya (UPC), C5 2nd Floor, Campus Nord, C\Jordi Girona, 1-3, 08034 Barcelona, Spain)

  • Lucía Mejía-Dorantes

    (Independent Researcher, 76185 Karlsruhe, Germany)

  • Jaume Barceló

    (Department of Statistics and Operations Reserach, Universitat Politècnica de Catalunya (UPC), C5 2nd Floor, Campus Nord, C\Jordi Girona, 1-3, 08034 Barcelona, Spain)

Abstract

Sequence analysis is a robust methodological approach that has gained popularity in various fields, including transportation research. It provides a comprehensive way to understand the dynamics and patterns of individual behaviors over time. In the context of the Metropolitan Region of Barcelona, applying sequence analysis to mobility surveys offers valuable insights into the sequencing of travel activities and modes, shedding light on the complex interrelationship between individuals and their travel choices and the built environment. Sequence analysis allows us to examine travel behaviors as dynamic processes and reveal the underlying structure and evolution of travel patterns over a day. Here, we describe a data analytics approach that enables the identification of common travel patterns and the exploration of variations across demographic groups or geographical regions. We propose a method for discovering similarities in travel behavior segments from diaries included in travel surveys in order to refine transport policies for selected segments. Unfortunately, the data collected by the authorities in the analyzed travel surveys do not include family structure, which seems critical in explaining the segmentation of travel sequences.

Suggested Citation

  • Lídia Montero & Lucía Mejía-Dorantes & Jaume Barceló, 2023. "Applying Data Analytics to Analyze Activity Sequences for an Assessment of Fragmentation in Daily Travel Patterns: A Case Study of the Metropolitan Region of Barcelona," Sustainability, MDPI, vol. 15(19), pages 1-22, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14213-:d:1247911
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/19/14213/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/19/14213/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ben-Elia, Eran & Alexander, Bayarma & Hubers, Christa & Ettema, Dick, 2014. "Activity fragmentation, ICT and travel: An exploratory Path Analysis of spatiotemporal interrelationships," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 56-74.
    2. Matthias Studer & Gilbert Ritschard, 2016. "What matters in differences between life trajectories: a comparative review of sequence dissimilarity measures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(2), pages 481-511, February.
    3. Cees H. Elzinga & Aart C. Liefbroer, 2007. "De-standardization of Family-Life Trajectories of Young Adults: A Cross-National Comparison Using Sequence Analysis," European Journal of Population, Springer;European Association for Population Studies, vol. 23(3), pages 225-250, October.
    4. Lê, Sébastien & Josse, Julie & Husson, François, 2008. "FactoMineR: An R Package for Multivariate Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i01).
    5. Bhat, Chandra R., 1996. "A hazard-based duration model of shopping activity with nonparametric baseline specification and nonparametric control for unobserved heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 189-207, June.
    6. Stopher, Peter R. & Greaves, Stephen P., 2007. "Household travel surveys: Where are we going?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 367-381, June.
    7. Christa Hubers & Tim Schwanen & Martin Dijst, 2008. "Ict And Temporal Fragmentation Of Activities: An Analytical Framework And Initial Empirical Findings," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 99(5), pages 528-546, December.
    8. Lucía Mejía-Dorantes & Lídia Montero & Jaume Barceló, 2021. "Mobility Trends before and after the Pandemic Outbreak: Analyzing the Metropolitan Area of Barcelona through the Lens of Equality and Sustainability," Sustainability, MDPI, vol. 13(14), pages 1-23, July.
    9. Martin Dijst & Velibor Vidakovic, 2000. "Travel time ratio: the key factor of spatial reach," Transportation, Springer, vol. 27(2), pages 179-199, May.
    10. Bhat, Chandra R., 1996. "A generalized multiple durations proportional hazard model with an application to activity behavior during the evening work-to-home commute," Transportation Research Part B: Methodological, Elsevier, vol. 30(6), pages 465-480, December.
    11. Chandra Bhat & Konstadinos Goulias & Ram Pendyala & Rajesh Paleti & Raghuprasad Sidharthan & Laura Schmitt & Hsi-Hwa Hu, 2013. "A household-level activity pattern generation model with an application for Southern California," Transportation, Springer, vol. 40(5), pages 1063-1086, September.
    Full references (including those not matched with items on IDEAS)

    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. Zidan Mao & Dick Ettema & Martin Dijst, 2018. "Analysis of travel time and mode choice shift for non-work stops in commuting: case study of Beijing, China," Transportation, Springer, vol. 45(3), pages 751-766, May.
    2. Shi, Hui & Su, Rongxiang & Xiao, Jingyi & Goulias, Konstadinos G., 2022. "Spatiotemporal analysis of activity-travel fragmentation based on spatial clustering and sequence analysis," Journal of Transport Geography, Elsevier, vol. 102(C).
    3. Marcel Raab & Emanuela Struffolino, 2020. "The Heterogeneity of Partnership Trajectories to Childlessness in Germany," European Journal of Population, Springer;European Association for Population Studies, vol. 36(1), pages 53-70, March.
    4. Devillanova, Carlo & Raitano, Michele & Struffolino, Emanuela, 2019. "Longitudinal employment trajectories and health in middle life: Insights from linked administrative and survey data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 1375-1412.
    5. Cees H. Elzinga & Matthias Studer, 2019. "Normalization of Distance and Similarity in Sequence Analysis," Sociological Methods & Research, , vol. 48(4), pages 877-904, November.
    6. Okka Zimmermann & Nicole Hameister, 2019. "Stable cohabitational unions increase quality of life: Retrospective analysis of partnership histories also reveals gender differences," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(24), pages 657-692.
    7. Arranz-López, Aldo & Soria-Lara, Julio A., 2022. "ICT use and spatial fragmentation of activity participation in post-COVID-19 urban societies," Land Use Policy, Elsevier, vol. 120(C).
    8. Bayarma Alexander & Martin Dijst, 2012. "Professional workers @ work: importance of work activities for electronic and face-to-face communications in the Netherlands," Transportation, Springer, vol. 39(5), pages 919-940, September.
    9. Zamani, Efpraxia D. & Spanaki, Konstantina, 2023. "Affective temporal experiences and new work modalities: The role of Information and Communication Technologies," Journal of Business Research, Elsevier, vol. 154(C).
    10. Tai-Yu Ma & Charles Raux & Eric Cornelis & Iragaël Joly, 2009. "multi-state non-homogeneous semi-markov model of daily activity type, timing and duration sequence," Post-Print halshs-00310900, HAL.
    11. Kharoufeh, Jeffrey P. & Goulias, Konstadinos G., 2002. "Nonparametric identification of daily activity durations using kernel density estimators," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 59-82, January.
    12. Lee, Backjin & Timmermans, Harry J.P., 2007. "A latent class accelerated hazard model of activity episode durations," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 426-447, May.
    13. Liao, Tim F. & Bolano, Danilo & Brzinsky-Fay, Christian & Cornwell, Benjamin & Fasang, Anette Eva & Helske, Satu & Piccarreta, Raffaella & Raab, Marcel & Ritschard, Gilbert & Struffolino, Emanuela & S, 2022. "Sequence analysis: Its past, present, and future," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 107, pages 1-1.
    14. Yamamoto, Toshiyuki & Madre, Jean-Loup & Kitamura, Ryuichi, 2004. "An analysis of the effects of French vehicle inspection program and grant for scrappage on household vehicle transaction," Transportation Research Part B: Methodological, Elsevier, vol. 38(10), pages 905-926, December.
    15. Timmermans, Harry & van der Waerden, Peter & Alves, Mario & Polak, John & Ellis, Scott & Harvey, Andrew S. & Kurose, Shigeyuki & Zandee, Rianne, 2002. "Time allocation in urban and transport settings: an international, inter-urban perspective," Transport Policy, Elsevier, vol. 9(2), pages 79-93, April.
    16. Andrade, Stefan B. & Fasang, Anette Eva & Helske, Satu & Karhula, Aleksi, 2023. "Typologies in Sequence Analysis: Practical Guidelines for Identifying Robust Cluster Solutions," SocArXiv kj8d5, Center for Open Science.
    17. Morten Wahrendorf & Anja Marr & Manfred Antoni & Beate Pesch & Karl-Heinz Jöckel & Thorsten Lunau & Susanne Moebus & Marina Arendt & Thomas Brüning & Thomas Behrens & Nico Dragano, 2019. "Agreement of Self-Reported and Administrative Data on Employment Histories in a German Cohort Study: A Sequence Analysis," European Journal of Population, Springer;European Association for Population Studies, vol. 35(2), pages 329-346, May.
    18. Jana Klimova Chaloupkova, 2023. "Solo living in the process of transitioning to adulthood in Europe: The role of socioeconomic background," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(3), pages 43-88.
    19. Yee, Julie L. & Niemeier, Debbie A., 2000. "Analysis of activity duration using the Puget sound transportation panel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(8), pages 607-624, November.
    20. Barbara Elisabeth Fulda, 2016. "The diversity in longitudinal partnership trajectories during the transition to adulthood: How is it related to individual characteristics and regional living conditions?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(37), pages 1101-1134.

    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:gam:jsusta:v:15:y:2023:i:19:p:14213-:d:1247911. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.