IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2308.04973.html
   My bibliography  Save this paper

The Mobilit\"at.Leben Study: a Year-Long Mobility-Tracking Panel

Author

Listed:
  • Allister Loder
  • Fabienne Cantner
  • Victoria Dahmen
  • Klaus Bogenberger

Abstract

The Mobilit\"at.Leben study investigated travel behavior effects of a natural experiment in Germany. In response to the 2022 cost-of-living crisis, two policy measures to reduce travel costs for the population in June, July, and August 2022 were introduced: a fuel excise tax cut and almost fare-free public transport with the so-called 9-Euro-Ticket. The announcement of a successor ticket to the 9-Euro-Ticket, the so-called Deutschlandticket, led to the immediate decision to continue the study. The Mobilit\"at.Leben study has two periods, the 9-Euro-Ticket period and the Deutschlandticket period, and comprises two elements: several questionnaires and a smartphone-based passive waypoint tracking. The entire duration of the study was almost thirteen months. In this paper, we report on the study design, the recruitment strategy, the study participation in the survey, and the tracking parts, and we share our experience in conducting such large-scale panel studies. Overall, 3,080 people registered for our study of which 1,420 decided to use the smartphone tracking app. While the relevant questionnaires in both phases have been completed by 818 participants, we have 170 study participants who completed the tracking in both phases and all relevant questionnaires. We find that providing a study compensation increases participation performance. It can be concluded that conducting year-long panel studies is possible, providing rich information on the heterogeneity in travel behavior between and within travelers.

Suggested Citation

  • Allister Loder & Fabienne Cantner & Victoria Dahmen & Klaus Bogenberger, 2023. "The Mobilit\"at.Leben Study: a Year-Long Mobility-Tracking Panel," Papers 2308.04973, arXiv.org.
  • Handle: RePEc:arx:papers:2308.04973
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2308.04973
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cinzia Cirillo & Kay Axhausen, 2010. "Dynamic model of activity-type choice and scheduling," Transportation, Springer, vol. 37(1), pages 15-38, January.
    2. Andreas Krämer & Gerd Wilger & Robert Bongaerts, 2022. "Das 9-Euro-Ticket: Erfahrungen, Wirkungsmechanismen und Nachfolgeangebot [The 9-Euro-Ticket: Experiences, Impact Mechanisms and Follow-Up]," Wirtschaftsdienst, Springer;ZBW - Leibniz Information Centre for Economics, vol. 102(11), pages 873-879, November.
    3. Peter Stopher & Camden FitzGerald & Min Xu, 2007. "Assessing the accuracy of the Sydney Household Travel Survey with GPS," Transportation, Springer, vol. 34(6), pages 723-741, November.
    4. Dennis Gaus & Neil Murray & Heike Link, 2023. "9-Euro-Ticket: Niedrigere Preise allein stärken Alltagsmobilität mit öffentlichen Verkehrsmitteln nicht," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 90(14/15), pages 163-171.
    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. Molloy, Joseph & Schatzmann, Thomas & Schoeman, Beaumont & Tchervenkov, Christopher & Hintermann, Beat & Axhausen, Kay W., 2021. "Observed impacts of the Covid-19 first wave on travel behaviour in Switzerland based on a large GPS panel," Transport Policy, Elsevier, vol. 104(C), pages 43-51.
    2. Chen, Cynthia & Gong, Hongmian & Lawson, Catherine & Bialostozky, Evan, 2010. "Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 830-840, December.
    3. Stopher, Peter & Clifford, Eoin & Swann, Natalie & Zhang, Yun, 2009. "Evaluating voluntary travel behaviour change: Suggested guidelines and case studies," Transport Policy, Elsevier, vol. 16(6), pages 315-324, November.
    4. Chen, Roger B., 2018. "Models of count with endogenous choices," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 862-875.
    5. Georges Sfeir & Filipe Rodrigues & Maya Abou Zeid & Francisco Camara Pereira, 2023. "Analyzing the Reporting Error of Public Transport Trips in the Danish National Travel Survey Using Smart Card Data," Papers 2308.01198, arXiv.org, revised Jul 2024.
    6. Rajesh Paleti & Rachel Copperman & Chandra Bhat, 2011. "An empirical analysis of children’s after school out-of-home activity-location engagement patterns and time allocation," Transportation, Springer, vol. 38(2), pages 273-303, March.
    7. Aschauer, Florian & Hössinger, Reinhard & Jara-Diaz, Sergio & Schmid, Basil & Axhausen, Kay & Gerike, Regine, 2021. "Comprehensive data validation of a combined weekly time use and travel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 66-82.
    8. Mars, Lidón & Arroyo, Rosa & Ruiz, Tomás, 2022. "Mobility and wellbeing during the covid-19 lockdown. Evidence from Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 107-129.
    9. Thomas, T. & Tutert, S.I.A., 2013. "An empirical model for trip distribution of commuters in The Netherlands: transferability in time and space reconsidered," Journal of Transport Geography, Elsevier, vol. 26(C), pages 158-165.
    10. Strömblad, Emma, 2024. "Identifying mobility segments for leisure travel: A cluster analysis based on a one-month travel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    11. Chenfeng Xiong & Lei Zhang, 2017. "Dynamic travel mode searching and switching analysis considering hidden model preference and behavioral decision processes," Transportation, Springer, vol. 44(3), pages 511-532, May.
    12. Chiara Calastri & Romain Crastes dit Sourd & Stephane Hess, 2020. "We want it all: experiences from a survey seeking to capture social network structures, lifetime events and short-term travel and activity planning," Transportation, Springer, vol. 47(1), pages 175-201, February.
    13. Andor, Mark Andreas & Dehos, Fabian & Gillingham, Kenneth & Hansteen, Sven & Tomberg, Lukas, 2023. "Public transport pricing: An evaluation of the 9-Euro Ticket and an alternative policy proposal," Ruhr Economic Papers 1045, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    14. Egu, Oscar & Bonnel, Patrick, 2020. "How comparable are origin-destination matrices estimated from automatic fare collection, origin-destination surveys and household travel survey? An empirical investigation in Lyon," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 267-282.
    15. Andrew Bwambale & Charisma F. Choudhury & Stephane Hess & Md. Shahadat Iqbal, 2021. "Getting the best of both worlds: a framework for combining disaggregate travel survey data and aggregate mobile phone data for trip generation modelling," Transportation, Springer, vol. 48(5), pages 2287-2314, October.
    16. Arentze, Theo A. & Ettema, Dick & Timmermans, Harry J.P., 2011. "Estimating a model of dynamic activity generation based on one-day observations: Method and results," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 447-460, February.
    17. Mofeng Yang & Yixuan Pan & Aref Darzi & Sepehr Ghader & Chenfeng Xiong & Lei Zhang, 2022. "A data-driven travel mode share estimation framework based on mobile device location data," Transportation, Springer, vol. 49(5), pages 1339-1383, October.
    18. Andreas Dypvik Landmark & Petter Arnesen & Carl-Johan Södersten & Odd André Hjelkrem, 2021. "Mobile phone data in transportation research: methods for benchmarking against other data sources," Transportation, Springer, vol. 48(5), pages 2883-2905, October.
    19. Habib, Khandker Nurul & Sasic, Ana & Weis, Claude & Axhausen, Kay, 2013. "Investigating the nonlinear relationship between transportation system performance and daily activity–travel scheduling behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 342-357.
    20. Guangnian Xiao & Qin Cheng & Chunqin Zhang, 2019. "Detecting travel modes from smartphone-based travel surveys with continuous hidden Markov models," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2308.04973. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.