IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v44y2017i4d10.1007_s11116-016-9732-4.html
   My bibliography  Save this article

The San Francisco Travel Quality Study: tracking trials and tribulations of a transit taker

Author

Listed:
  • Andre Carrel

    (University of California, Berkeley)

  • Raja Sengupta

    (University of California, Berkeley)

  • Joan L. Walker

    (University of California, Berkeley)

Abstract

In helping understand the dynamics of travel choice behavior and traveler satisfaction over time, multi-day panel data is invaluable (McFadden in Am Econ Rev 91(3): 351–378, 2001). The collection of such data has become increasingly feasible thanks to smartphones, which researchers can use to present surveys to travelers and to collect additional information through the phones’ location services and other sensors. This paper describes the design and implementation of the San Francisco Travel Quality Study, a multi-day research study conducted in autumn 2013 with 838 participants. The objective of the study was to investigate the link between transit service quality, the satisfaction and subjective well-being of transit riders, and travel choice behavior, with a particular interest in the influence of travelers’ choice history and personal experiences on future transit use. For that purpose, a rich panel data set was collected from multiple sources, including a number of mobile travel experience surveys capturing traveler satisfaction and emotions, two online surveys capturing demographics, attitudes and mode choice intentions, as well as high-resolution phone location data and transit vehicle location data. By fusing the phone location data with transit vehicle location data, individual-level transit travel diaries could be automatically created, and by fusing the location data with the survey responses, additional information about the context of the responses could be derived. While the behavioral and satisfaction-related findings of the study are detailed in other publications, this paper is intended to serve two purposes. First, it describes the study design, data collection effort and challenges faced in order to provide a learning opportunity for other researchers considering similar studies. Second, it discusses the key sociodemographic data and characteristics of the study population in order to provide a foundation and reference for further publications that make use of the data set described here. The authors would like to invite other researchers to collaborate with them on the evaluation of the data.

Suggested Citation

  • Andre Carrel & Raja Sengupta & Joan L. Walker, 2017. "The San Francisco Travel Quality Study: tracking trials and tribulations of a transit taker," Transportation, Springer, vol. 44(4), pages 643-679, July.
  • Handle: RePEc:kap:transp:v:44:y:2017:i:4:d:10.1007_s11116-016-9732-4
    DOI: 10.1007/s11116-016-9732-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-016-9732-4
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11116-016-9732-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. Laros, Fleur J.M. & Steenkamp, Jan-Benedict E.M., 2005. "Emotions in consumer behavior: a hierarchical approach," Journal of Business Research, Elsevier, vol. 58(10), pages 1437-1445, October.
    3. Sharmeen, Fariya & Arentze, Theo & Timmermans, Harry, 2014. "An analysis of the dynamics of activity and travel needs in response to social network evolution and life-cycle events: A structural equation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 159-171.
    4. Brendan Pender & Graham Currie & Alexa Delbosc & Nirajan Shiwakoti, 2014. "Social Media Use during Unplanned Transit Network Disruptions: A Review of Literature," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 501-521, July.
    5. Kay Axhausen & Andrea Zimmermann & Stefan Schönfelder & Guido Rindsfüser & Thomas Haupt, 2002. "Observing the rhythms of daily life: A six-week travel diary," Transportation, Springer, vol. 29(2), pages 95-124, May.
    6. Andrew Mondschein, 2015. "Five-star transportation: using online activity reviews to examine mode choice to non-work destinations," Transportation, Springer, vol. 42(4), pages 707-722, July.
    7. Pedersen, Tore & Friman, Margareta & Kristensson, Per, 2011. "The role of predicted, on-line experienced and remembered satisfaction in current choice to use public transport services," Journal of Retailing and Consumer Services, Elsevier, vol. 18(5), pages 471-475.
    8. 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.
    9. Ettema, Dick & Gärling, Tommy & Olsson, Lars E. & Friman, Margareta, 2010. "Out-of-home activities, daily travel, and subjective well-being," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 723-732, November.
    10. Stradling, Stephen & Carreno, Michael & Rye, Tom & Noble, Allyson, 2007. "Passenger perceptions and the ideal urban bus journey experience," Transport Policy, Elsevier, vol. 14(4), pages 283-292, July.
    11. 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.
    12. Ruth N. Bolton, 1998. "A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction," Marketing Science, INFORMS, vol. 17(1), pages 45-65.
    13. Eboli, Laura & Mazzulla, Gabriella, 2011. "A methodology for evaluating transit service quality based on subjective and objective measures from the passenger's point of view," Transport Policy, Elsevier, vol. 18(1), pages 172-181, January.
    14. Scheiner, Joachim & Holz-Rau, Christian, 2013. "A comprehensive study of life course, cohort, and period effects on changes in travel mode use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 47(C), pages 167-181.
    15. Vij, Akshay, 2013. "Incorporating the Influence of Latent Modal Preferences in Travel Demand Models," University of California Transportation Center, Working Papers qt7nq9p0cv, University of California Transportation Center.
    16. Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
    17. Satoshi Fujii & Ryuichi Kitamura, 2003. "What does a one-month free bus ticket do to habitual drivers? An experimental analysis of habit and attitude change," Transportation, Springer, vol. 30(1), pages 81-95, February.
    18. Robert Schlich & Kay Axhausen, 2003. "Habitual travel behaviour: Evidence from a six-week travel diary," Transportation, Springer, vol. 30(1), pages 13-36, February.
    19. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    20. Vij, Akshay, 2013. "Incorporating the Influence of Latent Modal Preferences in Travel Demand Models," University of California Transportation Center, Working Papers qt7ng2z24q, University of California Transportation Center.
    21. Richins, Marsha L, 1997. "Measuring Emotions in the Consumption Experience," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 24(2), pages 127-146, September.
    22. Lisa Schweitzer, 2014. "Planning and Social Media: A Case Study of Public Transit and Stigma on Twitter," Journal of the American Planning Association, Taylor & Francis Journals, vol. 80(3), pages 218-238, July.
    23. Vij, Akshay & Carrel, André & Walker, Joan L., 2013. "Incorporating the influence of latent modal preferences on travel mode choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 164-178.
    24. Oliver, Richard L, 1993. "Cognitive, Affective, and Attribute BAses of the Satisfaction Response," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(3), pages 418-430, December.
    25. Chenfeng Xiong & Xiqun Chen & Xiang He & Wei Guo & Lei Zhang, 2015. "The analysis of dynamic travel mode choice: a heterogeneous hidden Markov approach," Transportation, Springer, vol. 42(6), pages 985-1002, November.
    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. Brathwaite, Timothy & Walker, Joan L., 2018. "Causal inference in travel demand modeling (and the lack thereof)," Journal of choice modelling, Elsevier, vol. 26(C), pages 1-18.
    2. Melinda Matyas & Maria Kamargianni, 2019. "Survey design for exploring demand for Mobility as a Service plans," Transportation, Springer, vol. 46(5), pages 1525-1558, October.
    3. Huyen T. K. Le & Andre L. Carrel, 2021. "Happy today, satisfied tomorrow: emotion—satisfaction dynamics in a multi-week transit user smartphone survey," Transportation, Springer, vol. 48(1), pages 45-66, February.

    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. Cherchi, Elisabetta & Cirillo, Cinzia & Ortúzar, Juan de Dios, 2017. "Modelling correlation patterns in mode choice models estimated on multiday travel data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 146-153.
    2. La Paix Puello, Lissy & Chowdhury, Saidul & Geurs, Karst, 2019. "Using panel data for modelling duration dynamics of outdoor leisure activities," Journal of choice modelling, Elsevier, vol. 31(C), pages 141-155.
    3. Heinen, Eva & Chatterjee, Kiron, 2015. "The same mode again? An exploration of mode choice variability in Great Britain using the National Travel Survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 266-282.
    4. Ittamalla, Rajesh & Srinivas Kumar, Daruri Venkata, 2021. "Determinants of holistic passenger experience in public transportation: Scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    5. Yongsung Lee & Giovanni Circella & Patricia L. Mokhtarian & Subhrajit Guhathakurta, 2020. "Are millennials more multimodal? A latent-class cluster analysis with attitudes and preferences among millennial and Generation X commuters in California," Transportation, Springer, vol. 47(5), pages 2505-2528, October.
    6. Timmer, Sebastian & Merfeld, Katrin & Henkel, Sven, 2023. "Exploring motivations for multimodal commuting: A hierarchical means-end chain analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    7. Julia Janke & Calvin G. Thigpen & Susan Handy, 2021. "Examining the effect of life course events on modality type and the moderating influence of life stage," Transportation, Springer, vol. 48(2), pages 1089-1124, April.
    8. Carreira, Rui & Patrício, Lia & Natal Jorge, Renato & Magee, Chris, 2014. "Understanding the travel experience and its impact on attitudes, emotions and loyalty towards the transportation provider–A quantitative study with mid-distance bus trips," Transport Policy, Elsevier, vol. 31(C), pages 35-46.
    9. Carreira, Rui & Patrício, Lia & Natal Jorge, Renato & Magee, Chris & Van Eikema Hommes, Qi, 2013. "Towards a holistic approach to the travel experience: A qualitative study of bus transportation," Transport Policy, Elsevier, vol. 25(C), pages 233-243.
    10. 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.
    11. Siyu Li & Der-Horng Lee, 2017. "Learning daily activity patterns with probabilistic grammars," Transportation, Springer, vol. 44(1), pages 49-68, January.
    12. Ali Ardeshiri & Akshay Vij, 2019. "A lifestyle-based model of household neighbourhood location and individual travel mode choice behaviours," Papers 1902.01986, arXiv.org, revised Nov 2019.
    13. Sfeir, Georges & Abou-Zeid, Maya & Rodrigues, Filipe & Pereira, Francisco Camara & Kaysi, Isam, 2021. "Latent class choice model with a flexible class membership component: A mixture model approach," Journal of choice modelling, Elsevier, vol. 41(C).
    14. Rico Krueger & Akshay Vij & Taha H. Rashidi, 2018. "Normative beliefs and modality styles: a latent class and latent variable model of travel behaviour," Transportation, Springer, vol. 45(3), pages 789-825, May.
    15. Sfeir, Georges & Abou-Zeid, Maya & Kaysi, Isam, 2020. "Multivariate count data models for adoption of new transport modes in an organization-based context," Transport Policy, Elsevier, vol. 91(C), pages 59-75.
    16. repec:ipg:wpaper:2014-416 is not listed on IDEAS
    17. Chenfeng Xiong & Di Yang & Jiaqi Ma & Xiqun Chen & Lei Zhang, 2020. "Measuring and enhancing the transferability of hidden Markov models for dynamic travel behavioral analysis," Transportation, Springer, vol. 47(2), pages 585-605, April.
    18. Molin, Eric & Mokhtarian, Patricia & Kroesen, Maarten, 2016. "Multimodal travel groups and attitudes: A latent class cluster analysis of Dutch travelers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 14-29.
    19. Ardeshiri, Ali & Vij, Akshay, 2019. "Lifestyles, residential location, and transport mode use: A hierarchical latent class choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 342-359.
    20. Alemi, Farzad & Circella, Giovanni & Mokhtarian, Patricia & Handy, Susan, 2018. "Exploring the latent constructs behind the use of ridehailing in California," Journal of choice modelling, Elsevier, vol. 29(C), pages 47-62.
    21. Sarker, Rumana Islam & Kaplan, Sigal & Mailer, Markus & Timmermans, Harry J.P., 2019. "Applying affective event theory to explain transit users’ reactions to service disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 593-605.

    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:kap:transp:v:44:y:2017:i:4:d:10.1007_s11116-016-9732-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.