IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v147y2021icp106-132.html
   My bibliography  Save this article

Unveiling daily activity pattern differences between telecommuters and commuters using human mobility motifs and sequence analysis

Author

Listed:
  • Su, Rongxiang
  • McBride, Elizabeth C.
  • Goulias, Konstadinos G.

Abstract

This paper demonstrates the use of motif and sequence analysis in tandem to analyse differences and commonalities between telecommuters and usual commuters. In terms of substantive findings, telecommuters are by far more diverse in their allocation of time to places, activities, and travel. Approximately 20% of telecommuters stay at home all day during a workday, while only 8% of commuters do. Telecommuters that have at least one trip during their workday accrue more vehicle miles travelled and number of trips than their commuter counterparts. However, they travel less driving alone and tend to have more complex schedules visiting more locations. Within telecommuters and commuters, however, we have substantial variation in activity participation and travel captured by the combination of motifs and sequence analysis. As expected, a substantial proportion of commuters display morning and afternoon peaks of arriving at and departing from work, and telecommuters do not show this pattern. In addition, telecommuters do not only perform work tasks from home. Instead, during a day a high percentage travel to a variety of locations to either visit customers and/or use their spatio-temporal schedule flexibility to perform work tasks from locations other than home. In contrast, more than 80% of commuters perform work at their workplace. In addition, a slightly higher proportion of telecommuters function as the designated driver escorting other people to their activity locations.

Suggested Citation

  • Su, Rongxiang & McBride, Elizabeth C. & Goulias, Konstadinos G., 2021. "Unveiling daily activity pattern differences between telecommuters and commuters using human mobility motifs and sequence analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 106-132.
  • Handle: RePEc:eee:transa:v:147:y:2021:i:c:p:106-132
    DOI: 10.1016/j.tra.2021.03.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856421000574
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2021.03.002?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. Mokhtarian, Patricia L. & Handy, Susan L. & Salomon, Ilan, 1995. "Methodological issues in the estimation of the travel, energy, and air quality impacts of telecommuting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 29(4), pages 283-302, July.
    2. Chang-Hyeon Joh & Theo A Arentze & Harry J P Timmermans, 2001. "A Position-Sensitive Sequence-Alignment Method Illustrated for Space–Time Activity-Diary Data," Environment and Planning A, , vol. 33(2), pages 313-338, February.
    3. Mokhtarian, Patricia L, 1991. "Defining Telecommuting," Institute of Transportation Studies, Working Paper Series qt35c4q71r, Institute of Transportation Studies, UC Davis.
    4. Patricia L Mokhtarian & Gustavo O Collantes & Carsten Gertz, 2004. "Telecommuting, Residential Location, and Commute-Distance Traveled: Evidence from State of California Employees," Environment and Planning A, , vol. 36(10), pages 1877-1897, October.
    5. Kitamura, Ryuichi & Nilles, Jack M. & Conroy, Patrick & Fleming, David M., 1990. "Telecommuting as a Transportation Planning Meaure: Initial Results of California Pilot Project," University of California Transportation Center, Working Papers qt6j96d49k, University of California Transportation Center.
    6. Gimenez-Nadal, José Ignacio & Molina, José Alberto & Velilla, Jorge, 2018. "Telework, the Timing of Work, and Instantaneous Well-Being: Evidence from Time Use Data," IZA Discussion Papers 11271, Institute of Labor Economics (IZA).
    7. Pengyu Zhu & Liping Wang & Yanpeng Jiang & Jiangping Zhou, 2018. "Metropolitan size and the impacts of telecommuting on personal travel," Transportation, Springer, vol. 45(2), pages 385-414, March.
    8. Jinzhou Cao & Qingquan Li & Wei Tu & Feilong Wang, 2019. "Characterizing preferred motif choices and distance impacts," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-17, April.
    9. Gabadinho, Alexis & Ritschard, Gilbert & Müller, Nicolas S & Studer, Matthias, 2011. "Analyzing and Visualizing State Sequences in R with TraMineR," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i04).
    10. Martin Dijst & Velibor Vidakovic, 2000. "Travel time ratio: the key factor of spatial reach," Transportation, Springer, vol. 27(2), pages 179-199, 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. Shi, Shuyang & Wang, Lin & Wang, Xiaofan, 2022. "Uncovering the spatiotemporal motif patterns in urban mobility networks by non-negative tensor decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    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. Konstantinos Christopoulos & Konstantinos Eleftheriou & Peter Nijkamp, 2022. "The role of pre-pandemic teleworking and E-commerce culture in the COVID-19 dispersion in Europe," Letters in Spatial and Resource Sciences, Springer, vol. 15(1), pages 1-16, April.
    4. Rafiq, Rezwana & McNally, Michael G. & Sarwar Uddin, Yusuf & Ahmed, Tanjeeb, 2022. "Impact of working from home on activity-travel behavior during the COVID-19 Pandemic: An aggregate structural analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 35-54.
    5. Nicholas S. Caros & Jinhua Zhao, 2022. "Preparing urban mobility for the future of work," Papers 2201.01321, arXiv.org.
    6. Wang, Xize & Renne, John L., 2023. "Socioeconomics of Urban Travel in the U.S.: Evidence from the 2017 NHTS," SocArXiv cdw2y, Center for Open Science.
    7. Marc-Edouard Schultheiss, 2022. "Assessment of the Bus Transit Network: A Perspective from the Daily Activity-Travel Organization of Travelers," Sustainability, MDPI, vol. 14(4), pages 1-20, February.
    8. Somayeh Dodge & Trisalyn A. Nelson, 2023. "A framework for modern time geography: emphasizing diverse constraints on accessibility," Journal of Geographical Systems, Springer, vol. 25(3), pages 357-375, July.
    9. Asmussen, Katherine E. & Mondal, Aupal & Bhat, Chandra R. & Pendyala, Ram M., 2023. "On modeling future workplace location decisions: An analysis of Texas employees," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    10. Rongxiang Su & Somayeh Dodge & Konstadinos G. Goulias, 2022. "Understanding the impact of temporal scale on human movement analytics," Journal of Geographical Systems, Springer, vol. 24(3), pages 353-388, July.
    11. Xize Wang & John L. Renne, 2023. "Socioeconomics of Urban Travel in the U.S.: Evidence from the 2017 NHTS," Papers 2303.04812, arXiv.org.
    12. Su, Rongxiang & Goulias, Konstadinos, 2023. "Untangling the relationships among residential environment, destination choice, and daily walk accessibility," Journal of Transport Geography, Elsevier, vol. 109(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. Andrew Hook & Victor Court & Benjamin K Sovacool & Steven Sorrell, 2020. "A Systematic Review of the Energy and Climate Impacts of Teleworking," Working Papers hal-03192905, HAL.
    2. Pengyu Zhu, 2013. "Telecommuting, Household Commute and Location Choice," Urban Studies, Urban Studies Journal Limited, vol. 50(12), pages 2441-2459, September.
    3. Ozbilen, Basar & Wang, Kailai & Akar, Gulsah, 2021. "Revisiting the impacts of virtual mobility on travel behavior: An exploration of daily travel time expenditures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 49-62.
    4. Choo, Sangho, 2003. "Aggregate Relationships between Telecommunications and Travel: Structural Equation Modeling of Time Series Data," University of California Transportation Center, Working Papers qt4p78h623, University of California Transportation Center.
    5. Beck, Matthew J. & Hensher, David A., 2022. "Working from home in Australia in 2020: Positives, negatives and the potential for future benefits to transport and society," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 271-284.
    6. Georges A. Tanguay & Ugo Lachapelle, 2019. "Potential Impacts of Telecommuting on Transportation Behaviours, Health and Hours Worked in Québec," CIRANO Project Reports 2019rp-07, CIRANO.
    7. Pengyu Zhu & Liping Wang & Yanpeng Jiang & Jiangping Zhou, 2018. "Metropolitan size and the impacts of telecommuting on personal travel," Transportation, Springer, vol. 45(2), pages 385-414, March.
    8. Rafiq, Rezwana & McNally, Michael G. & Sarwar Uddin, Yusuf & Ahmed, Tanjeeb, 2022. "Impact of working from home on activity-travel behavior during the COVID-19 Pandemic: An aggregate structural analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 35-54.
    9. Balbontin, Camila & Hensher, David A. & Beck, Matthew J., 2024. "The influence of working from home and underlying attitudes on the number of commuting and non-commuting trips by workers during 2020 and 2021 pre- and post-lockdown in Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    10. Patricia L. Mokhtarian, 1998. "A Synthetic Approach to Estimating the Impacts of Telecommuting on Travel," Urban Studies, Urban Studies Journal Limited, vol. 35(2), pages 215-241, February.
    11. Ory, D T & Mokhtarian, Patricia L, 2005. "The Impact of Telecommuting on the Commute Time, Distance, and Speed of State of California Workers," Institute of Transportation Studies, Working Paper Series qt1fz1b5nz, Institute of Transportation Studies, UC Davis.
    12. Beck, Matthew J. & Hensher, David A. & Wei, Edward, 2020. "Slowly coming out of COVID-19 restrictions in Australia: Implications for working from home and commuting trips by car and public transport," Journal of Transport Geography, Elsevier, vol. 88(C).
    13. Minh Hieu Nguyen, 2021. "Factors influencing home-based telework in Hanoi (Vietnam) during and after the COVID-19 era," Transportation, Springer, vol. 48(6), pages 3207-3238, December.
    14. Hensher, David A. & Beck, Matthew J. & Wei, Edward, 2021. "Working from home and its implications for strategic transport modelling based on the early days of the COVID-19 pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 64-78.
    15. Pengyu Zhu, 2012. "Are telecommuting and personal travel complements or substitutes?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(2), pages 619-639, April.
    16. de Abreu e Silva, João & Melo, Patrícia C., 2018. "Does home-based telework reduce household total travel? A path analysis using single and two worker British households," Journal of Transport Geography, Elsevier, vol. 73(C), pages 148-162.
    17. Wöhner, Fabienne, 2022. "Work flexibly, travel less? The impact of telework and flextime on mobility behavior in Switzerland," Journal of Transport Geography, Elsevier, vol. 102(C).
    18. Su, Rongxiang & Xiao, Jingyi & McBride, Elizabeth C. & Goulias, Konstadinos G., 2021. "Understanding senior's daily mobility patterns in California using human mobility motifs," Journal of Transport Geography, Elsevier, vol. 94(C).
    19. Patricia L Mokhtarian & Gustavo O Collantes & Carsten Gertz, 2004. "Telecommuting, Residential Location, and Commute-Distance Traveled: Evidence from State of California Employees," Environment and Planning A, , vol. 36(10), pages 1877-1897, October.
    20. Kim, Seung-Nam & Choo, Sangho & Mokhtarian, Patricia L., 2015. "Home-based telecommuting and intra-household interactions in work and non-work travel: A seemingly unrelated censored regression approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 197-214.

    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:transa:v:147:y:2021:i:c:p:106-132. 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: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    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.