IDEAS home Printed from https://ideas.repec.org/a/sae/envira/v16y1984i5p571-581.html
   My bibliography  Save this article

The Effect of Selected Sociodemographic Characteristics on Daily Travel-Activity Behavior

Author

Listed:
  • E I Pas

    (Department of Civil and Environmental Engineering, Duke University, Durham, NC 27706, USA)

Abstract

The hypothesis that daily travel-activity behavior is influenced by the role, life-cycle, and life-style attributes of individuals and households is examined. Daily travel-activity behavior is described by a five-state categorical variable which is defined by analytical classification of a sample of daily travel-activity patterns. The explanatory variables used in this study are age, marital status, gender, employment status, education level, presence of young children, auto-ownership, income, and residential density. Parametric maximum likelihood models of multiway contingency tables are used to test the hypothesized relationships. The statistical analyses confirm that personal daily travel-activity behavior is significantly influenced by the role, life-cycle, and life-style characteristics of individuals and their households. The statistical results also demonstrate that specific sociodemographically defined segments of the urban travel market have differential likelihoods of undertaking particular daily travel-activity patterns.

Suggested Citation

  • E I Pas, 1984. "The Effect of Selected Sociodemographic Characteristics on Daily Travel-Activity Behavior," Environment and Planning A, , vol. 16(5), pages 571-581, May.
  • Handle: RePEc:sae:envira:v:16:y:1984:i:5:p:571-581
    DOI: 10.1068/a160571
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/a160571
    Download Restriction: no

    File URL: https://libkey.io/10.1068/a160571?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. Eric I. Pas, 1983. "A Flexible and Integrated Methodology for Analytical Classification of Daily Travel-Activity Behavior," Transportation Science, INFORMS, vol. 17(4), pages 405-429, 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. Golob, Thomas F., 1999. "A Simultaneous Model of Household Activity Participation and Trip Chain Generation," University of California Transportation Center, Working Papers qt0w16g0x2, University of California Transportation Center.
    2. Joh, Chang-Hyeon & Arentze, Theo & Hofman, Frank & Timmermans, Harry, 2002. "Activity pattern similarity: a multidimensional sequence alignment method," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 385-403, June.
    3. Ryuichi Kitamura, 2009. "Life-style and travel demand," Transportation, Springer, vol. 36(6), pages 679-710, November.
    4. Veronique Van Acker & Frank Witlox, 2005. "Exploring the relationship between land-use system and travel behaviour - some first findings," ERSA conference papers ersa05p601, European Regional Science Association.
    5. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    6. Zhai, Wei & Bai, Xueyin & Peng, Zhong-ren & Gu, Chaolin, 2019. "From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region," Journal of Transport Geography, Elsevier, vol. 78(C), pages 41-55.
    7. Pitombo, C.S. & Kawamoto, E. & Sousa, A.J., 2011. "An exploratory analysis of relationships between socioeconomic, land use, activity participation variables and travel patterns," Transport Policy, Elsevier, vol. 18(2), pages 347-357, March.
    8. Golob, Thomas F., 1996. "A Model of Household Demand for Activity Participation and Mobility," University of California Transportation Center, Working Papers qt00g9770f, University of California Transportation Center.
    9. Golob, Thomas F. & Bradley, Mark A. & Polak, John W., 1995. "Travel and Activity Participation as Influenced by Car Availability and Use," University of California Transportation Center, Working Papers qt9jt3t8v1, University of California Transportation Center.
    10. Golob, Thomas F., 2000. "A simultaneous model of household activity participation and trip chain generation," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 355-376, June.
    11. Alexander, Bayarma & Ettema, Dick & Dijst, Martin, 2010. "Fragmentation of work activity as a multi-dimensional construct and its association with ICT, employment and sociodemographic characteristics," Journal of Transport Geography, Elsevier, vol. 18(1), pages 55-64.
    12. Golob, Thomas F., 1999. "A Simultaneous Model of Household Activity Participation and Trip Chain Generation," University of California Transportation Center, Working Papers qt6xc704kp, University of California Transportation Center.
    13. Jinhyun Hong & Qing Shen & Lei Zhang, 2014. "How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales," Transportation, Springer, vol. 41(3), pages 419-440, May.
    14. Michael Smart, 2015. "A nationwide look at the immigrant neighborhood effect on travel mode choice," Transportation, Springer, vol. 42(1), pages 189-209, January.
    15. van Wissen, Leo J., 1991. "A Model of Household Interactions In Activity Patterns," University of California Transportation Center, Working Papers qt46q1c44f, University of California Transportation Center.
    16. Golob, Thomas F. & McNally, Michael G., 1997. "A model of activity participation and travel interactions between household heads," Transportation Research Part B: Methodological, Elsevier, vol. 31(3), pages 177-194, June.
    17. Bhat, Chandra R., 1997. "Work travel mode choice and number of non-work commute stops," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 41-54, February.
    18. Vij, Akshay & Gorripaty, Sreeta & Walker, Joan L., 2017. "From trend spotting to trend ’splaining: Understanding modal preference shifts in the San Francisco Bay Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 238-258.
    19. Siyu Li & Der-Horng Lee, 2017. "Learning daily activity patterns with probabilistic grammars," Transportation, Springer, vol. 44(1), pages 49-68, January.
    20. Kevin Krizek, 2003. "Neighborhood services, trip purpose, and tour-based travel," Transportation, Springer, vol. 30(4), pages 387-410, November.
    21. Goran Vuk & John L. Bowman & Andrew Daly & Stephane Hess, 2016. "Impact of family in-home quality time on person travel demand," Transportation, Springer, vol. 43(4), pages 705-724, July.
    22. van Wissen, Leo J., 1991. "A Model of Household Interactions In Activity Patterns," University of California Transportation Center, Working Papers qt4zw8s901, University of California Transportation Center.

    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. Zhai, Wei & Bai, Xueyin & Peng, Zhong-ren & Gu, Chaolin, 2019. "From edit distance to augmented space-time-weighted edit distance: Detecting and clustering patterns of human activities in Puget Sound region," Journal of Transport Geography, Elsevier, vol. 78(C), pages 41-55.
    2. Marlies Vanhulsel & Carolien Beckx & Davy Janssens & Koen Vanhoof & Geert Wets, 2011. "Measuring dissimilarity of geographically dispersed space–time paths," Transportation, Springer, vol. 38(1), pages 65-79, January.
    3. Dharmowijoyo, Dimas B.E. & Susilo, Yusak O. & Karlström, Anders, 2017. "Analysing the complexity of day-to-day individual activity-travel patterns using a multidimensional sequence alignment model: A case study in the Bandung Metropolitan Area, Indonesia," Journal of Transport Geography, Elsevier, vol. 64(C), pages 1-12.
    4. Joh, Chang-Hyeon & Arentze, Theo A. & Timmermans, Harry J. P., 1999. "Multidimensional Sequence Alignment Methods for Activity Pattern Analysis: A comparison of dynamic programming and genetic algorithms," ERSA conference papers ersa99pa279, European Regional Science Association.
    5. Erika Spissu & Abdul Pinjari & Chandra Bhat & Ram Pendyala & Kay Axhausen, 2009. "An analysis of weekly out-of-home discretionary activity participation and time-use behavior," Transportation, Springer, vol. 36(5), pages 483-510, September.
    6. Ciscal-Terry, Wilner & Dell'Amico, Mauro & Hadjidimitriou, Natalia Selini & Iori, Manuel, 2016. "An analysis of drivers route choice behaviour using GPS data and optimal alternatives," Journal of Transport Geography, Elsevier, vol. 51(C), pages 119-129.
    7. Elisabetta Cherchi & Cinzia Cirillo, 2014. "Understanding variability, habit and the effect of long period activity plan in modal choices: a day to day, week to week analysis on panel data," Transportation, Springer, vol. 41(6), pages 1245-1262, November.
    8. Morency, Catherine & Trépanier, Martin & Agard, Bruno, 2007. "Measuring transit use variability with smart-card data," Transport Policy, Elsevier, vol. 14(3), pages 193-203, May.
    9. Bhat, Chandra R. & Frusti, Teresa & Zhao, Huimin & Schönfelder, Stefan & Axhausen, Kay W., 2004. "Intershopping duration: an analysis using multiweek data," Transportation Research Part B: Methodological, Elsevier, vol. 38(1), pages 39-60, January.
    10. Joh, Chang-Hyeon & Arentze, Theo & Hofman, Frank & Timmermans, Harry, 2002. "Activity pattern similarity: a multidimensional sequence alignment method," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 385-403, June.
    11. Ron Buliung & Matthew Roorda & Tarmo Remmel, 2008. "Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto Travel-Activity Panel Survey (TTAPS)," Transportation, Springer, vol. 35(6), pages 697-722, November.
    12. Neutens, Tijs & Delafontaine, Matthias & Scott, Darren M. & De Maeyer, Philippe, 2012. "An analysis of day-to-day variations in individual space–time accessibility," Journal of Transport Geography, Elsevier, vol. 23(C), pages 81-91.
    13. Siyu Li & Der-Horng Lee, 2017. "Learning daily activity patterns with probabilistic grammars," Transportation, Springer, vol. 44(1), pages 49-68, January.
    14. D G Janelle & M F Goodchild & B Klinkenberg, 1988. "Space-Time Diaries and Travel Characteristics for Different Levels of Respondent Aggregation," Environment and Planning A, , vol. 20(7), pages 891-906, July.
    15. Jara-Díaz, Sergio & Rosales-Salas, Jorge, 2015. "Understanding time use: Daily or weekly data?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 38-57.
    16. 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.
    17. Rafiq, Rezwana & McNally, Michael G., 2021. "Heterogeneity in Activity-travel Patterns of Public Transit Users: An Application of Latent Class Analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 1-18.

    More about this item

    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:sae:envira:v:16:y:1984:i:5:p:571-581. 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: SAGE Publications (email available below). General contact details of provider: .

    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.