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Exploring day-to-day variability in time use for household members

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  • Kang, Hejun
  • Scott, Darren M.

Abstract

Studies of activity-travel patterns typically use 1-day or pooled samples, and more often than not, are conducted at the individual level. By default, they assume that activity-travel decisions are uniform from 1 day to the next and individuals are independent from one another. Such assumptions do not reflect reality. This research investigates day-to-day variability in activity time-use patterns of household members while incorporating variations in their interactions. Results from a descriptive analysis and a series of daily structural equation models provide evidence of day-to-day variability in activity time-use patterns. Specifically, time-use patterns on weekdays are substantially different from those on weekends. Furthermore, compared to independent activities, there is a higher proportion of intra-personal variability and a lower proportion of inter-personal variability for joint activities. These findings suggest that transportation planners should not combine independent and joint activities as has been the case in the recent past, nor should they use single-day or pooled models when estimating activity time-use patterns.

Suggested Citation

  • Kang, Hejun & Scott, Darren M., 2010. "Exploring day-to-day variability in time use for household members," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(8), pages 609-619, October.
  • Handle: RePEc:eee:transa:v:44:y:2010:i:8:p:609-619
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Minnen, Joeri & Glorieux, Ignace & van Tienoven, Theun Pieter, 2015. "Transportation habits: Evidence from time diary data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 25-37.
    2. Yu Liu & Chaogui Kang & Song Gao & Yu Xiao & Yuan Tian, 2012. "Understanding intra-urban trip patterns from taxi trajectory data," Journal of Geographical Systems, Springer, vol. 14(4), pages 463-483, October.
    3. Charles Raux & Tai-Yu Ma & Eric Cornelis, 2016. "Variability in daily activity-travel patterns: the case of a one-week travel diary," Post-Print halshs-01389479, HAL.
    4. Dharmowijoyo, Dimas B.E. & Susilo, Yusak O. & Karlström, Anders & Adiredja, Lili Somantri, 2015. "Collecting a multi-dimensional three-weeks household time-use and activity diary in the Bandung Metropolitan Area, Indonesia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 231-246.
    5. Wang, Bobin & Shao, Chunfu & Ji, Xun, 2017. "Dynamic analysis of holiday travel behaviour with integrated multimodal travel information usage: A life-oriented approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 255-280.
    6. Horner, Mark & Downs, Joni, 2014. "Integrating people and place: A density-based measure for assessing accessibility to opportunities," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 7(2), pages 1-18.
    7. Meng Zhou & Donggen Wang, 2019. "Investigating inter-generational changes in activity-travel behavior: a disaggregate approach," Transportation, Springer, vol. 46(5), pages 1643-1687, October.
    8. Lin, Tao & Wang, Donggen & Zhou, Meng, 2018. "Residential relocation and changes in travel behavior: what is the role of social context change?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 360-374.
    9. Allahviranloo, Mahdieh & Axhausen, Kay, 2018. "An optimization model to measure utility of joint and solo activities," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 172-187.
    10. 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.
    11. Walker, Joan L. & Ehlers, Emily & Banerjee, Ipsita & Dugundji, Elenna R., 2011. "Correcting for endogeneity in behavioral choice models with social influence variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 362-374, May.
    12. Dharmowijoyo, Dimas B.E. & Susilo, Yusak O. & Karlström, Anders, 2016. "Relationships among discretionary activity duration, its travel time spent and activity space indices in the Jakarta Metropolitan Area, Indonesia," Journal of Transport Geography, Elsevier, vol. 54(C), pages 148-160.
    13. Shen, Yue & Kwan, Mei-Po & Chai, Yanwei, 2013. "Investigating commuting flexibility with GPS data and 3D geovisualization: a case study of Beijing, China," Journal of Transport Geography, Elsevier, vol. 32(C), pages 1-11.
    14. 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.
    15. Wilson, Jeffrey & Spinney, Jamie & Millward, Hugh & Scott, Darren & Hayden, Anders & Tyedmers, Peter, 2013. "Blame the exurbs, not the suburbs: Exploring the distribution of greenhouse gas emissions within a city region," Energy Policy, Elsevier, vol. 62(C), pages 1329-1335.
    16. 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.
    17. Wang, Donggen & Cao, Xinyu, 2017. "Impacts of the built environment on activity-travel behavior: Are there differences between public and private housing residents in Hong Kong?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 25-35.
    18. Gerike, Regine & Gehlert, Tina & Leisch, Friedrich, 2015. "Time use in travel surveys and time use surveys – Two sides of the same coin?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 4-24.

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