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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

Author

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  • Balbontin, Camila
  • Hensher, David A.
  • Beck, Matthew J.

Abstract

Since the start of 2020, we have seen major changes in the way communities operate. Mobility behaviour has been drastically impacted by work from home (WFH) and by lockdowns and restrictions in different jurisdictions. This study investigates the influence of WFH and different lockdown patterns on commuting and non-commuting trips in Australia by workers between early 2020 and late 2021. The data includes three waves of data collection to represent different lockdown periods. A multiple discrete–continuous extreme value (MDCEV) model is estimated to represent the number of one-way trips undertaken weekly with different purposes (commuting, work-related, education, shopping, personal business/social recreation), and by different modes (car, public transport, active modes). Explanatory variables include socioeconomic characteristics, location, the time period during the pandemic (i.e., waves). In addition, latent variables were included representing underlying attitudes such as satisfaction towards life or concern about the use of public transport – which might certainly play an important role in understanding individual weekly travel behaviour decisions. The model structure has the advantage that it estimates commuting and non-commuting activity together, allowing for a substitution effect between them. The results suggest that across all waves and jurisdictions, respondents who WFH more are more likely to have a higher number of shopping trips and personal business/social recreation trips, perhaps substituting these trips in replacement of their lesser commuting trips. Interestingly, all other influences held constant, individuals who are more concerned about the use of public transport are more likely to undertake commuting trips by all modes, more likely to do shopping trips, and less likely to undertake personal business/social recreation trips – suggesting they are prioritising essential trips rather than social/personal trips and perceive the risk of COVID-19 to be higher due to this travel.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:transa:v:179:y:2024:i:c:s0965856423003579
    DOI: 10.1016/j.tra.2023.103937
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    References listed on IDEAS

    as
    1. Balbontin, Camila & Hensher, David A. & Beck, Matthew J. & Giesen, Ricardo & Basnak, Paul & Vallejo-Borda, Jose Agustin & Venter, Christoffel, 2021. "Impact of COVID-19 on the number of days working from home and commuting travel: A cross-cultural comparison between Australia, South America and South Africa," Journal of Transport Geography, Elsevier, vol. 96(C).
    2. Jokubauskaitė, Simona & Hössinger, Reinhard & Aschauer, Florian & Gerike, Regine & Jara-Díaz, Sergio & Peer, Stefanie & Schmid, Basil & Axhausen, Kay W. & Leisch, Friedrich, 2019. "Advanced continuous-discrete model for joint time-use expenditure and mode choice estimation," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 397-421.
    3. Sangho Choo & Patricia Mokhtarian & Ilan Salomon, 2005. "Does telecommuting reduce vehicle-miles traveled? An aggregate time series analysis for the U.S," Transportation, Springer, vol. 32(1), pages 37-64, January.
    4. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    5. Zhang, Junyi & Hayashi, Yoshitsugu & Frank, Lawrence D., 2021. "COVID-19 and transport: Findings from a world-wide expert survey," Transport Policy, Elsevier, vol. 103(C), pages 68-85.
    6. Diego Maria Barbieri & Baowen Lou & Marco Passavanti & Cang Hui & Inge Hoff & Daniela Antunes Lessa & Gaurav Sikka & Kevin Chang & Akshay Gupta & Kevin Fang & Arunabha Banerjee & Brij Maharaj & Louisa, 2021. "Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-18, February.
    7. Pinjari, Abdul Rawoof & Bhat, Chandra R. & Hensher, David A., 2009. "Residential self-selection effects in an activity time-use behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 729-748, August.
    8. 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.
    9. Hensher, David A. & Wei, Edward & Beck, MatthewJ. & Balbontin, Camila, 2021. "The impact of COVID-19 on cost outlays for car and public transport commuting - The case of the Greater Sydney Metropolitan Area after three months of restrictions," Transport Policy, Elsevier, vol. 101(C), pages 71-80.
    10. 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.
    11. John Horn, 1965. "A rationale and test for the number of factors in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 30(2), pages 179-185, June.
    12. 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.
    13. Beck, Matthew J. & Hensher, David A., 2020. "Insights into the impact of COVID-19 on household travel and activities in Australia – The early days of easing restrictions," Transport Policy, Elsevier, vol. 99(C), pages 95-119.
    14. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    15. Balbontin, Camila & Hensher, David A. & Beck, Matthew J., 2023. "How are life satisfaction, concern towards the use of public transport and other underlying attitudes affecting mode choice for commuting trips? a case study in Sydney from 2020 to 2022," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    16. 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).
    17. 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.
    18. Balbontin, Camila & Hensher, David A. & Beck, Matthew J., 2022. "Advanced modelling of commuter choice model and work from home during COVID-19 restrictions in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).
    19. Pinjari, Abdul Rawoof & Bhat, Chandra, 2010. "A multiple discrete-continuous nested extreme value (MDCNEV) model: Formulation and application to non-worker activity time-use and timing behavior on weekdays," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 562-583, May.
    20. Guevara, C. Angelo & Hess, Stephane, 2019. "A control-function approach to correct for endogeneity in discrete choice models estimated on SP-off-RP data and contrasts with an earlier FIML approach by Train & Wilson," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 224-239.
    21. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
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    More about this item

    Keywords

    COVID-19; Working from home; Commuting trips; Non-commuting trips; Productivity; Public transport implications;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R48 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government Pricing and Policy
    • R20 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

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