IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i17p7289-d1463369.html
   My bibliography  Save this article

The Impacts of Remote Work and Attitudinal Shifts on Commuting Reductions in Post-COVID Melbourne, Australia

Author

Listed:
  • Gheyath Chalabi

    (Department of Civil and Construction Engineering, Swinburne University of Technology, John St, Hawthorn, VIC 3122, Australia)

  • Hussein Dia

    (Department of Civil and Construction Engineering, Swinburne University of Technology, John St, Hawthorn, VIC 3122, Australia)

Abstract

This paper analyses the commuting frequencies and modal choices of travellers in Melbourne, using a dataset reflecting travel behaviour before and after COVID-19. A factor analysis of 63 latent variables identified seven key factors, which were used in cluster analysis to examine the relationships between latent constructs, land use, and socio-demographic variables, as well as commuting behaviours. The analysis categorised white-collar employees into four groups based on their remote work engagement, with socio-demographics and industry type as key factors. The analysis shows that female clerical and administrative workers who worked from home during the pandemic are now returning to the office, raising gender equality concerns within society. Meanwhile, the education and training sector mandates office attendance despite the feasibility of remote work, as universities prioritise in-person attendance to attract more international students, impacting societal norms around telecommuting. The analysis revealed that saving on commute costs, reducing travel time, and spending more time with family are the among the primary factors influencing travel behaviour among white-collar employee’s post-pandemic. The study found that the decrease in public transport trips is associated with increased telecommuting rather than service dissatisfaction, especially among Central Business District (CBD) employees who still rely on public transport. This trend suggests that the CBD sector’s growing acceptance of remote work is reducing daily commutes, which puts additional pressure on public transport providers to sustain and improve their services. A decline in service quality could further reduce ridership, highlighting the need for consistent, high-quality public transport. Furthermore, the study found that increased telecommuting is likely to reduce car trips in the future, especially among healthcare and social workers who prefer driving due to public transport’s unreliability for their demanding schedules. By examining variables like the advantages and disadvantages of working from home, convenience, accessibility, and the efficiency of public transport, this study enhances the understanding of transport behaviour and underscores the need to improve public transport reliability to support sustainable cities as remote work grows.

Suggested Citation

  • Gheyath Chalabi & Hussein Dia, 2024. "The Impacts of Remote Work and Attitudinal Shifts on Commuting Reductions in Post-COVID Melbourne, Australia," Sustainability, MDPI, vol. 16(17), pages 1-30, August.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7289-:d:1463369
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/17/7289/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/17/7289/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Handy, Susan & Cao, Xinyu & Mokhtarian, Patricia L., 2005. "Correlation or causality between the built environment and travel behavior? Evidence from Northern California," University of California Transportation Center, Working Papers qt5b76c5kg, University of California Transportation Center.
    3. Sonja Haustein, 2012. "Mobility behavior of the elderly: an attitude-based segmentation approach for a heterogeneous target group," Transportation, Springer, vol. 39(6), pages 1079-1103, November.
    4. Mokhtarian, Patricia & Varma, Krishna, 1998. "The Trade-Off Between Trips and Distance Traveled in Analyzing the Emissions Impacts of Center-Based Telecommuting," Institute of Transportation Studies, Working Paper Series qt43b756qg, Institute of Transportation Studies, UC Davis.
    Full references (including those not matched with items on IDEAS)

    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. Brown, Colby & Balepur, Prashant & Mokhtarian, Patricia L., 2005. "Communication Chains: A Methodology for Assessing the Effects of the Internet on Communication and Travel," University of California Transportation Center, Working Papers qt4cf351bc, University of California Transportation Center.
    2. Walls, Margaret & Safirova, Elena, 2004. "A Review of the Literature on Telecommuting and Its Implications for Vehicle Travel and Emissions," Discussion Papers 10492, Resources for the Future.
    3. Gheyath Chalabi & Hussein Dia, 2024. "Telecommuting and Travel Behaviour: A Survey of White-Collar Employees in Adelaide, Australia," Sustainability, MDPI, vol. 16(7), pages 1-28, March.
    4. Figueroa, Maria J. & Nielsen, Thomas A. Sick & Siren, Anu, 2014. "Comparing urban form correlations of the travel patterns of older and younger adults," Transport Policy, Elsevier, vol. 35(C), pages 10-20.
    5. Nicholas S. Caros & Jinhua Zhao, 2022. "Preparing urban mobility for the future of work," Papers 2201.01321, arXiv.org.
    6. Pirdavani, Ali & Bellemans, Tom & Brijs, Tom & Kochan, Bruno & Wets, Geert, 2014. "Assessing the road safety impacts of a teleworking policy by means of geographically weighted regression method," Journal of Transport Geography, Elsevier, vol. 39(C), pages 96-110.
    7. 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.
    8. Nayak, Suchismita & Pandit, Debapratim, 2021. "Potential of telecommuting for different employees in the Indian context beyond COVID-19 lockdown," Transport Policy, Elsevier, vol. 111(C), pages 98-110.
    9. Fabio Grazi & Jeroen C.J.M. van den Bergh & Jos N. van Ommeren, 2008. "An Empirical Analysis of Urban Form, Transport, and Global Warming," The Energy Journal, , vol. 29(4), pages 97-122, October.
    10. Kamruzzaman, Md. & Baker, Douglas & Washington, Simon & Turrell, Gavin, 2013. "Residential dissonance and mode choice," Journal of Transport Geography, Elsevier, vol. 33(C), pages 12-28.
    11. Pengyu Zhu, 2013. "Telecommuting, Household Commute and Location Choice," Urban Studies, Urban Studies Journal Limited, vol. 50(12), pages 2441-2459, September.
    12. Ding, Chuan & Wang, Donggen & Liu, Chao & Zhang, Yi & Yang, Jiawen, 2017. "Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 65-80.
    13. Van Acker, Veronique & Ho, Loan & Stevens, Larissa & Mulley, Corinne, 2020. "Quantifying the effects of childhood and previous residential experiences on the use of public transport," Journal of Transport Geography, Elsevier, vol. 86(C).
    14. Galit Cohen-Blankshtain & Peter Nijkamp & Kees van Montfort, 2004. "Modelling ICT Perceptions and Views of Urban Front-liners," Urban Studies, Urban Studies Journal Limited, vol. 41(13), pages 2647-2667, December.
    15. Barbora Mazúrová & Ján Kollár & Gabriela Nedelová, 2021. "Travel Mode of Commuting in Context of Subjective Well-Being—Experience from Slovakia," Sustainability, MDPI, vol. 13(6), pages 1-17, March.
    16. Ding, Yu & Lu, Huapu, 2016. "Activity participation as a mediating variable to analyze the effect of land use on travel behavior: A structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 52(C), pages 23-28.
    17. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    18. Chetan Doddamani & M. Manoj, 2023. "Analysis of the influences of built environment measures on household car and motorcycle ownership decisions in Hubli-Dharwad cities," Transportation, Springer, vol. 50(1), pages 205-243, February.
    19. Singh, Abhilash C. & Faghih Imani, Ahmadreza & Sivakumar, Aruna & Luna Xi, Yang & Miller, Eric J., 2024. "A joint analysis of accessibility and household trip frequencies by travel mode," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    20. Watanabe, Hajime & Maruyama, Takuya, 2024. "A Bayesian sample selection model with a binary outcome for handling residential self-selection in individual car ownership," Journal of choice modelling, Elsevier, vol. 51(C).

    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:gam:jsusta:v:16:y:2024:i:17:p:7289-:d:1463369. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.