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The impact of telecommuting on residential relocation and residential preferences: A latent class modelling approach

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  • Ettema, Dick

    (Utrecht University; Netherlands)

Abstract

The advance of information and communication technologies (ICTs) has changed travellers’ appreciation of travel distance in various ways. In the context of telecommuting, ICT increasingly allows us to work from home one or more days per week. One hypothesis that has been put forward is that because ICTs reduce the frequency of commuting, it allows workers to accept longer commute distances, implying that telecommuters have a different valuation of travel distance than regular commuters and would also favour more peripheral residential locations. The question can be raised, however, whether telecommuters can be regarded as a homogeneous group with respect to their valuation of commute distance and residential preferences. To investigate the heterogeneity of commuters’ and telecommuters’ preferences, latent class discrete choice models of workers’ intended relocation probability and preferred residential environment were estimated. The results suggest that telecommuting is not a factor that can be used to identify segments with different residential preferences. However, within the group of telecommuters, two different classes can be identified, which can be characterised as being sensitive and insensitive to commute distance.

Suggested Citation

  • Ettema, Dick, 2010. "The impact of telecommuting on residential relocation and residential preferences: A latent class modelling approach," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 7-24.
  • Handle: RePEc:ris:jtralu:0034
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    References listed on IDEAS

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    Cited by:

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    3. João de Abreu e Silva, 2022. "Residential preferences, telework perceptions, and the intention to telework: insights from the Lisbon Metropolitan Area during the COVID‐19 pandemic," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S1), pages 142-161, November.
    4. Kogus, Ayelet & Brůhová Foltýnová, Hana & Gal-Tzur, Ayelet & Shiftan, Yuval & Vejchodská, Eliška & Shiftan, Yoram, 2022. "Will COVID-19 accelerate telecommuting? A cross-country evaluation for Israel and Czechia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 291-309.
    5. Blumenberg, Evelyn & Paul, Julene & Pierce, Gregory, 2021. "Travel in the digital age: Vehicle ownership and technology-facilitated accessibility," Transport Policy, Elsevier, vol. 103(C), pages 86-94.
    6. 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.
    7. Asmussen, Katherine E. & Mondal, Aupal & Batur, Irfan & Dirks, Abbie & Pendyala, Ram M. & Bhat, Chandra R., 2024. "An investigation of individual-level telework arrangements in the COVID-era," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    8. Tomás Cox & Ricardo Hurtubia, 2021. "Latent Segmentation of Urban Space through Residential Location Choice," Networks and Spatial Economics, Springer, vol. 21(1), pages 199-228, March.
    9. Soroui, Sarah T., 2021. "Understanding the drivers and implications of remote work from the local perspective: An exploratory study into the dis/reembedding dynamics," Technology in Society, Elsevier, vol. 64(C).
    10. Sebastian Scheuer & Dagmar Haase & Annegret Haase & Nadja Kabisch & Manuel Wolff & Nina Schwarz & Katrin Großmann, 2020. "Combining tacit knowledge elicitation with the SilverKnETs tool and random forests – The example of residential housing choices in Leipzig," Environment and Planning B, , vol. 47(3), pages 400-416, March.
    11. Ahmadreza Faghih-Imani & Naveen Eluru, 2020. "A finite mixture modeling approach to examine New York City bicycle sharing system (CitiBike) users’ destination preferences," Transportation, Springer, vol. 47(2), pages 529-553, April.
    12. Khandker Nurul Habib & Ph. D. & PEng, 2020. "On the Factors Influencing the Choices of Weekly Telecommuting Frequencies of Post-secondary Students in Toronto," Papers 2004.04683, arXiv.org.
    13. Tim-Benjamin Lembcke & Mathias Willnat & Henrik Lechte & Maike Greve & Julia Heinsohn & Alfred Benedikt Brendel, 2021. "Mobility Need-Adaptive Housing Platforms: The Benefit of a Commute Time Search Feature," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    14. Longden, Thomas, 2016. "The Regularity and Irregularity of Travel: an Analysis of the Consistency of Travel Times Associated with Subsistence, Maintenance and Discretionary Activities," ETA: Economic Theory and Applications 243150, Fondazione Eni Enrico Mattei (FEEM).
    15. Jia Guo & Tao Feng & Harry J. P. Timmermans, 2020. "Modeling co-dependent choice of workplace, residence and commuting mode using an error component mixed logit model," Transportation, Springer, vol. 47(2), pages 911-933, April.
    16. Caldarola, Bernardo & Sorrell, Steve, 2022. "Do teleworkers travel less? Evidence from the English National Travel Survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 282-303.
    17. Tomás Cox & Ricardo Hurtubia, 2022. "Compact development and preferences for social mixing in location choices: Results from revealed preferences in Santiago, Chile," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 246-269, January.
    18. Longden, Thomas, 2016. "The Regularity and Irregularity of Travel: an Analysis of the Consistency of Travel Times Associated with Subsistence, Maintenance and Discretionary Activities," ET: Economic Theory 243150, Fondazione Eni Enrico Mattei (FEEM).
    19. Jiang, Wen & Feng, Tao & Timmermans, Harry J.P., 2020. "Latent class path model of intention to move house," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).

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    More about this item

    Keywords

    transport; land use; telecommuting;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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