Household preferences regarding residential location and commuter choices, depending on household type and teleworking options

Viktoriya Kolarova; Ilka Dubernet

doi:10.59490/ejtir.2026.26.3.7893

Household preferences regarding residential location and commuter choices, depending on household type and teleworking options

Authors

Viktoriya Kolarova German Aerospace Center – Institute of Transport Research, Berlin, Germany https://orcid.org/0000-0003-4365-5528
Ilka Dubernet German Aerospace Center – Institute of Transport Research, Berlin, Germany https://orcid.org/0000-0003-4130-8303

DOI:

https://doi.org/10.59490/ejtir.2026.26.3.7893

Keywords:

teleworking, residential location choices, mode choice, commuting, commuting preferences

Abstract

Residential location choices and travel behaviour have implications for sustainability. For example, preferences for detached single-family homes in a green environment may lead to longer commutes, mostly by car. In the face of environmental challenges, commuting is essential for developing strategies for a more sustainable future. At the same time, it remains uncertain how commuting distances, car use for commuting, and urbanisation trends will evolve in the future. This study focuses on understanding individual choices and the relationship between residential, work and commuting choices for different household types. It is based on a quantitative online survey of residential location and mode choices of commuters in Germany using discrete choice experiments. The results show that travel time values are significantly lower for teleworkers than for non-teleworkers. Regarding mode choice, walking is perceived more negatively by family households, young households are most sensitive to car travel time, and public transport seems less attractive to them. In general, in a teleworking scenario, the elements of public transport use that are currently perceived as burdensome (especially waiting time) become less important. In terms of modal shift, telework could reduce car use for young households, but not for family households. This study provides an insight into the relationship between residential location, commuting and mode choice and opens a discussion on the impact of teleworking on the sustainability of commuting.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

Anik, M. A. H., Khan, N. A., & Habib, M. A. (2024). Mapping the interplay of work-arrangement, residential location, and activity engagement within an integrated model. Transportation Research Part A: Policy and Practice, 190, Article 104294. https://doi.org/10.1016/j.tra.2024.104294.

Asmussen, K. E., Mondal, A., & Bhat, C. R. (2024). The interplay between teleworking choice and commute distance. Transportation Research Part C: Emerging Technologies, 165, Article 104690. https://doi.org/10.1016/j.trc.2024.104690.

Bliemer, M. C. J., & Rose, J. M. (2006). Designing stated choice experiments: State-of-the-art. In R. Kitamura (Ed.), Proceedings 11th IATBR conference, The expanding sphere of travel behaviour research (pp. 1–35). Kyoto University. https://research.tudelft.nl/en/publications/designing-stated-choice-experiments-state-of-the-art/

ChoiceMetrics (2021). Ngene 1.3.: User manual & reference guide. ChoiceMetrics.

De Abreu e Silva, J. (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, 14(1), 142–161. https://doi.org/10.1111/rsp3.12558.

Dubernet, I. (2019). Understanding the value of travel time: Advanced modelling techniques applied to the National German Value of Travel Time and Travel Time Reliability Study [Doctoral dissertation, ETH Zurich]. Research Collection. https://doi.org/10.3929/ethz-b-000347412

Dubernet, I., & Axhausen, K. W. (2020). The German value of time and value of reliability study: the survey work. Transportation, 47(3), 1477–1513. https://doi.org/10.1007/s11116-019-10052-4.

Dubernet, I., Dubernet, T., & Axhausen, K. W. (2020). Comparing values of travel time obtained from workplace and short-term decisions. Travel Behaviour and Society, 20, 83–90. https://doi.org/10.1016/j.tbs.2020.02.002.

Dubernet, I., & Kolarova, V. (2024, January 7–11). Unveiling the teleworking effect: How remote work alters residential choices and commuting preferences [Paper presentation]. 103rd Annual Meeting of the Transportation Research Board (TRB), Washington, DC, United States.

Echeverría, L., Giménez Nadal, J. I., & Molina, J. A. (2024). Commuting in dual-earner households: international gender differences with time use surveys. Review of Economics of the Household, 1-23. https://doi.org/10.1007/s11150-024-09726-5.

Fatmi, M. R., Orvin, M. M., & Thirkell, C. E. (2022). The future of telecommuting post COVID-19 pandemic. Transportation Research Interdisciplinary Perspectives, 16, Article 100685. https://doi.org/10.1016/j.trip.2022.100685.

Guo, J., Feng, T., & Timmermans, H. J. (2020). Modeling co-dependent choice of workplace, residence and commuting mode using an error component mixed logit model. Transportation, 47(2), 911–933. https://doi.org/10.1007/s11116-018-9931-1

Hensher, D. A., & Greene, W. H. (2003). The mixed logit model: The state of practice. Transportation, 30(2), 133–176. https://doi.org/10.1023/A:1022518621075

Hess, S., & Palma, D. (2019). Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application, Journal of Choice Modelling, 32,Article 100170. https://doi.org/10.1016/j.jocm.2019.100170.

Hu, Y., van Wee, B., & Ettema, D. (2023). Intra-household decisions and the impact of the built environment on activity-travel behavior: A review of the literature. Journal of Transport Geography, 106, Article 103485. https://doi.org/10.1016/j.jtrangeo.2022.103485.

Lara-Pulido, J. A., & Martínez-Cruz, A. L. (2021). Teleworking from a near-home shared office in Mexico City: A discrete choice experiment on office workers (CERE Working Paper No. 2021:2). SSRN. https://doi.org/10.2139/ssrn.3763703

Lara-Pulido, J. A. (2023). Stated benefits of teleworking in Mexico City: A discrete choice experiment on office workers. Transportation Research Part A: Policy and Practice, 168, 1–12. https://doi.org/10.1016/j.tra.2023.103577

Louviere, J.J. & Hensher, D.A. (1983). Using discrete choice models with experimental design data to forecast consumer demand for a unique cultural event. Journal of Consumer Research, 10(3), 348–381. https://www.google.com/search?q=https://doi.org/10.1086/208970

Maheshwari, R., Van Acker, V., & Gerber, P. (2024). Commuting vs teleworking: How does it impact the relationship between commuting satisfaction and subjective well-being. Transportation Research Part A: Policy and Practice, 182, Article 104041. https://doi.org/10.1016/j.tra.2024.104041.

Mao, Z., & Wang, D. (2020). Residential relocation and life satisfaction change: Is there a difference between household couples? Cities, 97, Article 102565. https://doi.org/10.1016/j.cities.2019.102565.

Nobis, C., & Kuhnimhof, T. (2018). Mobilität in Deutschland – MiD: Ergebnisbericht [Mobility in Germany – MiD: Result report]. Bundesministerium für Verkehr und digitale Infrastruktur.

Schirmer, P.M., van Eggermond, M.A.B., & Axhausen, K.W. (2014). The role of location in residential location choice models: a review of literature. Journal of Transport and Land Use, 7(2), 3–21. https://doi.org/10.5198/jtlu.v7i2.740

Schmid, B., Schatzmann, T., Winkler, C., & Axhausen, K. W. (2022). A two-stage RP/SP survey to estimate the value of travel time in Switzerland: Short- versus long-term choice behavior (Arbeitsberichte Verkehrs- und Raumplanung No. 1724). IVT, ETH Zürich.

Srinivasan, S., & Ferreira, J. (2002). Travel behavior at the household level: understanding linkages with residential choice. Transportation Research Part D: Transport and Environment, 7(3), 225–242. https://doi.org/10.1016/S1361-9209(01)00021-9.

Timmermans, H. J., & Zhang, J. (2009). Modeling household activity travel behavior: Examples of state of the art modeling approaches and research agenda. Transportation Research Part B: Methodological, 43(2), 187–190. https://doi.org/10.1016/j.trb.2008.06.004.

Train, K. E. (2009). Discrete choice methods with simulation (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511805202

United Nations. (2019). World urbanization prospects: The 2018 revision (ST/ESA/SER.A/420). United Nations Department of Economic and Social Affairs, Population Division.

Van Cranenburgh, S., & Garrido-Valenzuela, F. (2025). Computer vision-enriched discrete choice models, with an application to residential location choice. Transportation Research Part A: Policy and Practice, 192, Article 104300. https://doi.org/10.1016/j.tra.2024.104300.

Velvart, J., Dato, P., & Kuhlmey, F. (2022). Tailored interventions in a major life decision: A home relocation discrete choice experiment (WWZ Working Paper No. 2022/03). Center of Business and Economics (WWZ), University of Basel. https://doi.org/10.5451/unibas-ep87754

Zhu, P. (2013). Telecommuting, household commute and location choice. Urban Studies, 50(12), 2441–2459. https://doi.org/10.1177/0042098013476077