Table of contents
DOI: https://doi.org/10.58248/HS124
Overview
Promoting low-carbon, green travel options, such as active travel, could help to reduce carbon emissions from transport.[1][2][3] However, transport behaviour is complex and affected by many factors including personal attitudes, the nature of the built environment and weather conditions.[4][5][6][7][8][9][10] Transport planning and decision-making can assume that people make rational decisions when deciding which form of transport to use, when and where. However, these decisions are often influenced by ‘cognitive biases’ that mean that most people do not behave rationally. These biases should be accounted for in transport planning.[11]
Due to the low number of contributions to the horizon scan on this subject, and given overlap with other articles in this category, POST has not drafted an article for this topic. Instead, the main opportunities and challenges identified by contributors are briefly summarised below:
- Contributors stated a need to incentivise low carbon travel options. Available evidence suggests some common factors underlie successful schemes, such as the availability of personal data, public transport infrastructure and market supply of transport modes, such as e-bikes.[12] Both positive and negative financial incentives could be used.[13]
- Assessing the effect of Mobility as a Service (MaaS) on travel behaviour. MaaS is a concept looking to generate a shift in transport mode through the integration of transport services.[14] For example, users could use an app to access public transport, ride sharing and bike sharing services to complete a trip. However, it this could have unintended outcomes if it reduced the use of public transport options.[15]
- Contributors suggested using mobility narratives as a tool to promote social engagement with new forms of mobility infrastructure.[16][17] A narrative is a short story of what needs to be done to achieve something or solve a problem. For example, narratives could be created around mobility as a collective good or to promote a shift from ‘ownership’ to ‘usership’.[18][19][20]
- Greater understanding of why local traffic measures to promote active travel are often perceived as an imposition by affected local communities, including how to mitigate negative impacts and how to optimise and communicate benefits.[21][22][23][24][25]
- How to address the fact that individuals that otherwise demonstrate environmental consumption behaviour may have aviation use behaviours that result in greater individual GHG emissions than the savings arising from other behaviours.[26][27][28][29][30]
References
[1] Avis, A. (2023). Incentivising greener travel. TRL
[2] DfT. (2021). Decarbonising Transport A Better, Greener Britain. GOV.UK
[3] C40 Knowledge. (2021). Why green and healthy transport modes deliver vast rewards for cities.
[4] Deng. C. (2025). Analysis of Green Travel Choice Behavior of Residents in Central Urban Areas: Applying the Theory of Planned Behavior and Stimulus–Organism–Response Model. Sustainability, 17(5), 2208
[5] Nogueira, M., et al. (2023). Sustainable mobility choices: Exploring the impact of consumers’ values, attitudes, perceived behavioural control and subjective norms on the likelihood to choose sustainable mobility options. Journal of Consumer Behaviour, Volume22, Issue2, Special Issue: Consumers’ Transport and Mobility Decisions, Pages 511-528
[6] Garcia-Sierra, M., et al. (2015). Behavioural economics, travel behaviour and environmental-transport policy. Transportation Research Part D: Transport and Environment Volume 41, Pages 288-305
[7] Yap, M., et al. (2024). Passenger valuation of interchanges in urban public transport. Journal of Public Transportation, Volume 26, 2024, 100089
[8] Vongvit, R., et al. (2024). Effects of trust and customer perceived value on the acceptance of urban air mobility as public transportation. Travel Behaviour and Society, Volume 36, 100788
[9] Lim, T., et al. (2024). Effects of within-trip subjective experiences on travel satisfaction and travel mode choice: A conceptual framework. Transportation Research Part F: Traffic Psychology and Behaviour, Volume 104, Pages 201-216
[10] Huang, Y., et al. (2024). Travel behaviour and multimodality: a conceptual framework and critical review of research. Transport Reviews, Volume 44, 2024 – Issue 3
[11] Watkins, S., et al. (2025). Recognised cognitive biases: How far do they explain transport behaviour? Journal of Transport & Health, Volume 40, 101941
[12] Hine, R., et al. (2020). Incentivising low-carbon travel Lessons from a wide range of reward and platform schemes. Grantham Institute, Imperial College London, UK and ClimateWorks Foundation, USA
[13] Mitchell, M., et al. (2023). Moving with the Times: Financial incentives for sustainable travel. Centre for London
[14] Department for Transport. (2023). What is mobility as a service (MaaS)?
[15] Alyavina, E. et al. (2024). Mobility-as-a-Service and unsustainable travel behaviour: Exploring the car ownership and public transport trip replacement side-effects of the MaaS paradigm. Transport Policy Volume 150, May 2024, Pages 53-70
[16] Bergman, N. (2017). Stories of the future: Personal mobility innovation in the United Kingdom. Energy Research & Social Science, Volume 31, Pages 184-193
[17] Bock-Brown, O., et al. (2024). Winging it: visions, automation, and narrating alternative mobility futures. Mobilities, 1–16.
[18] Te Brömmelstroet, M., et al. (2022). Identifying, nurturing and empowering alternative mobility narratives. Journal of Urban Mobility, 2, Article 100031.
[19] Holding, E., et al. (2020). Grand Narratives for sustainable mobility: A conceptual review. Energy Research & Social Science, Volume 65,101454
[20] Gulc, A. et al. (2024). Classification of Smart and Sustainable Urban Mobility. Energies, 17(9), 2148
[21] Pritchett, R. et al. (2024). Exploring expectations and lived experiences of Low Traffic Neighbourhoods in Birmingham, UK. Travel Behaviour and Society, Volume 36,100800
[22] Dudley, G. et al. (2023). Why low traffic neighbourhood schemes must be led locally. LSE
[23] Furlong, J. et al. (2023). Are low-traffic neighbourhoods greenwashing? Here’s what the evidence says. The Conservation
[24] University of Westminster. (2022). Low Traffic Neighbourhoods in London Research Study.
[25] Aldred, R., et al. (2021). Equity in new active travel infrastructure: A spatial analysis of London’s new Low Traffic Neighbourhoods. Journal of Transport Geography, Volume 96,103194
[26] Oates, C., et al. (2015). Flying in the face of environmental concern. Journal of Marketing Management, 31 (13-14). 1503 – 1528.
[27] Cocolas, N. ,et al. (2020). Consumer attitudes towards flying amidst growing climate concern. Journal of Sustainable Tourism, Volume 29, 2021 – Issue 6
[28] Crosby, P., et al. (2024). Air travellers’ attitudes towards carbon emissions: evidence from the Google Flights interface. Journal of Sustainable Tourism, 1–24.
[29] Crouse, S., et al. (2024). Support for green initiatives in aviation: A case study across American aviation consumers. Journal of the Air Transport Research Society, Volume 2, June 2024, 100020
[30] Wendt, N. et al. (2024). Consumer willingness to pay for emission reduction in air travel: A meta-analysis. Transportation Research Part D: Transport and Environment, Volume 134,104347
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