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The 'Four Dimensions of Behaviour' framework: a tool for characterising behaviours to help design better interventions

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  • Tim Chatterton
  • Charlie Wilson

Abstract

This paper sets out the rationale and structure of a tool for assisting policy-makers and practitioners to understand behavioural challenges and open up thinking on the design of effective 'behaviour change' interventions. The 'Four Dimensions of Behaviour' (4DB) framework is based on the theoretical and empirical research in a range of policy domains including transport and pro-environmental behaviour more generally. The 4DB framework characterises multifaceted behaviours along dimensions of actor, domain, durability and scope. Its application in workshop or structured settings opens up diverse and non-exclusive discussion on designing interventions to match salient behavioural characteristics. The use of the 4DB framework in the transport domain is demonstrated for travel behaviours of interest to policy-makers using examples of buying plug-in vehicles (PiVs), commuting by bicycle, eco-driving and making business trips by train.

Suggested Citation

  • Tim Chatterton & Charlie Wilson, 2014. "The 'Four Dimensions of Behaviour' framework: a tool for characterising behaviours to help design better interventions," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(1), pages 38-61, February.
    • Handle: RePEc:taf:transp:v:37:y:2014:i:1:p:38-61
    DOI: 10.1080/03081060.2013.850257
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    Cited by:

    1. Maria Juschten & Shannon Page & Helen Fitt, 2020. "Mindsets Set in Concrete? Exploring the Perspectives of Domestic Travellers on New Zealand’s (Auto-)Mobility Culture," Sustainability, MDPI, vol. 12(18), pages 1-21, September.
    2. Jessica K. Breadsell & Christine Eon & Gregory M. Morrison, 2019. "Understanding Resource Consumption in the Home, Community and Society through Behaviour and Social Practice Theories," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    3. Troy Malatesta & Jessica K. Breadsell, 2022. "Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    4. Laura Fogg-Rogers & Enda Hayes & Kris Vanherle & Péter I. Pápics & Tim Chatterton & Jo Barnes & Stephan Slingerland & Corra Boushel & Sophie Laggan & James Longhurst, 2021. "Applying Social Learning to Climate Communications—Visualising ‘People Like Me’ in Air Pollution and Climate Change Data," Sustainability, MDPI, vol. 13(6), pages 1-16, March.
    5. Giest, Sarah & Mukherjee, Ishani, 2018. "Behavioral instruments in renewable energy and the role of big data: A policy perspective," Energy Policy, Elsevier, vol. 123(C), pages 360-366.

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