Towards a differentiated understanding of active travel behaviour: Using social theory to explore everyday commuting

Cornelia Guell · Jenna Panter · Natalia R. Jones · David Ogilvie

140 citations0/0 files storedSocial Science & Medicine

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Urban Transport and Accessibility Transportation Planning and Optimization Physical Activity and Health

Abstract

Fostering physical activity is an established public health priority for the primary prevention of a variety of chronic diseases. One promising population approach is to seek to embed physical activity in everyday lives by promoting walking and cycling to and from work ('active commuting') as an alternative to driving. Predominantly quantitative epidemiological studies have investigated travel behaviours, their determinants and how they may be changed towards more active choices. This study aimed to depart from narrow behavioural approaches to travel and investigate the social context of commuting with qualitative social research methods. Within a social practice theory framework, we explored how people describe their commuting experiences and make commuting decisions, and how travel behaviour is embedded in and shaped by commuters' complex social worlds. Forty-nine semi-structured interviews and eighteen photo-elicitation interviews with accompanying field notes were conducted with a subset of the Commuting and Health in Cambridge study cohort, based in the UK. The findings are discussed in terms of three particularly pertinent facets of the commuting experience. Firstly, choice and decisions are shaped by the constantly changing and fluid nature of commuters' social worlds. Secondly, participants express ambiguities in relation to their reasoning, ambitions and identities as commuters. Finally, commuting needs to be understood as an embodied and emotional practice. With this in mind, we suggest that everyday decision-making in commuting requires the tactical negotiation of these complexities. This study can help to explain the limitations of more quantitative and static models and frameworks in predicting travel behaviour and identify future research directions.

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