The potential for persuasive messaging to increase active travel in transport and health apps

Presenter: Dr Kate Pangbourne, Institute for Transport Studies, University of Leeds

Abstract

I present the results of a two-month intervention study testing the objective persuasiveness of walking and cycling messages via an active travel incentivization and tracking application (BetterPoints). The aim was to understand whether firstly, messaging impacts on levels of active travel during the study, and secondly, whether it is worthwhile to take more care in composing specific or even potentially personalised push messages in the context of active travel, journey planning and Mobility as a Service applications. Despite a diversity of persuasive strategies used in sustainable mobility apps, reviews of these apps have suggested that techniques for personalisation and tailoring are underdeveloped in relation to tailoring to personal characteristics (Anagnostopoulou et al., 2017; Sunio et al., 2017).

In this study, a randomized control design with three groups addressed four objectives. (1) compare messages previously identified as subjectively persuasive with a ‘no message’ condition and a ‘placebo’ consisting of a generally positive message condition; (2) use recorded trip data to analyse whether levels of walking and cycling change during the message intervention in comparison to the baseline in the first two weeks of the trial (no messaging), the four weeks of the trial (messages pushed three times a week), and the final two weeks (surveys only); (3) compare objective and perceived persuasiveness of the messages used in the trial, as well as message recall (from data collected in the surveys); and (4) analyse relevant psychodemographic variables, such as age, gender and personality trait to assess whether these have a predictable relationship with perceived and actual persuasiveness of individual messages.

This original study has contributed more nuanced knowledge regarding whether in-app messaging has a measurable impact on levels of active travel and which variables may be important to know for targeting messages to individuals. This is useful to transport authorities and application designers since it will enable more effective push messaging to encourage policy-relevant active travel behaviours that have significant co-benefits for public health, decarbonisation and place quality.

Biography

Kate is an Associate Professor in the Institute for Transport Studies, co-leading the Social and Political Sciences Group. She joined the University of Leeds in 2016 with a prestigious personal research fellowship from the EPRSC and an equally prestigious University Academic Fellowship from the University. Kate is also a Deputy Director of the cross-university Leeds Social Sciences Institute, leading on developing capacity to commercialise social science research.

Her research and practice are highly interdisciplinary and oriented towards systemically addressing social inclusion and climate change through shifting our transport system, policies, individual choices and collective practices. She is particularly interested in the implications for environment and society of the ongoing technological change in the transport sector. The recently completed ADAPT project on persuasive low carbon transport messaging is the focus of her seminar. Current and recent work engages with transport operators & authorities and governmental organisations, with an emphasis on social inclusion and reducing environmental impact, presently through the lens of Mobility as a Service. Through a Michael Beverley Innovation Fellowship, Kate is working with FOD Mobility Group to investigate the user value of MaaS platforms and using co-design methods with users and developers to explore future development directions that support low carbon travel.

Kate is also a certificated LEGO® SERIOUS PLAY® facilitator, a methodology that can be used for strategy development, ideas generation and problem-solving, both individually and in non-hierarchical team-based settings.