Journal
COMPUTERS IN HUMAN BEHAVIOR
Volume 125, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2021.106970
Keywords
Persuasive technology; Mobility behavior; Self-selection; Attrition; App churn; Behavior change
Funding
- City of Bellinzona
- Swiss Federal Office of Energy (SFOE) under the ERA-NET scheme
- Innosuisse - Swiss Innovation Agency within the Swiss Competence Center for Energy Research (SCCER) Mobility
Ask authors/readers for more resources
The study investigates the impact of a persuasive app promoting sustainable travel behavior by analyzing users' mobility data, finding no evidence of self-selection bias or critical attrition biases. This supports the relevance of app-based persuasive technologies for mobility behavior change.
App-based persuasive technologies emerged as promising tools to promote sustainable travel behavior. However, the opt-in, self-selection framework characterizing their use in real-life conditions might actually lead to wrongly estimate their potential and actual impact in analyses that do not rely on strict randomized controlled trials (RCTs). To investigate evidence of such biases, we analyze mobility data gathered from users of a persuasive app promoting public transport and active mobility launched in 2018 in Bellinzona (Switzerland). We consider the users' baseline mobility data: km per day (total and by car) traveled during the app validation period, when behavior change motivational features were not enabled. To estimate the possible self-selection bias, we compare these data with the reference population, using data from the Swiss Mobility and Transport Census; to study the possible attrition bias, we look at the relations between baseline mobility and the number of weeks of app's active use. We find evidence of neither self-selection nor critical attrition biases. This strengthens findings by earlier non RCT-based analyses and confirms the relevance of app-based persuasive technologies for mobility behavior change.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available