TY - JOUR
T1 - An investigation of the motivators and barriers of smartphone app incentives for encouraging cycling
AU - Huang, Bingyuan
AU - Thomas, Tom
AU - Groenewolt, Benjamin
AU - van Berkum, Eric C.
N1 - Funding Information:
This study is part of the EMPOWER project, which is funded by the European Union's Horizon 2020 research and innovation programme. The authors thank I G Ayu Andani for her valuable help with the discrete choice modelling. Finally, we thank our anonymous reviewers, whose fair and thorough feedback greatly improved this paper.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/12
Y1 - 2022/12
N2 - Reducing car use through positive intervention strategies using smartphone apps has attracted a great deal of attention. A common intervention strategy is bicycle use, which is cost-effective, fast, clean, and healthy. However, the potential effects of positive interventions on cycling behaviour have not been well explored. This study builds up a real-world lab by using the SMART Mobility smartphone application to test the effect of interventions. Participants are recruited through the app and their travel data is recorded by the app. Participants’ privacy is protected in the app and experimental concepts are reduced so that the real behaviours can be further reached and analysed. Four types of cycling-related challenges were designed in the app and provided to the users to adopt every month. A mixed logit explanatory model for behavioural change is developed to explain how the behavioural change is related to travel patterns, intervention types and other mediating factors and the possible moderators. More than 1,000 users from the Dutch region of Twente used the smart app from March 2017 to June 2018. We found that challenge type and travel pattern impacted behaviour changes differently. Overall, the cycling challenges were effective in encouraging people to use bikes instead of cars. However, the challenges also had the effect of causing additional bike usage without a modal shift. The findings from the study can help with intervention design decisions.
AB - Reducing car use through positive intervention strategies using smartphone apps has attracted a great deal of attention. A common intervention strategy is bicycle use, which is cost-effective, fast, clean, and healthy. However, the potential effects of positive interventions on cycling behaviour have not been well explored. This study builds up a real-world lab by using the SMART Mobility smartphone application to test the effect of interventions. Participants are recruited through the app and their travel data is recorded by the app. Participants’ privacy is protected in the app and experimental concepts are reduced so that the real behaviours can be further reached and analysed. Four types of cycling-related challenges were designed in the app and provided to the users to adopt every month. A mixed logit explanatory model for behavioural change is developed to explain how the behavioural change is related to travel patterns, intervention types and other mediating factors and the possible moderators. More than 1,000 users from the Dutch region of Twente used the smart app from March 2017 to June 2018. We found that challenge type and travel pattern impacted behaviour changes differently. Overall, the cycling challenges were effective in encouraging people to use bikes instead of cars. However, the challenges also had the effect of causing additional bike usage without a modal shift. The findings from the study can help with intervention design decisions.
KW - Challenge and reward
KW - Mixed logit model
KW - Positive incentive
KW - Predictive analytics
KW - Travel behavioural change
KW - UT-Gold-D
UR - http://www.scopus.com/inward/record.url?scp=85139075896&partnerID=8YFLogxK
U2 - 10.1016/j.dajour.2022.100127
DO - 10.1016/j.dajour.2022.100127
M3 - Article
AN - SCOPUS:85139075896
SN - 2772-6622
VL - 5
JO - Decision Analytics Journal
JF - Decision Analytics Journal
M1 - 100127
ER -