Although behavioural nudging has been often used as a method to promote sustainable choices, its application is quite limited in the field of active mobility. Gamification and rewarding schemes appeared recently in mobility sector to nudge urban cycling.
The scheme presented in this paper was based on a TRL9 antifraud system to certify, monitor and reward urban bike rides in Braga, Istanbul and Tallinn during 2022.Local authorities rewarded urban cyclists with monetary vouchers to be spent in local shops. Cities benefited from valuable cycling data collected for both evaluating already existing mobility measures and infrastructures and investing in data-driven policies guiding the transition towards climate neutrality. The cross-cutting themes of inclusion and accessibility were also addressed, since citizens were able to cooperate through the app on the creation of local maps pinning cycling-relevant infrastructure and to send reports about infrastructure related barriers (e.g., damaged road signs). About 1,500 users in 3 different cities were engaged, saving more than 133 tons of CO2 in 6 months and spending more than 85,000 euros in local shops. Additionally, more than 90% of the users stated that they will continue cycling after the end of the monetary rewards provided by the scheme.
The paper presents the quantitative (KPIs based) and qualitative (users questionnaires based) assessment as well as the additional data analysis results that were carried out during the scheme testing.
The correlation between trip, weather and socio-demographic data provided valuable knowledge that can be used to target vulnerable groups and to enhance the cycling incentives for bad weather days. The knowledge extracted can be integrated into the climate neutral strategies of the transition cities/regions for designing and implementing more efficient future actions and investments to successfully promote greener and more active mobility, ensuring high levels of cycling throughout the year.

Maria Konstantinidou (a), Josep Maria Salanova Grau (a), Annarita Leserri (b), Fariya Sharmeen (c), Matt Davoudizavareh (c)
(a): Centre for Research and Technology Hellas/CERTH-Hellenic Institute of Transport/HIT, (b): PinBike, (c): KTH Royal Institute of Technology

ID Abstract: 501