Dubai: Dubai's Roads and Transport Authority (RTA) recently concluded the Behavioural Science Awareness Week for Leadership, which resulted in the development of more than 27 behavioural use cases. The event was organised in line with the Government of Dubai's approach to leveraging behavioural science as a strategic tool to advance public policy, improve service quality, and support evidence-based decision-making, contributing to a positive and sustainable impact on corporate performance and customer experience.
According to Emirates News Agency, Moaza Saeed Al Marri, CEO of Executive Affairs Sector at RTA, highlighted the authority's commitment to embedding behavioural science as a supporting corporate approach to developing services and policies. This initiative aims to provide a deeper understanding of customer needs, design more efficient and effective experiences, and deliver a sustainable positive impact across Dubai's transport system, aligning with the Government of Dubai's directions to enhance quality of life and well-being in the emirate.
She further explained that the event serves as a practical platform for knowledge exchange and capacity building. It focuses on translating behavioural concepts into actionable initiatives that enhance customer experience, improve service efficiency, and strengthen a culture of innovation and continuous improvement within the corporate work environment.
The Behavioural Science Awareness Week for Leadership attracted a distinguished group of international behavioural science experts. They delivered a series of interactive sessions, leadership discussions, and practical exercises aimed at translating theoretical knowledge into applicable tools for RTA's projects and services. The programme covered a range of integrated topics, including evidence-based behavioural policy design, the promotion of positive behaviours within the transport system, enhancement of customer experience through behavioural interventions, and support for corporate decision-making using behavioural models.
