Anticipating the impact of circular interventions
How can we identify promising interventions before implementing them in the real world?
PREDICT is BELOOP’s AI-powered simulation and forecasting tool, developed by the El-Erian Institute of Behavioural Economics and Policy at Cambridge Judge Business School. It uses machine learning to identify, assess and prioritise behavioural interventions that can encourage circular consumption, helping researchers explore their potential effectiveness and identify promising approaches for different consumer groups and contexts.
As BELOOP progresses, PREDICT will be used across the project’s four pilot domains to forecast the potential impact of behavioural interventions and help identify promising approaches for real-world testing. The pilots will assess how these interventions perform in practice, generating evidence on their effectiveness across different consumption contexts.
HOW PREDICT SUPPORTS BELOOP
-
Explore potential outcomes
Use AI-powered forecasting to investigate the potential effects of proposed behavioural interventions.
-
Inform intervention design
Help identify promising approaches and inform the design and pre-testing of behavioural interventions.
-
Assess intervention effectiveness
Use evidence from the pilots to understand which interventions work, for whom and under what conditions.