Behavioural Data Science

Behavioural Data Science

Solving environmental and ecological problems is impossible without an understanding of how people and organizations behave.

Our work

We work with companies and governments to design and evaluate behavioural interventions aimed at promoting energy efficiency, low carbon transformation, and sustainability at large. We use experimental methods such as randomized control trials, online and laboratory experiments, to estimate the causal impacts of environmental policies and programmes. We combine these with machine learning methods to interpret and model observed behaviour from smart sensors and other digital devices. We have applied these approaches both in developed and developing countries, helping better understand energy and water use, waste recycling, and investment decisions.

ONGOING
EUNICE

Debiasing the uncertainties of climate stabilization ensembles

ONGOING
AdJUST

ADVANCING THE UNDERSTANDING OF CHALLENGES, POLICY OPTIONS AND MEASURES TO ACHIEVE A JUST EU ENERGY TRANSITION

ONGOING
CircEUlar

Developing circular pathways for a EU low-carbon transition

ONGOING
CircoMod

Circular Economy Modelling for Climate Change Mitigation

ONGOING
EDITS

Energy Demand changes Induced by Technological and Social innovations

CLOSED
COBHAM

The role of consumer behaviour and heterogeneity in the integrated assessment of energy and climate policies

BLECK, J., BONAN, J., LEMAY-BOUCHER, P., & SARR, B.

Drinking Tea with the Neighbors: Informal Clubs, General Trust, and Trustworthiness in Mali

American Political Science Review , 1-20 - 2023