Simulating households' energy transition in Amsterdam: An agent-based modeling approach

•This study adds sociality in building the agent-based model.•Tenants can play a game-changing role in the energy transition.•Higher energy prices motivate homeowners to adopt energy efficiency measures.•Social connections with similar neighbors influence adoption behavior. Energy efficiency measures and renewable energy are crucial to achieving climate targets and Sustainable Development Goals. Amsterdam is actively working toward these objectives by setting a carbon emissions reduction target and related policies. This study explores how homeowners' energy efficiency decisions contribute to Amsterdam's 2030 carbon emissions goal, using agent-based modeling and spatial microsimulation. We utilize spatial microsimulation to expand the data from the 2021 Dutch Housing Survey, while this generated data is then input into the agent-based model. The key finding stresses the significance of neighborhood-level analysis in energy transition planning due to the importance of contextual differences vis-à-vis energy efficiency decisions. The study also underscores tenants' game-changing role in achieving the target. The model developed for this study can be adapted and used for other places. Based on the insights from the model output, the study proposes policy recommendations that could be a useful addition to the current policy schemes in Amsterdam and similar cities.