An agent-based model framework for understanding the decisions of households and exploring bottom-up effects on housing sustainability

Abstract

Housing plays a crucial role in the transition towards sustainability. Zero-energy or low-carbon housing solutions are key, but their success depends on their acceptance by the users. We propose a conceptual and an operational framework for understanding households' residential choices as a base for an agent-based model, using the tenant as basic unit to populate it. We firstly conceptualise the decision-making process of tenants as a system. Secondly, we cluster the synthetic agents populating the model into typologies of dwellings and tenants. Thirdly, we display their actions in the action arena, and set-up the test runs. Lastly, we introduce the next steps to follow for the simulation of the bottom-up effects on housing sustainability.