Exploring Investment Decisions in Home Heating System Replacement with a Multi-stage Algorithm: An Agent-Based Model

The challenge of climate change demands active political interventions. Private building energy retrofitting is one of the main fields such interventions focus on, as in the European Union households consume around a quarter of total produced energy. Finding an efficient way to propose and evaluate policies aiming to stimulate private energy retrofitting is a promising direction approached from different methodical perspectives, among which agent-based modelling is a yet an underdeveloped one. This paper aims to introduce a psychologically grounded multi-stage algorithm to simulate houseowners’ decision-making related to heating system replacements. Preliminary model runs with this algorithm show that it is able to produce complex dynamics with different agents being at different decision-making stages at the same time.