Overcoming inaction: An agent-based modelling study of social interventions that promote systematic pro-environmental change

Abstract

Even though many people have pro-environmental convictions, oftentimes they do not actually engage in pro-environmental behaviour. We hypothesise that behavioural change is hampered by a social feedback loop that reinforces the status quo: People routinely underestimate others’ pro-environmental convictions, and when they expect that others care less, they are unlikely to show more pro-environmental behaviour themselves, which reinforces the general impression that people do not care. This leads to the question of how to effectively elicit a push from the current state to a state in which pro-environmental behaviour becomes more widespread. We examine this question with an agent-based model (ABM) which was parameterised using individual-level survey data collected in several Dutch neighbourhoods. We explore whether interventions that make people talk more about their convictions versus interventions that enhance the visibility of pro-environmental behaviour can trigger individuals to update their expectations and consequently tip the system into a more environmentally-friendly state. Our simulations suggest that enhancing the visibility of pro-environmental behaviour with an intervention may be most effective to motivate durable pro-environmental change. Motivating more talk on the topic only generates temporary effects in our simulations. These results can provide valuable guidance for empirical research on norm-based interventions and it may eventually inform the development of evidence-based policies that effectively encourage pro-environmental change.