Agent-based explanations of solar energy adoption and implications for incentive programs in Germany
*Names in bold indicate Presenter
What leads individuals to adopt more environmentally-sustainable patterns of consumption? An understanding of the factors that shape environmental consumption can inform policy interventions designed to promote more desirable environmental behaviors, such as an increased support for environmental protection or increased investments in energy-efficient technologies. This paper presents an agent-based model of the adoption of a particular, high-cost environmental technology: residential solar photovoltaic (PV) systems. We show how the dynamics of solar PV adoption are highly dependent on the degree to which social networks linking potential adopters exhibit network segregation, meaning those with similar propensities to adopt also influence one another’s adoption choices. The presence of network segregation can dramatically influence the efficacy of governmental programs meant to enhance solar PV adoption. To illustrate, this agent-based model is used to show how current incentives for solar adoption being used in Germany, particularly the feed-in tariff, may lead to an unanticipated outcome whereby adoption becomes even more likely among those who already have high propensity to adopt solar (agents within affluent communities) and less likely among those who are most in need of solar adoption incentives (less affluent agents). Furthermore, our model is used to explore how different policy incentives potentially influence PV adoption decisions in private households. Overall, this paper provides an illustration of how agent-based models may be used to evaluate and experiment with policy interventions in a virtual space, which enhances the scientific basis of policymaking.