资源环境科技发展态势分析平台

There has been a surge in the application of behavioral insights for environmental policymaking. It is often presented as an easy and low-cost intervention to alter individual behavior. However, there is limited insight into the cost effectiveness of these attempts and the impact of inserting behavioral policy instruments into an existing mix of traditional tools in a particular policy sector. Furthermore, there has been little focus on the intersection of large behavioral datasets and how they could complement behavioral insights. We present a conceptual overview of how the intersection of big data and behavioral knowledge would work in the renewable energy sector. We indicate that inserting behavioral insights into the energy instrument mix is complex due to technological trajectories, path dependencies and resistance from incumbent industries to change production patterns. We also highlight the underutilized role of large behavioral datasets that can inform not only policy implementation, but also policy design and evaluation efforts. Drawing on these findings, we introduce future research streams of government capacity in combining behavioral insights and data, the compatibility of this information with existing policy instruments and how this affects policy change.