Ready-made oTree applications for the study of climate change adaptation behavior

Abstract

Adaptation to climate change is an intricate decision-making process that requires balancing costs and uncertain benefits in a setting with high stakes and low probabilities. Risk preferences then shape the way individuals or groups adapt to these settings, dependent or independent of public policy. With the aim of shedding light on these preferences and aid policy efficiency, we develop a set of Climate Change Adaptation Applications based on oTree (CAT). The set consists of eight discrete apps that correspond to different risk perception biases and corrective treatments. From a scientific perspective CAT can be used to better understand adaptation decision constraints at the individual and community level, while from a policy perspective it can help policy makers plan or improve existing adaptation strategies. A pilot experiment with 75 subjects was conducted to evaluate CAT functionality and the decision-making process. The experiment examined adaptation decisions under different risk levels in a home flood context. It successfully explored the impact of unknown risks, various time horizons, framing conditions, and group dynamics. The results show that adaptation decisions are strongly correlated with risk levels, and adaptation rate increases when uncertainty is introduced. Collective adaptation increases in group dynamics, although polarization is observed, and uncertainty reinforces this through collective inaction. In addition, typical subject characteristics, including age, gender and home ownership, have a significant impact on adaptation.