Objective
Waste recycling has attracted growing attention within the circular economy, yet its effectiveness ultimately depends on correct sorting at the point of disposal. Such sorting, in turn, relies on citizens' voluntary compliance. To further promote waste separation behavior, this study aims to estimate the impact of descriptive norms through a field experiment conducted at local public events in Japan. Prior research (Uetake & Ando, under review) has shown that the pre-existing contents of waste receptacles can function as descriptive norms that influence sorting behavior. This study aims to identify the conditions under which descriptive norms are most operative.


Methods
This is a planned study; data collection is scheduled for November 2025. A two-day field intervention is conducted at a community event venue in Tochigi Prefecture, Japan. This municipal lifelong-learning event features student exhibits and presentations by local cultural groups. Daily attendance is projected at approximately 4,000 visitors, with the audience consisting predominantly of local children and their parents. Waste stations are assigned to control and treatment conditions and rotated across time blocks to counterbalance. In the treatment condition, we pre-seed the bins with incorrectly sorted items as descriptive norms. We analyze people's responses using both quantitative and qualitative indicators, including measuring the mis-sorting rate and conducting systematic behavioral observations.


Results & Discussion
We report comparisons of mis-sorting rates between the intervention and control groups, as well as behavioral observation-based comparisons, including the time required to dispose of an item when participants are in front of the bin. We expect that the presence of pre-existing mis-sorted items is expected to increase contamination, because people treat the visible contents as a descriptive normative cue during sorting. The study deepens understanding of the mechanisms through which descriptive norms operate and inform policy applications.