Testing a norm-based policy for waste management: An agent-based modeling simulation on nudging recycling behavior. (15th September 2021) - Ceschi, Andrea; Sartori, Riccardo; Dickert, Stephan; Scalco, Andrea; Tur, Elena M.; Tommasi, Francesco; Delfini, Keren
Abstract: The present study uses agent-based modeling (ABM) to examine the effectiveness of a nudge policy for improving recycling behavior. In our simulation, agents' recycling behavior is computed by components of the Theory of Planned Behaviour (i.e., attitudes, perceived behavioral control, social norms) and influenced by other agents as well as their surrounding (i.e., amount of waste in the area). The simulation, based on real data from a Taiwan community district, confirms realistic recycling trends and demonstrates the usefulness and reliability of ABM as a method to examine the effectiveness of waste management policies. An additional step in our simulation was to manipulate the amount of waste in the community to test the effect of a nudge policy based on social norms. Results showed that the policy increases recycling activity, but predominantly in low waste scenarios. This suggests that nudges, in the form of norm-based policies, can be an effective solution to enhancing people's recycling behavior under specific circumstances. Highlights: Using an ABM approach to investigate the effects of social norms (SN) on recycling behavior. The level of trash already present in the environment is an important moderator of recycling behavior. Nudges inspired by descriptive SN are powerful if preceded by nudges inspired by injunctive SN.