Ceschi A, Sartori R, Dickert S, Scalco A, Tur EM, Tommasi F, Delfini K. Testing a
norm-based policy for waste management: An agent-based modeling simulation on nudging recycling behavior.
J Environ Manage 2021;
294:112938. [PMID:
34214943 DOI:
10.1016/j.jenvman.2021.112938]
[Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 05/07/2021] [Accepted: 05/08/2021] [Indexed: 06/13/2023]
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.
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