Social Dynamics of Littering and Adaptive Cleaning Strategies Explored Using Agent-Based Modelling

Authored by Ruggero Rangoni, Andwander Jager

Date Published: 2017

DOI: 10.18564/jasss.3269

Sponsors: No sponsors listed

Platforms: NetLogo

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

In this paper we explore how social influence may cause a non-linear transition from a clean to a littered environment, and what strategies are effective in keeping a street clean. To study this, we first implement the Goal Framing Theory of Lindenberg and Steg (2007) in an agent based model. Next, using empirical data from a field study we parameterise the model so we can replicate the results from a field study. Following that, we explore how different cleaning strategies perform. The results indicate that an adaptive/dynamical cleaning regime is more effective and cheaper than pre-defined cleaning schedules.

Tags

Agent-based modelling behavior environment Norms Interventions Field Goal framing theory Littering Normative conduct Focus theory Signs