Social dynamics of littering and adaptive cleaning strategies explored using agent-based modelling

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.