Work

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

Year: 2017

Type: article

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 ( ) 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.

Source: Journal of Artificial Societies and Social Simulation

DOI: 10.18564/jasss.3269

Authors: Ruggero Rangoni, Wander Jager

Institution: University of Groningen

Language: English

Topic: Environmental Education and Sustainability

Subfield: Management, Monitoring, Policy and Law

Field: Environmental Science

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $1,300