Rangoni, Ruggero and Jager, Wander (2017) Social Dynamics of Littering and Adaptive Cleaning Strategies Explored Using Agent-Based Modelling. Journal of Artificial Societies and Social Simulation, 20 (2). ISSN 1460-7425
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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.
Item Type: | Article |
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Subjects: | STM One > Computer Science |
Depositing User: | Unnamed user with email support@stmone.org |
Date Deposited: | 07 Feb 2024 10:29 |
Last Modified: | 17 May 2024 10:34 |
URI: | http://publications.openuniversitystm.com/id/eprint/1675 |