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

Ruggero Rangoni () and Wander Jager ()
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Journal of Artificial Societies and Social Simulation, 2017, vol. 20, issue 2, 1

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.

Keywords: Littering; Goal Frame Theory; Tipping Point; Norms (search for similar items in EconPapers)
Date: 2017-03-31
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