EconPapers    
Economics at your fingertips  
 

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

Ruggero Rangoni () and Wander Jager ()
Additional contact information
Wander Jager: http://www.rug.nl/w.jager

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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://jasss.soc.surrey.ac.uk/20/2/1/1.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2015-67-3

Access Statistics for this article

More articles in Journal of Artificial Societies and Social Simulation from Journal of Artificial Societies and Social Simulation
Bibliographic data for series maintained by Flaminio Squazzoni ().

 
Page updated 2020-07-08
Handle: RePEc:jas:jasssj:2015-67-3