Amsterdam has become increasingly popular as a tourist destination. Visitor numbers increased sharply with an increase of 24% in 6 years. This resulted in 19 million visitors in 2017 – 2 million more than last year. This strong increase contributes to the crowdedness in Amsterdam and challenges the city’s liveability. Littering and dirtier streets is one of the main nuances of increased crowdedness.
Within the City Simulator Lab project from the Amsterdam Institute for Advanced Metropolitan Solutions (the AMS-Institute), researchers from both Wageningen University and Delft University collaborate to develop tools to explore the complex dynamics of modern cities. One of the approached used is agent-based modelling. Agent-Based Model (ABM) is a modeling concept that enables spatial modelers to describe (spatial) processes from the bottom-up.
Several theories try to explain littering behavior such as the broken window theory (Wilson and Kelling, 1982). Theory-based agent-based models can be used to explore littering behavior and develop scenarios of possible interventions.
- To identify and explore the most relevant social theories on littering
- To develop an agent-based model of littering behavior in collaboration with AMS researchers and the municipality of Amsterdam
- To explore the impact of possible interventions aiming to improve littering and dirty streets in the ABM
- To validate the model with empirical data
- Rangoni, R., Jager, W., 2017. Social Dynamics of Littering and Adaptive Cleaning Strategies Explored Using Agent-Based Modelling. J. Artificial Societies and Social Simulation 20(2)
- Enthusiasm for and if possible experience with agent-based modelling
- Willingness to commit to learning agent-based modelling platform
- Interest in social theory and social simulation
- Interest in empirical research
Theme(s): Modelling & visualisation, Human – space interaction