A Policy-oriented Agent-based Model of Recruitment into Organized Crime
Abstract
Criminal organizations exploit their presence on territories and local communities to recruit new workforce in order to carry out their criminal activities and business. The ability to attract individuals is crucial for maintaining power and control over the territories in which these groups are settled. This study proposes the formalization, development and analysis of an agent-based model (ABM) that simulates a neighborhood of Palermo (Sicily) with the aim to understand the pathways that lead individuals to recruitment into organized crime groups (OCGs). Using empirical data on social, economic and criminal conditions of the area under analysis, we use a multi-layer network approach to simulate this scenario. As the final goal, we test different policies to counter recruitment into OCGs. These scenarios are based on two different dimensions of prevention and intervention: (i) primary and secondary socialization and (ii) law enforcement targeting strategies.
Cite
@article{arxiv.2001.03494,
title = {A Policy-oriented Agent-based Model of Recruitment into Organized Crime},
author = {Gian Maria Campedelli and Francesco Calderoni and Mario Paolucci and Tommaso Comunale and Daniele Vilone and Federico Cecconi and Giulia Andrighetto},
journal= {arXiv preprint arXiv:2001.03494},
year = {2020}
}
Comments
15 pages, 2 figures. Paper accepted and in press for the Proceedings of the 2019 Social Simulation Conference (Mainz, Germany)