A Policy-Oriented Agent-Based Model of Recruitment into Organized Crime

Francesco Calderoni, Gian Maria Campedelli, Tommaso Comunale, Mario Paolucci, Daniele Vilone, Federico Cecconi, Giulia Andrighetto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publicationAdvances in Social Simulation Proceedings of the 15th Social Simulation Conference: 23–27 September 2019
Pages397-408
Number of pages12
DOIs
Publication statusPublished - 2021
Event15th Social Simulation Conference - Mainz am Rhein
Duration: 23 Sep 201927 Sep 2019

Publication series

NameSPRINGER PROCEEDINGS IN COMPLEXITY

Conference

Conference15th Social Simulation Conference
CityMainz am Rhein
Period23/9/1927/9/19

Keywords

  • Organized Crime

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