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

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

Risultato della ricerca: Contributo in libroContributo a convegno


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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteAdvances in Social Simulation Proceedings of the 15th Social Simulation Conference: 23–27 September 2019
Numero di pagine12
Stato di pubblicazionePubblicato - 2021
Evento15th Social Simulation Conference - Mainz am Rhein
Durata: 23 set 201927 set 2019

Serie di pubblicazioni



Convegno15th Social Simulation Conference
CittàMainz am Rhein


  • Organized Crime


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