Criminal network vulnerabilities and adaptations

Abstract

The current paper aimed to investigate the effectiveness of five law enforcement interventions in disrupting and dismantling criminal networks. We tested three law enforcement interventions that targeted social capital in criminal networks (betweenness, degree and cut-set) and two interventions that targeted human capital (actors who possess money and those who possess precursor chemicals). These five interventions are compared with each other and with random (opportunistic) removal of actors in two settings: (i) with network adaptation incorporated into the simulations and (ii) without network adaptation. Results illustrate that the removal of actors based on betweenness centrality was the most efficient strategy, leading to network disruption in the least number of steps and was relatively consistent across replications. Targeting actors who possessed money was the second most effective overall and was also relatively consistent in its disruptive effect.