Opportunistic Organization of Illicit Supply Chains
article
Objective This article aims to propose and utilize an agent-based model to understand how opportunistic behavior in criminal groups contributes to the adaptive capacity of illicit supply
chains. These efforts aim to better understand empirical studies, such as drug trafficking networks, that exhibit patterns of resilience and replacement after enforcement actions. Methods Strategic decisions are modeled dyadic and group contexts using an agent-based approach. To differentiate social relationships, transactions, and activities. Various simulations with different parameters were conducted to analyze the structural, functional, and temporal dependencies of the network. Results Simulation results point group interactions significantly boost the adaptive capacity of illicit supply chains only when interaction frequency is high, whereas dyadic interactions aremore effective for decentralized optimization. Risk-tolerant agents enhance network effectiveness, and low-visibility brokers are crucial for resilience. Lead-based interventions targeting connections of removed agents are more disruptive in low-interaction order networks, while random interventions are less effective in highly connected networks. Conclusion The emergence of low-visibility brokers urges to better understand the behavior of the illicit organization before deploying specific lawenforcement interventions. Simulation offers further insight in how to consider both structural properties and temporal dynamics when designing effective intervention strategies.
chains. These efforts aim to better understand empirical studies, such as drug trafficking networks, that exhibit patterns of resilience and replacement after enforcement actions. Methods Strategic decisions are modeled dyadic and group contexts using an agent-based approach. To differentiate social relationships, transactions, and activities. Various simulations with different parameters were conducted to analyze the structural, functional, and temporal dependencies of the network. Results Simulation results point group interactions significantly boost the adaptive capacity of illicit supply chains only when interaction frequency is high, whereas dyadic interactions aremore effective for decentralized optimization. Risk-tolerant agents enhance network effectiveness, and low-visibility brokers are crucial for resilience. Lead-based interventions targeting connections of removed agents are more disruptive in low-interaction order networks, while random interventions are less effective in highly connected networks. Conclusion The emergence of low-visibility brokers urges to better understand the behavior of the illicit organization before deploying specific lawenforcement interventions. Simulation offers further insight in how to consider both structural properties and temporal dynamics when designing effective intervention strategies.
TNO Identifier
1014796
Source
Journal of Quantitative Crimonoloy