Opportunistic Organization of Illicit Supply Chains

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 are more 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 law enforcement interventions. Simulation offers further insight in how to consider both structural properties and temporal dynamics when designing effective intervention strategies.