Decision Evolution and Governance Optimization in Duty-Free Quota Abuse Smuggling: A Multi-Agent Risk Avoidance Perspective

The pervasive misuse of Duty-Free Quota Abuse Smuggling has seriously undermined fiscal and market order. This study breaks through the traditional model’s assumption of complete rationality and establishes a Multi-Phase Dynamic Decision-Making Model for Duty-Free Quota Abuse Smuggling Chain System, incorporating the risk avoidance preference of illegal actors to analyze strategic interactions within the smuggling chain system. Through theoretical deduction and simulation experiments, the evolution of the system during the decision-making phases of Decentralized Profit-Seeking, Localized Collusive, and Collaborative Profit-Seeking was analyzed, and key intervention points were identified. The study results indicate that smuggling chains will continuously gravitate toward localized collusive; the risk avoidance of illegal actors suppresses local alliance benefits and shortens accumulation cycles; strengthening cost constraints reduces the overall level of smuggling in the system, with Quota Sellers being the most sensitive. Therefore, we propose hierarchical regulation, credit supervision, and differentiated law enforcement to precisely target smuggling chains.