Breaking the Chain: Division Norms and Criminal Deterrence

2026-08-13

AI Summary

This study addresses the problem of dismantling organized criminal groups at minimal deterrence cost, accounting for the dynamic interplay among member turnover, deterrence allocation, and norms governing payoff distribution. A three-stage game-theoretic model is developed: first, a coalition payoff-sharing rule is established; second, an authority allocates deterrence resources without knowledge of the eventual coalition structure; and third, undeterred members reconfigure coalitions. Incorporating population monotonicity into the allocation norm and integrating the Shapley value, coalition formation theory, and shortest-path graph algorithms, the analysis demonstrates that under this condition, the minimal deterrence budget equals the cost of the shortest sequential disintegration path. In contrast, when the Shapley value is employed, all disintegration paths incur identical—and maximal—deterrence costs, thereby revealing the critical influence of payoff allocation rules on dismantling efficiency.

Abstract

In organized crime, membership moves fastest, deterrence capacity moves more slowly, and division norms move slowest. We model this as a three-stage game: division norms fix how every possible coalition divides its proceeds; the authority then attaches deterrence capacity to named members, before knowing which coalition will form; membership adjusts last, around whoever remains undeterred. Under population-monotone division, the minimum deterrence budget is the cost of a shortest dismantling path, removing one member at a time. When the Shapley value is population monotone, it uniquely maximizes this budget by making every path equally costly.

Problem

• organized crime
• criminal deterrence
• division norms
• dismantling path
• Shapley value

Innovation

• division norms
• criminal deterrence
• population monotonicity
• Shapley value
• dismantling path