Fighting pickpocketing using a choice-based resource allocation model

Inspired by European actions to fight organized crimes, we develop a choice-based resource allocation model that can help policy makers to reduce the number of pickpocket attempts. In this model, the policy maker needs to allocate a limited budget over local and central protective resources as well as over potential pickpocket locations, while keeping in mind the thieves’ random preferences towards potential pickpocket locations. We prove that the optimal budget allocation is proportional in (i) the thieves’ sensitivity towards protective resources and (ii) the initial attractiveness of the potential pickpocket locations. On top of this, we also study two alternatives of our choice-based resource allocation model: one where pickpocket probabilities are enforced to be equal over the pickpocket locations, and one where the decision-making process of the thief becomes deterministic, with known preferences, as observed by the policy maker. For both alternatives, we also derive the optimal budget allocation and compare it with the initial budget allocation using numerical experiments. Finally, we illustrate how these optimal budget allocations perform against various others budget allocations, proposed by policy makers from the field.