Luis G. Nardin

Simulating protection rackets: a case study of the Sicilian Mafia

Protection racketeering groups are powerful, deeply entrenched in multiple societies across the globe, and they harm the societies and economies in which they operate in multiple ways. These reasons make their dynamics important to understand and an objective of both scientific and application-oriented interest. Legal and social norm-based approaches arguably play significant roles in influencing protection racket dynamics. We propose an agent-based simulation model, the Palermo Scenario, to enrich our understanding of these influences and to test the effect of different policies on protection racket dynamics. Our model integrates the legal and the social norm-based approaches and uses a complex normative agent architecture that enables the analysis of both agents’ behaviours and mental normative representations driving behaviour. We demonstrate the usefulness of the model and the benefits of using this complex normative architecture through a case study of the Sicilian Mafia.

The Norm-Signaling Effects of Group Punishment: Combining Agent-Based Simulation and Laboratory Experiments

Punishment plays a crucial role in favoring and maintaining social order. Recent studies emphasize the effect of the norm-signaling function of punishment. However, very little attention has been paid so far to the potential of group punishment. We claim that when inflicted by an entire group, the recipient of punishment views it as expressing norms. The experiments performed in this work provide evidence that humans are motivated not only by material incentives that punishment imposes but also by normative information that it conveys. The same material incentive has a different effect on the individuals’ future compliance depending on the way it is implemented, having a stronger effect when it also conveys normative information. We put forward the hypothesis that by inflicting equal material incentives, group punishment is more effective in enhancing compliance than uncoordinated punishment, because it takes advantage of the norm-signaling function of punishment. In support of our hypothesis, we present cross-methodological data, that is, data obtained through agent-based simulation and laboratory experiments with human subjects. The combination of these two methods allows us to provide an explanation for the proximate mechanisms generating the cooperative behavior observed in the laboratory experiment.

Planning horizon affects prophylactic decision-making and epidemic dynamics

The spread of infectious diseases can be impacted by human behavior, and behavioral decisions often depend implicitly on a planning horizon—the time in the future over which options are weighed. We investigate the effects of planning horizons on epidemic dynamics. We developed an epidemiological agent-based model (along with an ODE analog) to explore the decision-making of self-interested individuals on adopting prophylactic behavior. The decision-making process incorporates prophylaxis efficacy and disease prevalence with the individuals’ payoffs and planning horizon. Our results show that for short and long planning horizons individuals do not consider engaging in prophylactic behavior. In contrast, individuals adopt prophylactic behavior when considering intermediate planning horizons. Such adoption, however, is not always monotonically associated with the prevalence of the disease, depending on the perceived protection efficacy and the disease parameters. Adoption of prophylactic behavior reduces the epidemic peak size while prolonging the epidemic and potentially generates secondary waves of infection. These effects can be made stronger by increasing the behavioral decision frequency or distorting an individual’s perceived risk of infection.

Modelling Extortion Racket Systems: Preliminary Results

Mafias are highly powerful and deeply entrenched organised criminal groups that cause both economic and social damage. Overcoming, or at least limiting, their harmful effects is a societally beneficial objective, which renders its dynamics understanding an objective of both scientific and political interests. We propose an agent-based simulation model aimed at understanding how independent and combined effects of legal and social norm-based processes help to counter mafias. Our results show that legal processes are effective in directly countering mafias by reducing their activities and changing the behaviour of the rest of population, yet they are not able to change people’s mind-set that renders the change fragile. When combined with social norm-based processes, however, people’s mind-set shifts towards a culture of legality rendering the observed behaviour resilient to change.

Calibration and Validation

The aim of this chapter is to summarise the problems incurred during the phases of calibrating and validating the extortion racket models used by the GLODERS project. The chapter starts with the discussion of the data availability and summarises shortly the contents of Sect. 4.3. It continues with a discussion of what parameterisation, calibration, sensitivity analysis and validation have to do with each other and ends up with a discussion of the validity of the GLODERS models.

Social Norms and Extortion Rackets

Norms, in their many forms, are all around us. The social world that we inhabit is saturated with them. As others have elegantly put it, ‘from forceps to grave, human life is wrapped in a tightly woven tapestry of rules, standards, and expectations that govern every aspect of social behaviour’ (Anderson & Dunning, 2014). Not only are norms widespread, but they also have powerful effects on our individual and social behaviour, often for the better but sometimes for the worse (Ellickson, 1991; Fehr & Fischbacher, 2004; Henrich et al., 2001). Actions taken within the context of protection rackets are arguably not exempt. Domain-specific norms, regarding paying or supporting behaviour, and domain-general norms such as reciprocity and fairness may shape behaviour there too.

An Agent-Based Model of Extortion Racketeering

Mafias can be considered as criminal organisations that are in the business of producing, promoting, and selling protection. Here, we describe the Palermo Scenario, an agent-based model of protection rackets aimed to deepen our understanding of protection rackets, and help policymakers to evaluate methods for destabilising them. Additionally, since the system is explicitly specified, we can use it to investigate the entire causal pathway from cause to effect: not only from actions to Mafia destabilisation, but also the intermediate actions along the path and actors’ internal mental representations among the population.