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Criminal organizations exploit their presence on territories and local communities to recruit new workforce in order to carry out their criminal activities and business. The ability to attract individuals is crucial for maintaining power and control over the territories in which these groups are settled. This study proposes the formalization, development and analysis of an agent-based model (ABM) that simulates a neighborhood of Palermo (Sicily) with the aim to understand the pathways that lead individuals to recruitment into organized crime groups (OCGs). Using empirical data on social, economic and criminal conditions of the area under analysis, we use a multi-layer network approach to simulate this scenario. As the final goal, we test different policies to counter recruitment into OCGs. These scenarios are based on two different dimensions of prevention and intervention: (i) primary and secondary socialization and (ii) law enforcement targeting strategies., 15 pages, 2 figures. Paper accepted and in press for the Proceedings of the 2019 Social Simulation Conference (Mainz, Germany)

While indicators assessing the quality of life often comprise measures of crime or fear of crime, these components usually refer to property or violent crimes. More complex crimes, which may significantly impact on the social, economic, and political conditions of local communities, are often overlooked, mostly due to problems in adequately measuring the levels of e.g. organised crime and corruption. Indeed, despite the growing scholarly attention, measurements of organised crime are rare and frequently affected by important methodological limitations. This study addresses this issue by proposing the Mafia Presence Index (MPI), a composite indicator measuring the presence of the mafias in Italy. The MPI aggregates variables measuring different dimensions of mafia presence, namely the presence and activities of mafia groups, mafia violence, and infiltration in politics and the economy. Furthermore, the analysis explores the validity and robustness of the MPI by considering possible alternative variables and by assessing the impact of different calculation strategies. Results show that the MPI is a parsimonious and consistent measure of mafia presence, relying on a core set of five variables directly related to mafia presence. The index is also robust to different calculation methods and is negatively associated with the most popular indexes measuring the quality of life in Italy.

This chapter presents a systematic review of the social, psychological, and economic factors relating to involvement and recruitment into organized crime groups (OCGs), including mafias, drug trafficking organizations (DTOs), gangs, and other criminal organizations. This review has three objectives: (i) identifying the most commonly reported factors leading to recruitment into OCGs, (ii) highlighting whether these factors are independent of one other or they are correlated, and (iii) assessing the validity and generalizability of research findings. The review searched all possible relevant studies indexed in selected databases and published in five languages (i.e. English, French, German, Italian, and Spanish), without limitations as to their year of publication or geographic origin. Starting from 48,731 potentially eligible records, integrated with experts’ suggestions, this systematic review includes 47 empirical studies employing quantitative, qualitative, or mixed-methods approaches. The findings show that social and economic factors are the most commonly reported factors relating to recruitment into OCGs, while psychological factors are marginal. Although factors are highly interrelated and shared across OCGs, their predominance varies across types of criminal organizations. For instance, individuals join mafias and gangs attracted by strong group identity, whereas individuals enter DTOs mainly for financial gain. In light of these findings, recommendations for future research and implications for prevention policies are discussed.

Brokerage is crucial for dark networks. In analyzing communications among criminals, which naturally induce bipartite networks, previous studies have focused on the classic Freeman's betweenness, conceived for one-mode matrices and possibly biasing the results. We explore different betweenness centrality including three inspired by the dual projection approach recently suggested by Everett and Borgatti 2013. We test these measures in identifying criminal leaders in a meeting participation network. Despite the expected high correlations among them, the measures yield different node rankings, capturing different characteristics of brokerage. Overall, the dual projection approaches show higher success than classic approaches in identifying the criminal leaders.

Criminal organizations tend to be clustered to reduce risks of detection and information leaks. Yet, the literature exploring the relevance of subgroups for their internal structure is so far very limited. The paper applies methods of community analysis to explore the structure of a criminal network representing the individuals’ co-participation in meetings. It draws from a case study on a large law enforcement operation (“Operazione Infinito”) tackling the ‘Ndrangheta, a mafia organization from Calabria, a southern Italian region. The results show that the network is indeed clustered and that communities are associated, in a non-trivial way, with the internal organization of the ‘Ndrangheta into different “locali” (similar to mafia families). Furthermore, the results of community analysis can improve the prediction of the “locale” membership of the criminals (up to two thirds of any random sample of nodes) and the leadership roles (above 90% precision in classifying nodes as either bosses or non-bosses). The implications of these findings on the interpretation of the structure and functioning of the criminal network are discussed.

The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.

Social network analysis has often been applied to the communications within criminal groups to understand their internal structure and dynamics. While access to the content of communications may be restricted by constitutional and procedural constraints, this article applies advanced network analysis techniques based on spectral embedding to telephone communications data. Spectral embedding facilitates deeper analysis by embedding the graph representing a social network in a geometric space such that Euclidean distance reflects pairwise node dissimilarity. This enables drawing a network in ways that accurately reflect the structure of the underlying group, and computing properties directly from the embedding. We illustrate spectral approaches for two Ndrangheta drug-smuggling networks, and extend them to a) examine triad structure (through the identification of the Simmelian backbone), which elicits key members, and b) to display temporal properties, which illustrates changing group structure. The results show that the two groups, although having the same purpose and coming from the same criminal milieu, have substantially different internal structure which was not detectable using conventional social-network approaches. The techniques presented in this study may support law enforcement in the early stages of an investigation.

This study provides a methodology with which to estimate the volumes and revenues of the illicit cigarette market at the subnational level. It applies the methodology to Italy for a 4-year period (2009–2012), enabling assessment of the prevalence of the illicit trade across years and regions. Notwithstanding the alleged importance of mafias, the results provide a more complex picture of the Italian illicit tobacco market. The maximum total revenues from the illicit trade in tobacco products (ITTP) increased from €0.5 bn in 2009 to €1.2 bn in 2012. The prevalence of illicit cigarettes varies significantly across regions, because of the proximity to countries with cheaper cigarettes and the possible occurrence of other crime opportunities. Understanding of these factors is crucial for the development of appropriate policies against the ITTP. The methodology may be applicable to all other EU countries, providing detailed, yearly estimates of the illicit market at the subnational level.

Law enforcement agencies have frequently shown skepticism toward the results of the application of social network analysis to organized crime. Indeed, most studies to date have analyzed data (e.g. telephone intercepts) whose content was already well-known to the practitioners. Shifting the focus to data on mafia meetings, this chapter explores whether network analysis can identify the bosses in a large mafia network. The analysis relies on data from a large-scale investigation on the presence of the ‘Ndrangheta, a mafia from the Southern Italian region of Calabria. Operation Infinito identified several mafia families and tracked a number of mafia meetings. The results show that betweenness centrality is the most significant predictor of leadership in the mafia. A logistic regression model, using network measures as predictors, is able successfully to predict the position (boss or other) of 92 % of the individuals in the network. If supported by further studies, network analysis of meetings may provide law enforcement agencies with information useful for identifying the bosses of criminal organizations.

Organised crime is a field vulnerable to mythical numbers, i.e. exaggerated estimates lacking empirical support, but acquiring acceptance through repetition. The figures on mafia proceeds in Italy are a striking example of this problem. This study proposes an estimation of mafia proceeds in Italy from nine criminal activities (sexual exploitation of women, illicit firearms trafficking, drug trafficking, counterfeiting, the illicit cigarette trade, illicit gambling, illicit waste disposal, loan sharking, and extortion racketeering) by region and type of mafia (Cosa Nostra, Camorra, ‘Ndrangheta, Apulian mafias, and other mafias). The results estimate yearly mafia proceeds at approximately €10.7 bn (0.7% of the Italian GDP), discussing the impact on the regional and national economies and the differences among the types of mafias as to their geographical sources of revenues.

In recent years, official reports, the academic literature and the media have dedicated increased attention to foreign criminal groups in Italy. The actual nature of foreign criminal organisations, and particularly their comparability to Italian mafias, is still under researched. This study explores the application of the offence of mafia-type association (Article 416-bis of the Criminal Code) to foreign criminal organisations. It analyses the theoretical applicability of the offence as well as statistics and jurisprudence of relevant cases. Results show that the offence of mafia-type association is theoretically applicable to foreign criminal groups. However, the number of cases is very low. This is due to two concurring factors: foreign criminal groups do not always have the same characteristics of domestic mafias (stability, continuity, use of the mafia method); the evidentiary difficulties have brought the prosecution and the courts to apply other offences, carrying high penalties but without the need to prove the mafia method.

The paper analyses the social organization of two drug trafficking mafia groups. The groups belonged to the 'Ndrangheta, a mafia from Calabria, a Southern Italian region. Based on judicial sources, multiple linked analyses examine the tasks, statuses and social network structures of the two groups. The analyses showed that the formal hierarchy of the mafias does not play a relevant role in the organization of drug trafficking. At the same time, the two groups exhibited a particular organizational structure, with a clear division of tasks and signals of status differentiation among the members. Remarkably, the analyses highlighted the strategic positioning of the criminal leaders. The most prominent participants (high-status individuals) were not those most involved in criminal activities (i.e. the most central in the network). This positioning strategy allowed minimizing the risks and ensuring effective management of smuggling operations. Criminal leaders were able to control the activities thanks to the specific cultural, family, kinship and ritual ties characterizing the mafias. This specific organizational structure may explain the strong resilience of mafias to law enforcementaction. Implications for both research and law enforcement are discussed.

PurposeThe paper aims at expanding knowledge on the presence of organized criminal groups in public contract procurement in the south of Italy. It seeks to highlight how the capabilities of law enforcement agencies could be enhanced by means of criminological models.Design/methodology/approachThe paper sets out a criminological model with which to assess the general and specific risks of the infiltration of public procurement in the south of Italy by organized crime (OC).FindingsAccording to the geographical risk assessment, infiltration by OC of public procurement seems to be widespread in some areas of south Italy, especially Sicily, Calabria and Campania. On the other hand, the specific risk may increase according to certain features of the company and its representatives, the value of the contract, the low specialization of the activities required by the public contract.Originality/valueThe paper describes a criminological model with which to assess the general and specific risk of infiltration by OC of public procurement in south Italy.

The last meeting of the MARC Consortium Board (Paris, 27–28 October 2005) approved a general and flexible legislative crime risk mechanism which could be used for a variety of possible applications. Since then, further steps have been taken to implement the mechanism, and a pilot study on public procurement sector has been carried out to test its functioning. It highlighted some critical issues and weaknesses of the Legislative Crime Risk formula, the related indicators and the scoring system. Accordingly, the present article introduces some adjustments to the model and tackles those issues not yet addressed. It sets out the Legislative Crime Risk formula and its components, states rules for assessing each component, refines the indicators that operationalize the variables, and provides information about the reliability of a crime risk assessment.

Through a novel data set comprising the criminal records of 11,138 convicted mafia offenders, we compute criminal career parameters and trajectories through group-based trajectory modeling. Mafia offenders report prolific and persistent careers (16.1 crimes over 16.5 years on average), with five distinct trajectories (low frequency, high frequency, early starter, moderate persistence, high persistence). While showing some similarities with general offenders, the trajectories of mafia offenders also exhibit significant differences, with several groups offending well into their middle and late adulthood, notwithstanding intense criminal justice sanctions. These patterns suggest that several mafia offenders are life-course persisters and career criminals and that the involvement in the mafias is a negative turning point extending the criminal careers beyond those observed in general offenders.