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The main purpose of this paper is to analyze what happens to a business model when the governance of the focal organization changes, particularly when it has to re-shape its transactional network.

The paper reviews literature on governance structure of criminal organizations and uses two case studies to show two different approaches in re-shaping the business transactional network after the seizure from Mafia organization.

The paper finds three different approaches about governance structure in criminal organizations and describes what happens to a business model when the governance of the focal organization changes as is the case of the seizure and confiscation of Mafia businesses. The paper shows that when a judicial administrator is able to effectively build a new transactional network, the business he manages can survive and can also give good performance.

The paper provides two business cases, but this is not enough to give empirical evidence; this could be provided through other case studies or through quantitative methods using surveys or data provided by the Italian courts.

The paper has some potential managerial implications, in particular for the judicial administrator. He should encourage the construction of a new transactional network, first analyzing the existing network, going deeply into the content and the motivators of the relationships with the stakeholders, and deciding if such relationships can be re-formulated or must be left.

The originality of the paper is that it analyzes criminal organizations using well-known approaches, applying them to the case of seized and confiscated business.

Target prioritization is routinely done among law enforcement agencies, but the criteria to establish which targets will lead to the most crime reduction are neither systematic, nor do they take into account the networks in which offenders are embedded. The purpose of this paper is to propose network capital as a guide for prioritization exercises. The approach simultaneously considers a participant’s network centrality and their crime-affiliated attributes.

Data on all police interactions are used to map the social networks of two mutually connected police targets from a mid-size city in British Columbia, Canada. Network capital is captured by combining the extent to which individuals act as brokers between otherwise unconnected individuals (betweenness centrality), their number of contacts in the network (degree centrality), and whether they have a criminal record, gang ties, and a firearm carrier status.

The network comprises 101 associates, with nine mutual contacts amongst the two targets, and half of the network having a crime-affiliated attribute. Network capital directed the prioritization process to seven associates who stood out. Targeting strategies from two different investigative outcomes are compared.

The specific recommendations of the study can only be interpreted within the context of the initial targets around which the network was constructed. As a prioritization approach, however, network capital is generalizable to other contexts with implications for law enforcement officials and, more broadly, the community.

The study provides insights into the practical application of network analysis with already existing police data. Network capital is data driven, which comes with its own limitations, but which constitutes an improvement over purely informal approaches to target prioritization.

Purpose – Criminal groups have long been central to explanations of crime and deviance. Yet, challenges in measuring their dynamic and transient nature meant that group-level explanations were often displaced in favor of individual-level ones. This chapter outlines how network methods provide a powerful tool for modeling the dynamic nature of criminal groups.

Approach – The chapter starts by providing a brief introduction to social network analysis, including key concepts and terminology. The chapter then focuses on the types of relational data available to study criminal groups, and how network methods can be used to delineate group boundaries. The chapter concludes by presenting a framework for understanding group dynamics from a network perspective, describing the contributions of network analysis to theories of group processes.

Findings – Network methods have provided meaningful advances to the study of group dynamics, leading scholars to revisit assumptions about the impact of group’ structure on delinquent behavior. Network studies of group dynamics have primarily focused on the cohesion–delinquency link (within-group structure) and the social contagion of conflict (between-group structure), highlighting important opportunities for the intersection of these two inquiries.

Value – Network methods provide a means to revisit and extend theories of crime and delinquency with a focus on social structure. The unique affinity between group dynamics and network methods highlights immense opportunities for expanding the knowledge of collective trajectories.

In North Korea, illicit activities directly or implicitly supported by the North Korean Government are an integral part of the nation’s survival strategies. This study aims to discuss how North Korea directs its national power and resources to facilitate narcotics trafficking activities and how the role of North Korean State in the narcotics trafficking network has changed over time since the 1970s.

Analysis of narcotics trafficking in North Korea has primarily involved a review of secondary data, including previous academic research in this field, news articles, circumstantial and forensic evidence, seizure data and defector testimony.

This paper argues that prior to 2000, North Korea was systematically and directly engaged in narcotics production and distribution. The nation state could be regarded as a form of “criminal sovereignty”, because the sovereign state is itself criminal. However, in the post-2000s, North Korea’s Government began to gradually withdraw from narcotics trafficking, creating space for various non-state actors – such as criminal syndicates, private traders and local officials – to enter the once-monopolistic network. De-centralisation of narcotics trafficking network in North Korea suggests that the state’s criminal sovereignty may be gradually eroding and the pattern of state criminalisation in North Korea may be transforming.

This paper draws on theories concerning state criminalisation to understand the changing dynamics of narcotics trafficking network in North Korea.

This paper seeks to explore the applicability of the eclectic framework of international production in explaining the growth of transnational crime groups.

The paper adopts a comparative discussion perspective. It examines a number of both similarities and differences between legitimate and illegal international business organizations suggesting that similarities between the two are sufficient to ensure the usefulness of existing explanatory frameworks which focus on ownership, location and internalization (OLI) advantages.

Similarities are apparent in the growing internationalization of criminal activities and the emergence of network structures. Key changes in the business environment, particularly globalization and technological change, are affecting both legitimate and illegal business. Like legitimate business, international crime is undergoing significant change. Increased diversification is apparent as traditional criminal activities – gambling, loan sharking and prostitution – are combined with cross‐border automobile smuggling, art and archaeological theft, arms trafficking, trade in illegal wildlife products and credit‐card fraud.

The discussion suggests a “mirroring” of legitimate international business strategies and structures by transnational criminal organizations. This raises interesting policy implications as to how such organisations might develop over time and how policy could be used to contain such activities.

The purpose of this paper is to provide an analysis of the changing practices of cattle rustling in Kenya from a relatively small isolated and opportunistic activity to a much more planned and systematic entrepreneurial business involving collusion and corruption.

This paper provides a conceptual approach using key literature and documentary evidence to show how, in the northern part of Kenya, cattle rustling is common occurrence with criminals taking advantage of remote rural environments with minimal surveillance and consequently less opportunity of being stopped and searched by police.

Results evidence significant differences in how rustling is perceived and valorized. Rustling in Kenya is now an entrepreneurial crime with the involvement of rural organized criminal gangs (ROCGs), who are operating in food supply chains throughout Kenya and the African continent.

This paper suggests that a more nuanced understanding of the entrepreneurial nature of some illegal practices in a rural Kenya is necessary and how it requires multi-agency investigation.

The paper is unique in that it considers how cattle rustling is becoming a more entrepreneurial crime than previously. Little prior work on this subject exists in Kenya. The paper utilizes the framework of Smith and McElwee (2013) on illegal enterprise to frame cattle rustling as an entrepreneurial crime.

The social network analysis of criminal networks at both the ego and socio-centric level is well established. This purpose of this study is to expand this literature with a social capital analysis of a criminal network. The focus of the analysis will be the recent egregious investment fraud of Bernard L. Madoff Investment Securities (BLMIS).

This research involves a case study of the BLMIS financial fraud. The article uses a social capital theoretical lens, with archival sources taken from the court records of Madoff v. NY to include victim impact statements and the defendant’s Plea Allocution.

Financial crime literature can be expanded with a social capital analysis which facilitates a socio-economic analysis of ego-centric criminal networks.

Each financial crime is of its time; however, there are recurring socio-economic network characteristics that could be applied to develop an understanding of criminal networks.

Any understanding of financial crime, including contemporary instances of criminal innovation, such as cyber-crime, can be enhanced with a social capital analysis of criminal networks.

A social capital analysis of financial crime draws attention to “human factors” in criminal networks that are integral to this form of crime.

Addresses the rapid expansion of computer connectivity and the opportunities provided for criminals to exploit security vulnerabilities in the online environment.

International efforts to combat cyber‐crime are reviewed by evaluating the forms of mutual legal assistance (MLA) now in place.

Cyber‐crime is often traditional crime (e.g. fraud, identify theft, child pornography) albeit executed swiftly and to vast numbers of potential victims, as well as unauthorised access, damage and interference to computer systems. Most detrimental are malicious and exploit codes that interrupt computer operations on a global scale and along with other cyber‐crimes threaten e‐commerce. The cross‐national nature of most computer‐related crimes have rendered many time‐honoured methods of policing both domestically and in cross‐border situations ineffective even in advanced nations, while the “digital divide” provides “safe havens” for cyber‐criminals. In response to the threat of cyber‐crime there is an urgent need to reform methods of MLA and to develop trans‐national policing capability.

The international response is briefly outlined in the context of the United Nations (UN) Transnational Organised Crime Convention (in force from September 2003) and the Council of Europe's innovative Cyber‐crime Convention (in force from July 2004). In addition, the role of the UN, Interpol, other institutions and bi‐lateral, regional and other efforts aimed a creating a seamless web of enforcement against cyber‐criminals are described.

The potential for potent global enforcement mechanisms are discussed.

This study builds on the extant research of the authors on illegal rural enterprise (IRE). However, instead of taking a single or micro case approach within specific sections of the farming and food industries we examine the concept holistically from a macro case perspective. Many IRE crimes simply could not be committed without insider knowledge and complicity, making it essential to appreciate this when researching or investigating such crimes.

Using data from published studies, we introduce the theoretical concept of “Shadow infrastructure” to analyse and explain the prevalence and endurance of such criminal enterprises. Using a multiple case approach, we examine data across the cases to provide an analysis of several industry wide crimes—the illicit halal meat trade; the theft of sheep; the theft of tractors and plant; and the supply of illicit veterinary medicines.

We examine IRE crimes across various sectors to identify commonalities in practice and in relation to business models drawing from a multidisciplinary literature spanning business and criminology. Such enterprises can be are inter-linked. We also provide suggestions on investigating such structures.

We identify academic and practical implications in relation to the investigation of IRE crime and from an academic perspective in relation to researching the phenomenon.

This study combines data from numerous individual studies from a macro perspective to provide practical solutions to a multifaceted problem.

Telecommunication (telecom) fraud is one of the most common crimes and causes the greatest financial losses. To effectively eradicate fraud groups, the key fraudsters must be identified and captured. One strategy is to analyze the fraud interaction network using social network analysis. However, the underlying structures of fraud networks are different from those of common social networks, which makes traditional indicators such as centrality not directly applicable. Recently, a new line of research called deep random walk has emerged. These methods utilize random walks to explore local information and then apply deep learning algorithms to learn the representative feature vectors. Although effective for many types of networks, random walk is used for discovering local structural equivalence and does not consider the global properties of nodes.

The authors proposed a new method to combine the merits of deep random walk and social network analysis, which is called centrality-guided deep random walk. By using the centrality of nodes as edge weights, the authors’ biased random walks implicitly consider the global importance of nodes and can thus find key fraudster roles more accurately. To evaluate the authors’ algorithm, a real telecom fraud data set with around 562 fraudsters was built, which is the largest telecom fraud network to date.

The authors’ proposed method achieved better results than traditional centrality indices and various deep random walk algorithms and successfully identified key roles in a fraud network.

The study used co-offending and flight record to construct a criminal network, more interpersonal relationships of fraudsters, such as friendships and relatives, can be included in the future.

This paper proposed a novel algorithm, centrality-guided deep random walk, and applied it to a new telecom fraud data set. Experimental results show that the authors’ method can successfully identify the key roles in a fraud group and outperform other baseline methods. To the best of the authors’ knowledge, it is the largest analysis of telecom fraud network to date.