scholarly journals Criminal networks in a digitised world: on the nexus of borderless opportunities and local embeddedness

2019 ◽  
Vol 22 (3) ◽  
pp. 324-345 ◽  
Author(s):  
E. Rutger Leukfeldt ◽  
Edward R. Kleemans ◽  
Edwin W. Kruisbergen ◽  
Robert A. Roks
2021 ◽  
pp. 1-26
Author(s):  
Paula Martínez-Sanchis ◽  
Cristina Iturrioz-Landart ◽  
Cristina Aragón-Amonarriz ◽  
Miruna Radu-Lefebvre ◽  
Claire Seaman

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255067
Author(s):  
Annamaria Ficara ◽  
Lucia Cavallaro ◽  
Francesco Curreri ◽  
Giacomo Fiumara ◽  
Pasquale De Meo ◽  
...  

Data collected in criminal investigations may suffer from issues like: (i) incompleteness, due to the covert nature of criminal organizations; (ii) incorrectness, caused by either unintentional data collection errors or intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyze nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data, and to determine which network type is most affected by it. The networks are firstly pruned using two specific methods: (i) random edge removal, simulating the scenario in which the Law Enforcement Agencies fail to intercept some calls, or to spot sporadic meetings among suspects; (ii) node removal, modeling the situation in which some suspects cannot be intercepted or investigated. Finally we compute spectral distances (i.e., Adjacency, Laplacian and normalized Laplacian Spectral Distances) and matrix distances (i.e., Root Euclidean Distance) between the complete and pruned networks, which we compare using statistical analysis. Our investigation identifies two main features: first, the overall understanding of the criminal networks remains high even with incomplete data on criminal interactions (i.e., when 10% of edges are removed); second, removing even a small fraction of suspects not investigated (i.e., 2% of nodes are removed) may lead to significant misinterpretation of the overall network.


Crimen ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 325-345
Author(s):  
Kosara Stevanović

This paper is highlighting the main criminal networks that are trafficking cocaine in Europe, through the lenses of social embeddedness and criminal network theories. We will try to show that social ties between European and Latin American organized crime networks, as well as between different European crime networks, are the main reason for the staggering success of European criminal groups in cocaine trafficking in the 21st century. In the beginning, we lay out the social embeddedness theory and criminal network theory, and then we review the main criminal networks involved in cocaine trafficking in Europe and social ties between them, with special attention to Serbian and Montenegrin criminal networks. At the end of the article, we analyze what role does ethnicity, seen as social ties based on common language and tradition, play in cocaine trafficking in Europe.


2017 ◽  
Vol 1 (2) ◽  
pp. 97
Author(s):  
Li Zhao

Financial constraints may contribute to poverty traps. In the underdeveloped capital markets of rural China, many poor farmers in disadvantaged areas are financially constrained and denied access to formal financial services. A few attempts have been made to reform rural credit co-operatives but with limited impact. Recently, the development of rural mutual co-operatives, as one of new-type rural financial institutions, has gained increasing attention among scholars. While scholars predict that it would be difficult for true co-operative financial institutions to establish themselves and develop in China, this study discusses the conditions for the development of rural mutual co-operatives and identifies their institutional advantages in poverty outreach and financial sustainability. The analysis of the study is largely based on the primary data collected from field investigations and case studies. The study reveals that these organizations have played a significant role in promoting financial inclusion and become a sustainable driver for poverty reduction. This observation is in contrast to the widely-believed prediction that it is hardly probable for true credit co-operatives to establish themselves in modern China due to excessive government intervention and China’s peculiar political culture and social context. The findings also suggest two conditions be necessary to achieve their potential, namely, the co-operation between credit co-operatives and agricultural co-operatives, and local embeddedness with good social connectedness.


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