Many illicit markets are transnational in nature: illicit products are consumed in a country different from the one in which they were produced. Therefore, reconstructing the trafficking network and estimating the size of cross-border illicit flows are crucial steps to gain better understanding of these crimes and to enforce actions aimed at countering them. In this respect, the present study outlines a methodology with which to map and size illicit flows and applies it in estimation of transnational cigarette trafficking flows. The proposed methodology traces each step in the paths followed by illicit cigarettes flowing from their origin to the final consumption country and then estimates the quantity of cigarettes moving between each pair of countries. It exploits data on consumption of illicit cigarettes in 57 countries located in Europe, the Middle East, Central Asia, and North Africa, together with data on seizure cases and geographical information for 158 countries worldwide. These data are combined by a function that assigns a likelihood value of illicit cigarettes being transported between any pair of countries. An algorithm is then implemented in order to identify the most likely paths from the origin to the destination country. By merging results for all the different combinations of origins and destinations, this study estimates the size of all cross-border illicit flows and reconstructs a dynamic transnational cigarette trafficking network for the period 2008–2017. The results highlight the multifaceted role of countries in the cigarette trafficking network, the emergence of identifiable cigarette trafficking routes, and the evolution over time of the structure of this transnational illicit network. Finally, the paper discusses how the methodology developed could be adapted to the study of other transnational crimes.
Meneghini, C., Aziani, A., Dugato, M. (2020). Modeling the structure and dynamics of transnational illicit networks: an application to cigarette trafficking. APPLIED NETWORK SCIENCE, 5(1) [10.1007/s41109-020-00265-3].
Modeling the structure and dynamics of transnational illicit networks: an application to cigarette trafficking
Aziani, A;
2020
Abstract
Many illicit markets are transnational in nature: illicit products are consumed in a country different from the one in which they were produced. Therefore, reconstructing the trafficking network and estimating the size of cross-border illicit flows are crucial steps to gain better understanding of these crimes and to enforce actions aimed at countering them. In this respect, the present study outlines a methodology with which to map and size illicit flows and applies it in estimation of transnational cigarette trafficking flows. The proposed methodology traces each step in the paths followed by illicit cigarettes flowing from their origin to the final consumption country and then estimates the quantity of cigarettes moving between each pair of countries. It exploits data on consumption of illicit cigarettes in 57 countries located in Europe, the Middle East, Central Asia, and North Africa, together with data on seizure cases and geographical information for 158 countries worldwide. These data are combined by a function that assigns a likelihood value of illicit cigarettes being transported between any pair of countries. An algorithm is then implemented in order to identify the most likely paths from the origin to the destination country. By merging results for all the different combinations of origins and destinations, this study estimates the size of all cross-border illicit flows and reconstructs a dynamic transnational cigarette trafficking network for the period 2008–2017. The results highlight the multifaceted role of countries in the cigarette trafficking network, the emergence of identifiable cigarette trafficking routes, and the evolution over time of the structure of this transnational illicit network. Finally, the paper discusses how the methodology developed could be adapted to the study of other transnational crimes.File | Dimensione | Formato | |
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