Tobacco Products Contraband & Counterfeit Risk Identification

Dimitar Dimitrov; Tsvetan Tsvetkov; Georgi Penchev (885); Konstantin Poudin

doi:10.37075/YB.2019.1.06

Authors

Prof. Dr Dimitar Dimitrov Department of National and Regional Security, Faculty of Economics of Infrastructure, UNWE Author
Assoc. Prof. Dr Tsvetan Tsvetkov Department of National and Regional Security, Faculty of Economics of Infrastructure, UNWE Author
Assoc. Prof. Dr Georgi Penchev (885) Department of National and Regional Security, Faculty of Economics of Infrastructure, UNWE Author https://orcid.org/0000-0001-9321-1357
Assoc. Prof. Dr Konstantin Poudin Department of National and Regional Security, Faculty of Economics of Infrastructure, UNWE Author

DOI:

https://doi.org/10.37075/YB.2019.1.06

Keywords:

Tobacco products, Contraband & Counterfeit, Risk identification, Modus operandi, Business process analysis, Structural equation modelling, Spatial-temporal analysis

C15, K10, L66

Abstract

This article presents the results of a research project “Contraband & Counterfeit Risks Identification (Analysis of Business Processes and Spatial Aspects)“, funded by PMI IMPACT. The project has been developed by the team of Department “National and Regional Security” at the UNWE. It is focused on states located on the Balkan route of trafficking from Turkey to the Western Europe, including France, the UK, Germany and Italy. The main focused is on Bulgaria due to its key geographical location.Within the project а unique illicit tobacco trade identification indicator has been developed. It is so called – Illicit Trade in Tobacco Products Indicator (ITTPI). ITTPI can be visualized on an interactive map and could be implemented all over the world. It can be used in the daily work of institutions dealing with the counteractions of the illicit tobacco and tobacco products trade. Despite other methods the model can forecast and detect centers and channels of illicit tobacco trade by visualizing certain regions. The method has been tested in 186 countries and separately for 1744 EU regions (EUROSTAT NUTS3). Model data have been validated by comparison with several studies of other international research centers.

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