Mapping drug smuggling networks in Japan: a social network analysis of trial documents

Martina Baradel and Niles Breuer

Global Crime, 2024, vol. 25, issue 3-4, 220-241

Abstract: This paper addresses a significant gap in drug market literature by examining high-level drug trafficking networks in Japan. We focus on three aspects: the structure of drug importation networks, the impact of transport methods on these structures, and the role of Japan’s mafia, the yakuza. Using novel statistical techniques that extend exponential random graph models (ERGMs) to multi-network samples, we analyse 573 Japanese trial documents on wholesale drug importation. We test the theory that trafficking operations with higher information-processing demands exhibit more efficiency-oriented network structures, while governance-type groups avoid expanding into trade activities. Our findings support these theories, showing that networks with higher information-processing demands are more efficiency-oriented but maintain security. Conversely, smaller networks with simpler transport methods prioritise security and concealment. Additionally, the yakuza do not organisationally engage in drug trafficking; when involved, yakuza members act as independent entrepreneurs.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/17440572.2024.2375241 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:fglcxx:v:25:y:2024:i:3-4:p:220-241

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/FGLC20

DOI: 10.1080/17440572.2024.2375241

Access Statistics for this article

Global Crime is currently edited by Carlo Morselli

More articles in Global Crime from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().