liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Illicit Network Dynamics: The Formation and Evolution of a Drug Trafficking Network
Flinders Univ S Australia, Australia.
Linköping University, Department of Management and Engineering, The Institute for Analytical Sociology, IAS. Linköping University, Faculty of Arts and Sciences. Univ Manchester, England; Univ Manchester, England; Univ Melbourne, Australia.
Calif State Univ Long Beach, CA 90840 USA.
2019 (English)In: Journal of quantitative criminology, ISSN 0748-4518, E-ISSN 1573-7799, Vol. 35, no 2, p. 237-258Article in journal (Refereed) Published
Abstract [en]

ObjectivesThe project aims to: (1) investigate structural and functional changes in an Australian drug trafficking network across time to determine ways in which such networks form and evolve. To meet this aim, the project will answer the following research questions: (1) What social structural changes occur in drug trafficking networks across time? (2) How are these structural changes related to roles/tasks performed by network members? (3) What social processes can account for change over time in drug trafficking networks?MethodThe relational data on the network was divided into four two years periods. Actors were allocated to specific roles. We applied a stochastic actor-oriented model to explain the dynamics of the network across time. Using RSiena, we estimated a number of models with the key objectives of investigating: (1) the effect of roles only; (2) the endogenous effect of degree-based popularity (Matthew effect); (3) the endogenous effect of balancing connectivity with exposure (preference for indirect rather than direct connections); (4) how degree-based popularity is moderated by tendencies towards reach and exposure.ResultsPreferential attachment is completely moderated by a preference for having indirect ties, meaning that centralization is a result of actors preferring indirect connections to many others and not because of a preference for connecting to popular actors. Locally, actors seek cohesive relationships through triadic closure.ConclusionsActors do not seek to create an efficient network that is highly centralized at the expense of security. Rather, actors strive to optimize security through triadic closure, building trust, and protecting themselves and actors in close proximity through the use of brokers that offer access to the rest of the network.

Place, publisher, year, edition, pages
SPRINGER/PLENUM PUBLISHERS , 2019. Vol. 35, no 2, p. 237-258
Keywords [en]
Drug trafficking; Social network analysis; Dynamic; Stochastic actor-oriented models; Longitudinalsocial network analysis
National Category
Other Legal Research Criminology
Identifiers
URN: urn:nbn:se:liu:diva-158311DOI: 10.1007/s10940-018-9379-8ISI: 000468597300002OAI: oai:DiVA.org:liu-158311DiVA, id: diva2:1333944
Note

Funding Agencies|Leverhulme Trust [RPG-2013-140]; BA/Leverhulme SRG

Available from: 2019-07-02 Created: 2019-07-02 Last updated: 2025-02-20

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Koskinen, Johan
By organisation
The Institute for Analytical Sociology, IASFaculty of Arts and Sciences
In the same journal
Journal of quantitative criminology
Other Legal ResearchCriminology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 146 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf