Collaboration between members of different criminal groups is an important feature of crime that is considered organised, as it allows criminals to access resources and skills in order to exploit illicit economic opportunities. Collaboration across criminal groups is also difficult and risky due to the lack of institutions supporting peaceful cooperation in illicit markets. Thus cross-group collaboration has been thought to take place mostly among small and transient groups. This paper determines whether and under what conditions members of different, larger organised crime groups collaborate with one another. To do so we use intelligence data from the Canadian province of Alberta, centering on criminals and criminal groups engaged in multiple crime types in multiple geographic locations. We apply a multilevel network analytical framework and exponential random graph models using Bayesian techniques to uncover the determinants of cross-group criminal collaboration. We find cross-group collaboration depends not only on co-location, but also on the types of groups to which the criminals are affiliated, and on illicit market overlap between groups. When groups are operating in the same geographically-situated illicit markets their members tend not to collaborate with one another, providing evidence for the difficulty or undesirability of cross-group collaboration in illicit markets. Conversely, members of Outlaw Motorcycle Gangs are more likely to collaborate across groups when markets overlap, suggesting the superior capacity and motivation of biker gangs to coordinate criminal activity. Our paper contributes to the understanding of criminal networks as complex, emergent, and spatially embedded market phenomena.
- Criminal groups
- Exponential Random Graph Models
- Illegal drugs
- Illegal markets
- Multilevel networks