| This study focuses on transnational smuggling, and puts forth an analytical framework from the smugglers' perspective with respect to route selection, focusing primarily on aspects of economic, political, and human geography. It is predicated on three interconnected decision-making domains that constitute the smuggler's operational landscape, namely access, risk and connectivity, which interact to drive the smugglers' perceptions of route attractiveness. The first two domains operate reciprocally, primarily at the national level of analysis, and together both shape and are shaped by the third at the transnational level to form a feedback loop. With respect to connectivity, the convention of the smuggling vector is also introduced.; As a benchmark commodity, heroin is used to demonstrate the utility of this approach with the primary aim of applying and validating the generic geographic smuggling model, meant to be extensible in terms of space, time and commodity. A review of the literature, focusing on the range of smuggled commodities, the nature and evolution of smuggling actors, the complex relationship between smuggling networks and nation-states, and potential modes of transportation by land, water and air. A discussion of the spatial parameters of the global heroin trade itself, with specific reference to the geography of supply and demand, is also undertaken.; For case studies, Afghanistan has been chosen as one of the two largest opium cultivators worldwide, as well as by virtue of its recent and dramatic history. In addition to established cocaine smuggling routes and methods, Colombia has also become a primary heroin source country with respect to the U.S. market. Finally, Nigeria is a known transit hub without being a center of production, demonstrating that factors other than mere proximity can be decisive.; Each case study first examines those geographic and historical factors that shape heroin smuggling at the national level, focusing on the themes of terrain, tradition and domestic turmoil, before considering the various sets of smuggling vectors that proceed outward via various modes and points of transit to their final destinations. This methodology not only highlights data gaps inherent in analyzing black markets, but also optimizes extant sources of information. |
