Development of a product-counterfeiting incident cluster tool

Abstract

There is growing awareness of the increasing scope, scale, and threat of product counterfeiting. Awareness is also growing for the drafting of countermeasures that specifically address deceptive and non-deceptive counterfeiting. This research developed a method and tool to help review, understand, and cluster product-counterfeiting incidents. The intent is to assist brand owners and government agencies select effective countermeasures. The research builds upon earlier work that developed a typology of product counterfeiters, counterfeiting and offender groups, which is used here to create an original tool to organize and cluster the incidents. While incident data is often confidential or classified, several methods were used to access open-source information in order to apply the tool. First, a set of examples was selected from the literature to demonstrate the tool in principle. Second, in order to examine a complete data set of counterfeiting incidents, the open-source cases of the U.S. National Intellectual Property Rights Center were gathered, reviewed, coded, and analyzed to demonstrate the application of the tool. A Product-Counterfeiting Incident Cluster Tool was developed which is consistent with Routine Activity Theory and Situational Crime Prevention and is intended to identify efficient and effective countermeasures. It is important to establish the type of fraud and the fraudster when developing anti-counterfeit strategies. The insight gained from assessing the specific product-counterfeiting incidents will assist in the profiling and selection of effective industry and government countermeasures. The scientific basis for understanding product counterfeiting is broadened by applying the outlined concepts and describing incidences through the clustering tool.