2017 A-CAPP CENTER
RESEARCH LAB
DESCRIPTIONS
RESEARCH LABS
Anatomy of a Research Project: The Product Counterfeiting
Database
The Product Counterfeiting Database (PCD) utilizes open source
information on product counterfeiting crimes committed in the United States
to explore the various elements of the schemes, offenders, and victims
involved in those crimes. This research lab will provide an A-Z description of
this signature A-CAPP Center research project including the PCD research
process, development, maintenance, and data analysis, as well the ability to
draw evidence-based implications from the research for policy and practice.
Analyzing Internet Sales of Cigarettes
This research includes a multi-phase investigation into the sale and distribution of
cigarettes through the Internet. The goal of the current study phase is to gather
detailed information about websites that offer cigarettes for sale to American
consumers. The second phase of this study will involve a series of chemical
forensic analyses that will be used to compare the products offered on these sites
to legitimate cigarettes sold in stores. The third and final phase of the study will be
an experimental investigation of the factors that have the greatest influence on
consumer decision-making.
Advertisements for Counterfeit Products on Social Media
This research explores the growing prevalence of advertisements for counterfeit
products on social media platforms, focusing on the ability of consumer to
distinguish between counterfeit and legitimate advertisements and their willingness
to purchase counterfeits, particularly those illegally reproducing university
trademarks.
State Level Enforcement of Counterfeiting Laws
The variation and inconsistency in the application of existing anti-counterfeiting
legislation across states is explored in this research project, focusing specifically on
implications for the ability of brand owners to successfully enforce their trademark
rights, and law enforcement and prosecutors use of these tools.
Finding Illicit Goods Online Using Big Data
Chinese e-commerce websites are explored through the development of an
adaptive and predictive algorithm and the collection of large amounts of
information from e-commerce sites. This “big data” research project aims to
develop a set of web-based tools that can assist in the early identification of
potentially illicit product listings. Additionally, the data collected will allow the
team to identify product- and messaging-specific trends that develop across the
range of illicit goods promoted through these websites.
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