RESEARCH LAB DESCRIPTIONS A-CAPP CENTER BRAND 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 of the application of existing anti-counterfeiting legislation across the 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 11 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.