FINDING YOUR FOCUS - American Marketing Association

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4 FINDING YOUR FOCUS June 5–8, 2011 • Palm Desert, CA CONFERENCE PROGRAM Sunday, June 5 7:45–8:15 am Breakfast 8:15 am–12:15 pm Preconference Tutorials MarketingPower.com/artforum (see website for complete descriptions) A. Introduction to Bayesian Statistics and Marketing Greg M. Allenby, The Ohio State University B. Introduction to Discrete Choice Modeling Brian Orme, Sawtooth Software Jon Pinnell, MarketVision Research C. Introduction to R for Marketing Research Eric Zivot, University of Washington Chris Chapman, Microsoft D. Introduction to Text Mining and Sentiment Analysis Matt Taddy, University of Chicago 12:15–1:00 pm Lunch on Your Own 1:00–5:00 pm Preconference Tutorials (see website for complete descriptions) E. Advanced Computer Simulations for Improved Marketing Decisions David G. Bakken, KJT Group F. Analyzing Network Data Wolfgang Jank, University of Maryland G. Structural Modeling of Forward-Looking Consumer Behavior Andrew Ching, University of Toronto 5:00–5:30 pm New Attendee Orientation 5:30–7:00 pm Welcome Reception Register by May 5 and save!
Monday, June 6 22ND ANNUAL Advanced Research Techniques Forum ART2011 7:45–8:15 am Breakfast 8:15 am–12:00 pm Monday Morning Sessions SESSION 1: EMERGING METHODS Evolving Viral Marketing Strategies William Rand, University of Maryland Forrest Stonedahl, Northwestern University Uri WIlensky, Northwestern University As the growth of social media accelerates, viral marketing as a mechanism to spread an idea or product through online social venues has become increasingly important. However, in a complex social network, which consumers should be targeted to maximize the reach and increase the speed of diffusion within these systems? We explore a way to select consumers on the basis of local network properties, and then examine how these network properties affect the ability of consumers to influence their social networks. In the end, to provide an answer to the question of which consumers to target, we construct a tool that uses a combination of social network metrics, agent-based modeling and genetic algorithms, to discover a robust solution that we demonstrate on several social networks, including Twitter and a college alumni social networking site. Exponential Random Graph Models of Linked Records in a Consumer Panel Mark Kinnucan, The Nielsen Company Christina Gutierrez, The Nielsen Company Recent concerns about online panel quality have prompted efforts to ensure that panels are free of duplicate registrations; these efforts have become a standard practice in the market research industry. In the process of identifying duplicates, the duplicate records are linked. By studying the networks formed by these links, we can increase our understanding of the threat posed by duplicates in a panel. Recent advances in estimation, inference and software availability of exponential random graph models (ERGMs) have greatly increased their utility for analyzing social and other networks. This presentation describes the use of ERGMs (also called p* models) to explore the panelist attributes and network microstructures that characterize duplication within an active online panel. MarketingPower.com/artforum 5
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