Bill Rand
I am an Associate Professor of Marketing at the Poole College of Management at North Carolina State University, where I focus on the application of computer science methods to marketing problems.
Research and Application
My research investigates the diffusion of information. I examine three large questions: (1) How do consumers find things out?, (2) What do consumers do with that information once they have it?, and (3) How do they pass their product insights along to others through online word-of-mouth? Given the explosion of new forms of Internet-based communication technologies, especially with the advent of social media, the answers to these questions are changing and new every day. Digital transformation is and will continue to fundamentally alter the way business is done, and at the base of this transformation is the flow of information among consumers. If we can understand that, then we can better prepare managers for the constantly changing future. I view this process through the lens of complex systems, i.e., that the best way to understand information diffusion is to model the consumers as individuals who are diffusing product insights and marketing information and their interactions, and then observe the emergent outcome of those models, such as product purchases, churn processes, and overall customer lifetime value.
I have applied my research to social media analytics, freemium network-based games, app adoption, not-for-profit donations, and innovation adoption. I have worked with a number of different companies and organizations while studying these research questions, including: Teradata, Expedia, American Red Cross, National Geographic, Brazil's Institute of Applied Economic Research, and many more.
Methods
Besides providing marketing insights to understand the diffusion of information, I am also interested in creating tools, pedagogy, and frameworks to help managers make more data-driven decisions. I teach classes, workshops, and MOOCs on agent-based modeling, digital marketing analytics, and data science, and the application of these methods to marketing and management decisions. In my research, I work extensively with machine learning and artificial intelligence, including causal state modeling, natural language processing, neural networks, and evolutionary computation, and I have written a textbook on agent-based modeling and teach an award winning MOOC based on this book.
- February 14, 2020: Presented "Finding the Bots: Classification and Combat of Social Media Bots and Malignant Users" at Winter AMA.
- January 23-25, 2020: Organized and presented at the first ever Inverse Generative Social Science Workshop.
- November 8, 2019: Presented an "Introduction to Agent-Based Modeling", a hands-on workshop, at the Santa Fe Institute's Annual Applied Complexity Network and Board of Trustees Symposium.
- July 2, 2019: “Is the Grass Greener? On the Strategic Implications of Moving Along the Value Chain for IT Service Providers”, with Anand Gopal, Sabari Karmegan, and Balaji Koka, was accepted for publication at Information Systems Research.
- June 15, 2019: Our paper, "Evidence of Herding and Stubbornness in Jury Deliberations", led by Keith Burghardt and co-authored with Michelle Girvan has recently been accepted for publication at PLoS One.
