HN RESEARCH GROUP
Exploring the evolving relationships between consumers, technology, and emergent digital experiences.
We are currently developing a comprehensive digital repository that will provide access to our complete body of work. The repository will include journal publications, working papers, book chapters, and conference presentations spanning over three decades of our research in digital marketing and online consumer behavior.
Donna L. Hoffman is the Louis Rosenfeld Distinguished Scholar and Professor of Marketing, Emeritus and was the co-director of the Center for the Connected Consumer at the George Washington School of Business in Washington, D.C. Her current research is focused on using conceptual, empirical and computational approaches to understand consumer experience with AI. Her work has been published in all of the field's top journals and enjoys wide impact with over 42,000 Google scholar citations. Professor Hoffman has been awarded many of the field's most prestigious awards, including being named a Fellow of the Society for Consumer Psychology, the Robert B. Clarke Educator of the Year Award from the DMEF, the Sheth Foundation/Journal of Marketing Award for long-term contributions to the discipline of marketing, the Stellner Distinguished Scholar Award from the University of Illinois, the William O'Dell/Journal of Marketing Research Award for long-term research impact, and others. Her PhD is from the L.L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill and she was a faculty member at Columbia University, the University of Texas, Vanderbilt University and the University of California before joining George Washington University. She has also spent sabbatical visits at UCLA, Stanford, USC, and UCSD. She was named a Distinguished Graduate Alumnus of UNC in 2002.
Consumer experience with AI using conceptual, computational, and empirical approaches. Digital marketing strategy and online consumer behavior.
Thomas P. Novak is the Denit Trust Distinguished Scholar and Professor of Marketing, Emeritus and was the co-director of the Center for the Connected Consumer at the George Washington University School of Business (GWSB) in Washington, D.C. Professor Novak received his A.B. in Psychology from Oberlin College in 1977 and his M.A. (1980) and Ph.D. (1984, in quantitative psychology with a formal minor in Biostatistics) from the L.L. Thurstone Psychometric Laboratory at the University of North Carolina, Chapel Hill. He was recognized as a University of North Carolina Distinguished Graduate Alumni in 2002. An internationally recognized scholar in Web-based commerce, Dr. Novak has published extensively on the subject in top academic journals in a range of scholarly disciplines. His work has had global impact with over 40,000 citations in Google Scholar. He is an area editor for the Journal of Consumer Research, and is on the editorial boards of the Journal of Marketing, the Journal of Advertising, and the Journal of Interactive Marketing. He has received numerous prestigious research awards, including the Sheth Foundation/Journal of Marketing Award for long term contributions to the discipline of marketing, the Lazaridis Prize, the Stellner Distinguished Scholar Award, the Robert D. Buzzell MSI Best Paper Award Honorable Mention. Prior to joining the faculty at George Washington University in 2013, Dr. Novak served on the faculties of the University of California Riverside, Vanderbilt University, and Southern Methodist University. He has been a visiting scholar at Paul Allen's Interval Research Corp., the University of Hong Kong, University of California San Diego, USC Annenberg School, and Stanford University. Prior to joining academia, he spent five years at Young & Rubicam, New York.
Consumer behavior in online environments, Internet of Things, and machine learning methods for understanding emergent consumer experiences.
Developing new frameworks for understanding consumer-object relationships in the Internet of Things through assemblage theory approaches.
Pioneering applications of flow theory to understand optimal experiences in digital environments and online consumer behavior.
Investigating how artificial intelligence transforms consumer experiences through computational social science and machine learning methods.
Foundational research in web-based commerce, social media marketing, and digital consumer engagement spanning three decades.
Exploring emergent experiences and relationship journeys between consumers and smart objects in connected environments.
Applying topological data analysis, natural language processing, and visualization techniques to understand consumer behavior.