Dr. Usman studies consumers’ responses to new technologies in marketing using experimental research designs. He is currently working on projects related to generative AIs and has published an article on Behavioral Research on AI in Marketing recently in Foundations and Trends in Marketing.

Projects:

• Artificial Intelligence in Marketing and Consumer Behavior Research
  • Brief Description: This project reviewed the behavioral research on AI in marketing and presented a synthesis of what the current trends are, including the predominant dependent variables being measured by researchers, theories being used to explain the findings and the types of behavioral research design used in the research. The manuscript concludes with our key observations and identifies future research directions, raises interesting questions that are yet to be answered by behavioral research on AI in marketing, and suggests means to enhance the methodology and behavioral research designs currently being used in marketing.
    View Article: TaeWoo Kim, Umair Usman, Aaron Garvey and Adam Duhachek (2023), “Artificial Intelligence in Marketing and Consumer Behavior Research”, Foundations and Trends® in Marketing: Vol. 18: No. 1, pp 1-93.

• The Persuasive Power of AI Ingratiation: A Persuasion Knowledge Theory Perspective
  • Brief Description:  This research examines the emerging marketing tactic of AI ingratiation of humans and reveals that AI ingratiation leads to increased consumer acceptance of product recommendations. Using behavioral experiments, including online studies and a real human-AI interaction, we show that these ingratiation effects are moderated by the extent to which AI is anthropomorphized. Our findings advance the current knowledge about human-AI interaction in consumption contexts and finds support for our hypotheses based on the Persuasion Knowledge Model and Anthropomorphism literature. Specifically, we find that consumers perceive ingratiation by human-like (vs. machine-like) AI systems to be more driven by ulterior motives, thereby activating consumer defense mechanisms against ingratiation attempts. Our theory and findings elucidate how AI design features serve to strengthen or weaken consumer resistance to persuasion.