Weize Yin

Weize Yin is a Ph.D. candidate in Marketing at the Carlson School of Management, University of Minnesota, advised by Professor Yi Zhu. He is on the academic job market during the 2026–27 cycle and expects to graduate in 2027.

His research studies how emerging technologies, especially large language models (LLMs), are reshaping markets, with particular attention to the strategic implications of their limitations. His work combines large-scale LLM experiments, representation engineering, analytical modeling, and market simulation, sitting at the intersection of marketing and computer science. In his job market paper, “Strategic Design of Shopping LLMs Under Prompt-Induced Evaluation Gap,” he finds that LLM-powered shopping assistants can evaluate the same product differently depending on how a request is phrased, and shows that this prompt-induced evaluation gap can serve as a strategic design lever rather than a flaw to be eliminated. His active pipeline extends this agenda: in collaboration with one of the largest food-delivery platforms in China, he is building LLM digital twins of consumers from real purchase data to simulate markets at scale, and, with consumer-behavior researchers, he studies how consumers perceive the human’s contribution in human-AI collaboration.

Beyond LLMs, his work extends to the economics of other digital markets, including research on news media (under a second major revision at Marketing Science) and on sustainability in platform markets.

Research Interests: Shopping LLMs, LLM Digital Twins, Human-AI Interaction, Information Economics, Sustainability