内容简介：As platforms increasingly deploy AI chatbots for transaction negotiations, how users respond to detecting algorithmic counterparts—rather than human agents—remains poorly understood. Analyzing driver call-in data from a freight platform where drivers independently recognized AI identity during price negotiations, this paper examines how drivers’ detection of AI identity affects deal-closing intentions. Using high-dimensional fixed effects model and robustness checks (e.g. instrumental variable regression model), this study reveals that the detection of AI chatbot during price negotiations increases deal-closing likelihood. Further mechanism analysis demonstrate that this effect stems from cognitive trust: Drivers perceive AI as more efficient (avoiding human delays) and ethically constrained (reducing opportunism), thereby accepting prices they might reject from humans. Counterintuitively, chatbots’ affective expressions diminish trust by triggering skepticism about motive alignment. These findings challenge algorithm aversion theories by showing appreciation dominates in transaction contexts where AI capabilities align with task logic (speed, consistency). We advance human-AI interaction research by establishing context-specific trust mechanisms in bargaining. For practitioners, results suggest redesigning negotiation bots to emphasize cognitive transparency over anthropomorphism—a paradigm shift for AI-mediated deal-making.
主讲人简介：Yi Zhu is Margaret J. Holden and Dorothy A. Werlich Endowed Professor at the Carlson School of Management, University of Minnesota. He received his PhD in Business Administration from the University of Southern California (USC) . His research interests focus on the application of industrial organization models in marketing, online auctions, consumer search, advertising, media slant, sharing economy and Chinese economy. His recent works have appeared or are forthcoming at Marketing Science, Management Science, Journal of Marketing Research etc.. Beyond academic publications, his research has been discussed in Harvard Business Review, Wall Street Journal, Forbes, Fast Company, CBS among others.