Abstarct<\/p>\n
Drawing on the Emerging Technology Acceptance Model, this study integrates perceived benefits and perceived risks into a unified analytical framework to examine public acceptance of generative artificial intelligence (GenAI). Using three scenario-based survey experiments, the study shows that perceived usefulness and perceived ease of use significantly promote GenAI acceptance, whereas perceived social welfare loss, personal property loss, and technical\u2013ethical conflict all significantly reduce acceptance. The negative effects of these three risk scenarios also differ in magnitude, with personal property loss exerting the strongest inhibitory effect. Heterogeneity analyses further indicate that technology usage behavior moderates these relationships selectively rather than universally, with stronger evidence on the risk side than on the benefit side. In addition, lower confi-dence in regulatory oversight is more clearly associated with stronger risk sensitivity, whereas evidence for stronger benefit sensitivity under higher regulatory trust remains weak. These findings deepen understanding of the differentiated benefit\u2013risk trade-offs shaping attitudes toward emerging AI technologies among Chinese internet users in a online survey context.<\/p>\n
Biography<\/p>\n
Dr. Ning Ma is an Associate Professor in the department of public management, Xi’an Jiaotong University. He earned his PhD degree from Xi’an Jiaotong University. His research interests include public administration and data analysis. He hosted two grants from National Social Science Foundation of China. He published papers in peer-reviewed academic journals, including Computers & Operations Research, IISE Transaction. He is reachable via maning@xjtu.edu.cn<\/p>\n","protected":false},"featured_media":5136,"template":"","meta":{"_acf_changed":false},"schedule":[5],"speaker-category":[6],"class_list":["post-5259","speaker","type-speaker","status-publish","has-post-thumbnail","hentry","schedule-day-1","speaker-category-speakers"],"acf":[],"yoast_head":"\n