报告题目：1+ 1< 2? Unveiling the impact of AI-assisted disclosure on service satisfaction in professional services.
报告人： 李屹博士（华中科技大学）
时间：2026年 3月30日 9:30－10:10
地点：管理学院A南507
报告内容摘要：
AI-assisted human employees have become widespread, particularly in professional services such as healthcare, law, and management consulting. However, little is known about how consumers respond to AI-assisted employees in professional services. This study examines how disclosing AI-assisted employees in professional services impacts service satisfaction and explores the underlying mechanisms and boundary conditions. Through six experiments (N = 1664), we find that disclosing (vs. non-disclosure) AI-assisted employees leads consumers to infer that the employees possess lower professional competence, negatively affecting satisfaction. This effect disappears when consumers perceive AI to have high capability. Moreover, the negative impact is mitigated when a complementary capability or self-selection disclosure strategy is employed. This research provides new insights into the impact of human-AI collaboration and AI disclosure in service delivery. The findings also offer practical implications for organizations and employees using AI assistance in professional service.
【李屹个人简介】
李屹，华中科技大学博士研究生，研究领域为人工智能营销、人智协同、GAI商业应用，在《International Journal of Information Management》《Journal of Retailing and Consumer Services》《International Journal of Contemporary Hospitality Management》等重要学术期刊发表学术论文四篇，并参与多项国家级重点课题的研究。
报告题目：The desire to bargain: Upward comparison increases aversion to algorithmic decision-making in product disposition
报告人： 梁嘉明博士（中山大学）
时间：2026年 3月30日 10:10－10:50
地点：管理学院A南507
报告内容摘要：
Algorithmic systems are now widely deployed in product disposition channels, from used-car platforms to electronics trade-in services. As consumers increasingly encounter algorithms that assess the value of their belongings, understanding when and why consumers prefer algorithmic versus human decision-making has become critically important. This research examines how social comparisons influence consumer preference for algorithmic versus human decision-making in product disposition. Drawing on compensatory control theory, six studies integrating experimental research and secondary data analysis reveal an asymmetric pattern: consumers engaging in upward (vs. downward) comparison show stronger aversion to algorithmic decision-making. This occurs because upward comparers are more motivated to seek bargaining—a compensatory strategy for perceived lack of control—and thus prefer human decision-makers who are perceived as more subjective and negotiable. Moreover, the perceived subjectivity of the decision context moderates these effects.
【梁嘉明个人简介】
梁嘉明，中山大学管理学院博士生，研究领域为数智营销与消费者行为，在《南开管理评论》《营销科学学报》《Journal of Business Research》《Journal of Business and Psychology》《Journal of Hospitality & Tourism Research》《Electronic Commerce Research and Applications》等国内外重要学术期刊发表学术论文九篇。参与国家自然科学基金面上项目、国家社会科学基金一般项目、及教育部人文社会科学研究规划基金项目等课题。
报告题目：AI appreciation effect: how contagious diseases influence medical AI adoption
报告人：胡颖博士（中国人民大学）
时间：2026年 3月30日 10:50－11:30
地点：管理学院A南507
报告内容摘要：
Despite the promising potential of AI to revolutionize healthcare, patients’ aversion to AI remains widespread. This research explores how experiencing contagious diseases, a major challenge for public health, affects patient preferences for medical care providers. Across five studies (N = 4,470, with a combination of one large-scale field survey and four randomized behavioral experiments), we provide converging evidence that individuals experiencing contagious (vs. noncontagious) diseases exhibit a significant preference for AI-based diagnostic and therapeutic interventions over human physicians. This AI appreciation effect is driven by anticipated interpersonal stigma (Study 2). However, it weakens when patients perceive low physician occupational exposure risk, which reduces anticipated interpersonal stigma (Study 3), and when they perceive algorithmic bias, which undermines trust in AI (Study 4). This research contributes to the literatures on AI appreciation and AI ethics and offers actionable insights for healthcare technology marketers and public health organizations by identifying disease type as a motivational driver of medical AI adoption and by demonstrating how institutional communications about physician safety and algorithmic bias can modulate this preference.
【胡颖个人简介】
胡颖，中国人民大学商学院博士生，研究领域为人工智能营销、人机交互、健康消费，在《International Journal of Research in Marketing》《营销科学学报》等重要学术期刊发表学术论文三篇。主持美国市场营销协会项目，并参与多项国家级课题的研究。
欢迎有兴趣的教师，全体博士生、硕士生参加。
管理学院人力资源中心
