领导对员工-生成式人工智能建议的反应机制:基于社会比较视角多层次研究OACHSSCD
The differential perception of leaders' response to employee-GenAI advice:A multi-level study based on social comparison view
GenAI参与组织决策已经成为不可阻挡的趋势,但学术界对于GenAI建议采纳的研究尚不完善.在领导决策过程中,领导如何比较员工建议、GenAI建议、员工-GenAI团队建议并进行采纳?领导的感知有何差异?为此,本研究从社会比较理论的视角出发,通过5个子课题的研究,主要解决以下5个问题:1)GenAI建议采纳如何进行界定?2)领导对于员工-GenAI建议采纳存在何种差异?3)领导对于员工-GenAI团队建议采纳的差异如何?4)如何比较员工-GenAI建议采纳的差异效果?5)员工-GenAI协同过程中建议障碍如何差异化影响建议质量?干预策略是否有效?最终,本研究系统构建了领导对于员工-GenAI建议采纳的多层次模型,为跨学科理论发展赋予了新的视角,也为组织优化人智协同决策,降低技术风险提供了实践指导.
The involvement of Generation artificial intelligence(GenAI)in organizational decision-making has become an irresistible trend.However,academic research on the adoption of GenAI advice remains insufficient.In the process of leadership decision-making,how do leaders compare and adopt employee advice,GenAI advice,and employee-GenAI team advice?What differences exist in leaders' perceptions?Grounded in social comparison theory,this study explores how leaders' differing perceptions shape their adoption of advice from employees,GenAI,and human-GenAI teams through five sub-studies:1)How to define the GenAI advice-taking?2)What are the differences in leaders' adoption of employee advice versus GenAI advice?3)How do leaders differ in their adoption of employee-GenAI team advice?4)How to compare the effect of employee-GenAI advice?5)How do advice barriers in employee-GenAI comparisons affect advice quality,and to what extent can intervention strategies mitigate these effects?Ultimately,this study systematically constructs a multi-level model of leaders' adoption of employee-GenAI advice,providing a new perspective for interdisciplinary theoretical development and offering practical guidance for organizations to optimize human-AI collaborative decision-making and mitigate technological risks.
韩翼;马朝翊;宗树伟
中南财经政法大学工商管理学院,武汉 430073中南财经政法大学工商管理学院,武汉 430073西南石油大学经济管理学院,成都 610500
社会科学
领导力GenAI建议建议反应社会比较理论感知差异
leadershipGenAI adviceadvice responsesocial comparison theoryperceptual differences
《心理科学进展》 2026 (4)
626-646,21
国家自然科学基金面上项目(72572169)国家自然科学基金青年项目(72402183).
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