AI赋能视角下极限目标设置的驱动机制及其影响效应OACHSSCD

As artificial intelligence(AI)is increasingly adopted and deployed in enterprises,many teams are moving away from traditional goal-setting methods.In AI-enabled contexts,they are instead using stretch goals to stimulate employee and team creativity.However,the emergence of such goals in AI-enabled settings and their effects on creativity remain underexplored and lack empirical testing.Accordingly,this study aims to:(1)uncover how stretch goals emerge in AI-enabled settings;(2)draw on socio-technical systems theory to examine the mediating role of individual exploratory learning between stretch goals and individual creativity,as well as the moderating role of perceived AI usefulness;(3)draw on the same theory to test the mediating role of human-AI collaboration between stretch goals and team creativity,along with the moderating role of human-AI role clarity;and(4)verify the application of the formation mechanism and impact effects of stretch goals.The core conclusions derived from the"environmental stimuli → goal setting→ employee behavioral outcomes"framework are then applied to practical scenarios,offering a reference for enterprises seeking to enhance individual and team creativity.The findings aim to fill the research gap concerning stretch goals in AI-enabled contexts and guide managers in leveraging AI to overcome constraints typically associated with stretch goals.