生成式AI、任务类型与绿色产业企业员工绩效OACHSSCD

Against the backdrop of the in-depth advancement of the"Dual Carbon"goals and the accel-erated implementation of digital transformation in the green industry,generative AI has emerged as an important digital tool for empowering knowledge-based work in enterprises.Exploring its impact on the job performance of employees in green industry enterprises constitutes a crucial research for the innova-tive management of green enterprises and the digital development of the industry.Based on the Task-Technology Fit theory,and taking the knowledge-based work of employees in green industry enterprises as the research context,this study adopted a 2×2 between-subjects behavioral experiment to examine the influence of structured and unstructured task types on human-AI collaboration performance.The re-sults show that the application of generative AI can significantly improve employees'job performance in both types of tasks,and task type exerts a significant moderating effect on the performance empower-ment of generative AI.Specifically,generative AI has a stronger effect on improving job performance in structured tasks compared with unstructured ones.This study clarifies the task heterogeneity character-istics of generative AI in empowering the job performance of employees in green industry enterprises,expands the application of the Task-Technology Fit theory in the context of generative AI,and also pro-vides empirical evidence for green enterprises to carry out differentiated human-AI collaboration config-uration in knowledge-based work and improve employees'job performance in their innovative manage-ment practices.