人工智能技术对新能源企业资源配置效率提升的影响OA

Driven by the dual demands of global energy transition and environmental governance,artificial intelligence(AI)has emerged as a core force for upgrading the efficiency of new energy enterprises.Using data from new energy companies listed on China's Shanghai and Shenzhen A-share markets from 1991 to 2023,this study constructed a theoretical model integrating AI technology and re-source allocation of new energy enterprises.It employed the Richardson residual method to measure the resource allocation efficiency of new energy enterprises and adopted the fixed-effect model to empirically analyze the key impact and underlying mechanisms of AI tech-nology on enhancing this efficiency.The results showed that:(1)AI technology had a significant and positive correlation with the re-source allocation efficiency of new energy enterprises,yielding an average promotion effect of approximately 2.58%.This conclusion re-mained valid after a series of robustness tests.(2)Heterogeneity analysis indicated that the impact of AI technology on enhancing re-source allocation efficiency was most pronounced in enterprises in the western region,whereas the effects in the eastern and central re-gions were relatively weaker.Furthermore,state-owned enterprises leveraged resource and policy advantages to increase investment in AI technology,while private enterprises accurately optimized resource allocation through flexible cooperation models;both served as pivotal drivers of industrial growth.(3)Mechanism analysis revealed that AI technology mitigated resource misallocation and improved allocation efficiency by enhancing human capital quality,increasing R&D investment intensity,and advancing digital financial services level.Therefore,in the new era of China's economic and energy transition,policymakers should firmly seize the new opportunities brought by the development of AI technology and integrate AI into new energy development.At the same time,it is necessary to strengthen policy guidance and support,improve digital inclusive finance policies,and optimize human resource structures to achieve a regional development pattern characterized by coordination and mutual benefit.