Unlocking Environmental Sustainability With Generative Artificial Intelligence: Insights From Resource Orchestration Theory
基于260家中国高科技制造企业调查数据，研究发现生成式人工智能通过资源编排能力与脱碳能力的连续中介作用提升环境绩效，且环境动态性增强脱碳能力的中介效应。
Despite the potential of generative artificial intelligence (GenAI) to unlock environmental sustainability, many firms still struggle to translate this potential into actionable practices. It is imperative to gain a deeper insight into the mechanisms by which GenAI unlocks environmental performance (EP). To tackle this issue, we propose a novel research framework grounded in resource orchestration theory (ROT). Drawing on survey responses from 260 high-tech manufacturing firms in China, we find that resource orchestration capabilities do not independently mediate the GenAI usage–EP relationship but instead require the support of decarbonization capabilities (DCs) to jointly serve as serial mediators. Moreover, environmental dynamism enhances the mediating effect of DCs in the GenAI usage–EP relationship. Our research elucidates the underlying mechanisms and boundary conditions associated with the use of GenAI to achieve environmental sustainability from the perspective of ROT, contributing to the field of technology-enabled management research. Our findings also provide valuable insights to guide firms in their transition towards carbon neutrality.