通过人工智能实现可持续发展:研究绿色创新的吸收能力途径
Wei Zhang1, Haowen Xu1, Oksana Grebinevych2
1School of Economics and Management, Xi'an University of Technology, Xi'an, 710054, China.
Journal of environmental management
|April 8, 2025
概括
人工智能 (AI) 能力通过改善企业吸收外部知识的方式来增强绿色创新 (GI). 当企业面临更大的环境异质性 (EH) 时,这种影响更为强烈.
科学领域:
- 商业和管理的管理.
- 环境科学 环境科学
- 技术与创新 技术与创新
背景情况:
- 企业在利用人工智能 (AI) 来实现绿色创新 (GI) 方面面临着挑战.
- 对于将AI能力与GI联系在一起的机制缺乏明确的理解.
- 吸收能力理论为探索这些关系提供了一个框架.
研究的目的:
- 研究人工智能能力如何影响绿色创新 (GI).
- 检查潜在吸收能力 (PAC) 和实现吸收能力 (RAC) 的调解作用.
- 探索环境异质性 (EH) 对AI-GI关系的缓和效应.
主要方法:
- 开发一个调节调解模型.
- 经验分析使用来自361家中国企业的数据.
- 基于吸收能力理论. 吸收能力理论.
主要成果:
- 人工智能能力通过PAC和RAC积极影响GI.
- 环境异质性 (EH) 显著放大了PAC和RAC的调解效应.
- 具有人工智能能力的公司表现出增强的知识吸收能力,特别是在高EH的情况下.
结论:
- 人工智能能力对于通过增强吸收能力来推动GI至关重要.
- 环境异质性起到了关键的调节作用,加强了人工智能对地理标志的积极影响.
- 这项研究为寻求通过人工智能采用和战略知识管理实现GI的公司提供了见解.
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