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人工智能赋能农业企业创新能力基于知识创造与知识重组的双路径研究

Artificial intelligence and the innovation capability of agricultural enterprises: a dual-path study based on knowledge creation and knowledge recombination

  • 摘要: 基于动态能力理论,本文利用2010—2024年中国农业类上市公司数据,构建农业企业专属人工智能词典,并采用双向固定效应模型、双重机器学习等方法考察人工智能对农业企业创新能力的影响。研究发现:人工智能能够显著提升农业企业创新能力,基准回归的估计弹性为0.137,且该结论经过一系列稳健性检验与内生性处理后依然成立。机制检验表明,知识创造与知识重组是人工智能赋能农业企业创新的重要渠道。异质性分析表明,人工智能的创新促进作用在大型企业和非国有企业中更为明显,不同成长性企业之间未表现出显著差异;在知识产权保护水平较高、地形起伏度较低和受灾程度较高的地区,其促进作用也相对突出。通过创新路径与方式的分析中发现,人工智能能够促进突破式创新和渐进式创新,其中对渐进式创新的促进作用更强;人工智能显著促进企业独立创新,但对联合创新的影响未通过显著性检验。基于上述结论,应加快人工智能在农业企业中的深度应用,完善数据、人才和数字基础设施等配套条件,实施分层分类的扶持政策,并统筹推进渐进式创新与突破式创新,不断提升农业企业创新能力与市场竞争力。

     

    Abstract: Drawing on dynamic capability theory, this study uses data from Chinese listed agricultural enterprises from 2010 to 2024, constructs an artificial intelligence dictionary tailored to agricultural enterprises, and employs two-way fixed effects models and double machine learning to examine the impact of artificial intelligence on the innovation capability of agricultural enterprises. The results show that artificial intelligence significantly enhances the innovation capability of agricultural enterprises, with an estimated elasticity of 0.137 in the baseline regression. This finding remains robust after a series of robustness checks and endogeneity treatments. Mechanism analysis indicates that knowledge creation and knowledge recombination are important channels through which artificial intelligence enhances the innovation capability of agricultural enterprises. Heterogeneity analysis shows that the innovation-enhancing effect of artificial intelligence is more pronounced in large enterprises and non-state-owned enterprises, while no significant differences are observed among enterprises with different levels of growth. The effect is also relatively stronger in regions with higher levels of intellectual property protection, lower topographic relief, and greater disaster severity. Analysis of innovation paths and modes shows that artificial intelligence promotes both breakthrough innovation and incremental innovation, with a stronger effect on incremental innovation. Artificial intelligence significantly promotes independent innovation, whereas its effect on collaborative innovation is not statistically significant. Based on these findings, efforts should be made to accelerate the deep application of artificial intelligence in agricultural enterprises, improve supporting conditions such as data, talent, and digital infrastructure, implement tiered and targeted support policies, and coordinate the development of incremental and breakthrough innovation to continuously enhance the innovation capability and market competitiveness of agricultural enterprises.

     

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