人工智能背景下制造业企业全要素生产率的研究

Research on Total Factor Productivity of Manufacturing Enterprises under the Background of Artificial Intelligence

我国人工智能技术的发展主要是从2006年深度学习网络兴起后开始的,由此不断向前推进。从经验上看,自2006年深度学习网络出现后,制造业企业全要素生产率随着其对人工智能技术应用的增加而有所提高。目前,在新一轮科技革命发展下人工智能技术的应用更是直接对制造业企业的全要素生产率产生了重要作用。本文主要通过双重固定效应模型考察人工智能技术对制造业企业全要素生产率的影响,研究结果表明:1) 人工智能技术对制造业企业的全要素生产率存在正向且显著的影响;2) 从地理位置角度来看,在东部地区,人工智能技术对制造业企业的全要素生产率的影响更大。The development of artificial intelligence technology in China primarily commenced following the emergence of deep learning networks in 2006 and has since been consistently advanced. Empirically, the total factor productivity of manufacturing enterprises has shown an increase concomitant with the growing application of artificial intelligence technology subsequent to the advent of deep learning networks in 2006. Currently, amidst a new wave of scientific and technological revolution, the direct impact of artificial intelligence technology on the total factor productivity of manufacturing enterprises is substantial. This study predominantly investigates the influence of artificial intelligence technology on the total factor productivity of manufacturing enterprises through a dual fixed effect model. The research findings indicate that: 1) Artificial intelligence technology exerts a positive and significant influence on the total factor productivity of manufacturing enterprises;2) Geographically, within the eastern region, AI technology demonstrates a more pronounced impact on the total factor productivity of manufacturing enterprises.