摘要
推进新型工业化是实现中国式现代化的关键路径,新质生产力对其具有战略驱动作用。选取新质生产力关键要素为自变量,工业创新投入为因变量,基于长三角7个标杆城市2009—2023年面板数据,通过多元线性回归模型分析要素的线性关系,借助神经网络模型捕捉要素间的非线性关联,最后采用两个模型对工业创新投入进行预测,发现神经网络模型在拟合优度与预测精度上更优。研究表明,新质生产力要素协同赋能长三角工业创新,其中科技创新与高素质劳动者要素是核心动力,为长三角区域工业创新发展政策的制定提供依据。
Selecting the key elements of new quality productive forces as independent variables and industrial innovation investment as the dependent variable,based on the panel data of seven benchmark cities in the Yangtze River Delta from 2009 to 2023,the linear relationships of elements is analyzed by multiple linear regression model,and the nonlinear correlation between elements is captured with the help of neural network model.Finally,the two models are used to predict industrial innovation investment,and it is found that the neural network model is better in terms of goodness of fit and prediction accuracy.The research shows that the synergy of new quality productive forces empowers industrial innovation in the Yangtze River Delta,among which scientific and technological innovation and high-quality workers are the core driving forces,which provides an important basis for the formulation of industrial innovation and development policies in the Yangtze River Delta region.
作者
庄苏
申珂
应婷婷
朱可歆
Zhuang Su;Shen Ke;Ying Tingting;Zhu Kexin(School of Mathematical Sciences,Nanjing Normal University of Special Education,Nanjing Jiangsu 210038,China)
出处
《现代工业经济和信息化》
2025年第12期1-5,共5页
Modern Industrial Economy and Informationization
关键词
新质生产力
工业创新投入
长三角区域
多元线性回归
神经网络
new quality productive forces
industrial innovation investment
Yangtze River Delta Region
multiple linear regression
neural network
