摘要
Abstract
The impact of new quality productivity development on the labor structure in manufacturing is undergoing changes.Based on data from China's A-share listed manufacturing companies from 2011 to 2022,and referencing existing measurement methods for the new quality productivity development index,this study employs benchmark regression analysis and backpropagation(BP)neural networks to analyze the influence of new quality productivity development on labor structure.The findings reveal that new quality productivity exerts substitution and iteration effects on low-and medium-skilled traditional labor in manufacturing.At the same time,it promotes the growth of new-type labor in the sector.According to the predictive results of the BP neural network model,the positive predictive effect of new quality productivity development is the most significant.Its positive impact on general manufacturing far exceeds that on high-tech industries,and its beneficial effect on manufacturing enterprises in the central region is much greater than that in the eastern and western regions.Additionally,its positive influence on industries such as pharmaceutical manufacturing,food manufacturing,and automobile manufacturing is substantially stronger than on chemical manufacturing and information and communication technology(ICT)manufacturing.关键词
新质生产力/制造业/劳动力结构/影响研究/BP神经网络Key words
New quality productivity/Manufacturing/Labor structure/Impact study/BP neural network分类
社会科学
