新质生产力的形成逻辑、发展路径与关键着力点
Formation Logic,Development Path,and Key Levers of New Quality Productive Forces
彭绪庶1
作者信息
- 1. 中国社会科学院大学商学院,北京 102445
- 折叠
摘要
新质生产力本质上是时代最新科技产业化的产物,代表了生产力发展方向和趋势,新质生产力的形成是生产力代际革命和生产力跃迁的体现.颠覆性创新引致主导技术体系变更是形成新质生产力的技术前提,产生通用目的技术和发生科技革命分别为新质生产力的形成提供了充分条件和时代条件,加速形成新质生产力需要完善的科技转化应用制度体系加以保障.在新一轮科技革命和产业变革背景下,发展新质生产力需要加快实现高水平科技自立自强;推动创新创业融合,搭建技术转化渠道;推动数实深度融合,以数字化智能化为引领;促进数据、科技人才和科技金融三类要素高效流通,实现资源优化配置.
Abstract
New quality productive forces are essentially the industrialization product of the latest technolo-gies of the times,representing the development direction and trend of productive forces.The formation of new quality productive forces embodies the intergenerational revolution and transition of productive forces.The technological system changes led by disruptive innovation are technological prerequisites for the formation of new quality productive forces.The generation of technologies with universal purposes and the occurrence of technological revolution provide sufficient and contemporary conditions,respectively,for the formation of new quality productive forces.The formation of new quality productive forces necessitates the institutional condi-tions created by the systems of research achievement transformation and application.In the context of a new round of technological revolution and industrial transformation,the development of new quality productive forces requires high-level technological self-reliance and self-improvement.Innovation and entrepreneurship should be integrated to create channels for technological transformation.The deep integration of the digital economy and the real economy should be promoted to give play to the leading role of digital intelligence.The efficient circulation of data,technology talents,and technology finance should be boosted to optimize resource allocation.
关键词
新质生产力/创新/成果转化/科技自立自强Key words
New Quality Productive Forces/Innovation/Achievement Transformation/Technological Self-reliance and Self-improvement引用本文复制引用
基金项目
中国社科院重大创新项目(2023YZD057)
出版年
2024
NETL
NSTL
万方数据