智能化、产业转型升级与低碳技术创新
Intelligence,Industrial Transformation and Upgrading and Low-carbon Technology Innovation
侯建 1康围2
作者信息
- 1. 河南农业大学信息与管理科学学院,郑州 450046
- 2. 厦门大学经济学院,厦门 361005
- 折叠
摘要
智能化是推动生态建设和实现经济高质量发展的必由之路.本文基于中国2013-2020年省际面板数据,系统构建了中国区域智能化评价指标体系,进而运用动态门槛模型,以产业转型升级为切入视角,探析产业转型升级的不同水平下智能化对于低碳技术创新的复杂动态影响.结果表明:我国区域智能化水平相对较低,区域异质性明显.智能化对低碳技术创新存在明显的产业转型升级异质门槛效应,较低程度的产业转型升级并不利于助力智能化驱动低碳技术创新.而随着产业转型升级程度的提高并突破临界点,在一定程度上有效发挥了智能化的赋能作用,进而促进低碳技术创新,即存在U型关系.研究对于明晰数字经济时代推进区域低碳技术创新的驱动机制、方案制订与政策实施有着重要的理论和实践意义.
Abstract
Intelligence is a key path to promoting ecological construction and achieving high-quality economic development.This paper,based on panel data from 2013 to 2020 in China,systematically constructs an evaluation index system for regional intelligence.Then,using a dynamic threshold model,from the perspective of industrial transformation and upgrading,it explores the complex dynamic im-pact of intelligence on low-carbon technology innovation at different levels of industrial transformation and upgrading.The results indicate that the level of regional intelligence in China is relatively low,and regional heterogeneity is significant.Intelligence has a significant het-erogeneous threshold effect on low-carbon technology innovation in industrial transformation and upgrading,and a lower degree of indus-trial transformation and upgrading is not conducive to assisting intelligence in driving low-carbon technology innovation.As the degree of industrial transformation and upgrading improves and breaks through critical points,it has effectively played the empowering role of intel-ligence to a certain extent,thereby promoting low-carbon technological innovation,which means there is a U-shaped relationship.This research has important theoretical and practical significance for clarifying the driving mechanism,plan formulation,and policy implemen-tation of promoting regional low-carbon technology innovation in the digital economy era.
关键词
智能化/低碳技术创新/产业转型升级/动态门槛模型Key words
intelligence/low-carbon technology innovation/industrial transformation and upgrading/dynamic threshold model引用本文复制引用
基金项目
河南省高校人文社会科学研究一般项目(2025-ZZJH-170)
河南省高等学校重点科研项目(21A630017)
河南省高等学校哲学社会科学基础研究重大项目(2024-JCZD-21)
河南省高等教育教学改革研究与实践项目(研究生教育类)(2023SJGLX205Y)
河南科技厅软科学研究计划项目(242400410173)
出版年
2024
NETL
NSTL
万方数据