Has the digital transformation promoted energy-saving-biased technological progress in China's manufacturing sector?

被引:1
|
作者
Lyu, Xichen [1 ]
Pang, Zhen [1 ,2 ]
Xu, Yingying [1 ]
机构
[1] Harbin Univ Sci & Technol, Harbin, Heilongjiang, Peoples R China
[2] Harbin Univ Sci & Technol, Sch Econ & Management, 4 Linyuan Rd, Harbin 150081, Heilongjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Chinese manufacturing; digital transformation; energy-saving-biased technological progress; digital transformation phase; TECHNICAL CHANGE; ENVIRONMENT; EMPLOYMENT; GROWTH; DEA;
D O I
10.1080/00036846.2024.2315093
中图分类号
F [经济];
学科分类号
02 ;
摘要
In the context of 'Digital China' and the 'Dual-Carbon' targets, there is an escalating need for energy saving and pollution reduction in China's manufacturing sector. By optimizing resource allocation, enhancing precision in energy consumption monitoring and fostering the integration of traditional production factors, digital elements are pivotal in steering the sector towards energy technology progress, thereby affecting overall energy usage and carbon emissions. This study leverages panel data from 2009 to 2020 to quantify the manufacturing sector's digital transformation and its energy-saving technology progress bias. It also examines the catalytic role of digital transformation in fostering energy-saving technological progress. The findings reveal the following: (1) The trajectory of technological progress within China's manufacturing sector has progressively improved and predominantly demonstrates an energy-saving bias. (2) Digital transformation has significantly catalysed energy-saving-biased technological progress across various manufacturing subsectors, this conclusion is still significantly credible after a series of robustness tests. (3) Heterogeneity analysis reveals that as the digital transformation progresses from collaborative innovation to comprehensive digitalization phases, it has dramatically optimized the energy-saving-biased technological progress in various industries, especially in pollution-intensive industries. These insights offer substantial implications for policy formulation and industrial evolution.
引用
收藏
页数:18
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