Does artificial intelligence improve energy productivity in China's industrial sector? Empirical evidence based on the spatial moderation model

被引:0
作者
Rong, Jing [1 ,2 ]
Wang, Wei [2 ]
Zhang, Haijun [2 ]
机构
[1] Anhui Acad Social Sci, Hefei, Peoples R China
[2] Chaohu Univ, Sch Econ & Law, Hefei, Peoples R China
基金
中国国家社会科学基金;
关键词
Industrial intelligence; total factor energy productivity; spatial moderation model; global Malmquist-Luenberger; non-radial directional distance function; China; FOREIGN DIRECT-INVESTMENT; CARBON EMISSIONS; ECONOMIC-GROWTH; PERFORMANCE; IMPACT; GENERATION; EFFICIENCY; QUALITY;
D O I
10.1177/0958305X231177732
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study investigates the impacts of industrial intelligence on the total factor energy productivity (TFEP) using extended STIRPAT and spatial moderation models for China's industrial sector. The results show that TFEP and industrial intelligence are both increasing, and industrial intelligence positively affects TFEP, for every 1% increase in industrial intelligence will lead to TFEP growth by 0.121% in the study area and 0.031% in surrounding areas. Environmental regulation, industrial upgrading, and advanced human capital all function as helpful moderators between industrial intelligence and TFEP, that is, for every 1% increase in environmental regulation, industrial upgrading, and advanced human capital, the growth of TFEP caused by industrial intelligence enhanced by 0.003%, 0.009%, and 0.022% in study area and 0.005%, 0.042%, and 0.054% in surrounding areas.
引用
收藏
页码:4026 / 4048
页数:23
相关论文
共 62 条
  • [1] Impact of Industrial Intelligence on Total Factor Productivity
    An, Ke
    Shan, Yike
    Shi, Sheng
    [J]. SUSTAINABILITY, 2022, 14 (21)
  • [2] Do Artificial Intelligence Applications Affect Carbon Emission Performance?-Evidence from Panel Data Analysis of Chinese Cities
    Chen, Ping
    Gao, Jiawei
    Ji, Zheng
    Liang, Han
    Peng, Yu
    [J]. ENERGIES, 2022, 15 (15)
  • [3] How does the use of industrial robots affect the ecological footprint? International evidence
    Chen, Yang
    Cheng, Liang
    Lee, Chien-Chiang
    [J]. ECOLOGICAL ECONOMICS, 2022, 198
  • [4] Cheng H., 2022, Econ. Anal. Lett., V1, DOI [10.58567/eal01010003, DOI 10.58567/EAL01010003]
  • [5] Research on the impact of circular economy on total factor carbon productivity in China
    Cui, Tiening
    Zhang, Yang
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (52) : 78780 - 78794
  • [6] The carbon impact of artificial intelligence
    Dhar, Payal
    [J]. NATURE MACHINE INTELLIGENCE, 2020, 2 (08) : 423 - 425
  • [7] Dams
    Duflo, Esther
    Pande, Rohini
    [J]. QUARTERLY JOURNAL OF ECONOMICS, 2007, 122 (02) : 601 - 646
  • [8] An empirical research on the relationship amongst renewable energy consumption, economic growth and foreign direct investment in China
    Fan, Weiyang
    Hao, Yu
    [J]. RENEWABLE ENERGY, 2020, 146 : 598 - 609
  • [9] Input Digitization of the Manufacturing Industry and Carbon Emission Intensity Based on Testing the World and Developing Countries
    Fang, Hui
    Jiang, Chunyu
    Hussain, Tufail
    Zhang, Xiaoye
    Huo, Qixin
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (19)
  • [10] How does renewable energy technology innovation affect the upgrading of industrial structure? The moderating effect of green finance
    Ge, Tao
    Cai, Xuesen
    Song, Xiaowei
    [J]. RENEWABLE ENERGY, 2022, 197 : 1106 - 1114